Le FTI Tech Trends Report de 2017

1

2017 Tech Trend Report

Emerging technology trends that will influence business, education, politics, government, education and society in the coming year.

A great wave of disruption—anchored in artificial intelligence, robotics, self-driv-ing cars, genomic editing, cognitive computing, the Internet of Things, and big data—is underway. As these technologies move from the fringe to the main-stream, they promise to forever change how we live, work and play.

The 2017 Tech Trends Report, now in its 10th year, focuses on mid- to late-stage emerging technologies that are on a growth trajectory. We have identified more than 150 trends for the coming year across numerous industries, and our broad scope was intentional. In this era of rapidly accelerating technological advance-ment, changes within one industry necessarily impact another. We listen to sig-nals across different sectors, and we encourage you to do the same.

Now more than ever, organizations must examine the potential impact of tech trends. Whether you are a Fortune 500 company, a government agency, a start-up, a university, a foundation or a small business, you must factor the trends in this report into your strategic thinking for the coming year, and adjust your planning, operations and business models accordingly. Failing to track trends in a meaningful way will put your competitive advantage and growth at risk.

This is a robust, detailed document—don’t try to read it in one sitting. Start with the executive summary, and read through the top trends listed for your industry. In the coming weeks, spend some time with all of the trends. I hope you will take your time with our 2017 report, and allow your mind to wander productively.

If you use our trends during an annual meeting to set your strategy for the com-ing year, that’s a good start—but it isn’t enough to safeguard your organization from what’s on the horizon. Organizations that use a formal process to research and track trends are more likely to reduce risk, harness new opportunities and drive change within their fields. What comes next won’t arrive fully formed. The future is yours to build. The Future Today Institute is eager to help you in 2017 and beyond.

This is a robust, detailed document–don’t try to read it in one sitting. Start with the executive summary, and read through the top trends listed for your industry. In the coming weeks, spend some time with all of the trends. I hope you will take your time with our 2017 report, and allow your mind to wander productively.

Amy Webb | Founder | Future Today Institute

2 © 2017 Future Today Institute

Key Takeaways

• Convergence: In 2017, a critical mass of emerging technologies will start to converge, finding advanced uses beyond initial testing and applied research. That’s a signal worth paying attention to. We have devoted extra attention to artificial intelligence, mixed reality, object recognition systems, robots, autonomous vehicles, genomics, bioelectronics and automation.

• Artificial Intelligence: For the first time, artificial intelligence research has advanced enough that it is now a core component of most of our trends. It is vitally important that all decision-makers within an organization familiarize themselves with what AI is, what it is not, and why it matters. We have included an AI Primer in our Trend Re-port this year to aid in that effort.

• Crossover Trends: Leaders must pay attention to signals outside their immediate industries. In 2017 and beyond, technology developments in one industry sector will impact many others. For example, why should a logistics company like UPS or a grocery store chain like Kroger pay close attention to gene editing? Well...advance-ments in the CRISPR gene editing technique will lead to seeds for hyper-productive plants that require just a few feet of space and don’t need much water. Those plants could be farmed within dense urban areas, decreasing a reliance on local grocery stores. This would impact merchants, importers, truck drivers, UPC code sticker pro-viders, and marketing agencies, which would all experience a loss in profit. It would devastate the farmers in countries such as Brazil, Thailand and Mexico, who could rise up or revolt, causing political instability in those countries. This scenario isn’t guaranteed, but it is plausible, and it’s why UPS and Kroger should at least have gene editing on their 2017 radar. We can very easily build scenarios connecting the dots between myriad technologies, companies and industry sectors. For that rea-son, we encourage you to pay close attention to technology trends adjacent to your industry.

EXECUTIVE SUMMARYOur mission at the Future Today Institute is to help organizations see around corners. Leaders tend to make bad decisions under duress. When surprised by a new, disruptive technology, their “flight-or-fight” response system kicks in, and they either ignore important tech trends and imperil their companies, or they act rashly and make ill-informed investments. Right now, all organizations, regardless of their size and scope, should be paying close attention to the fringe so that when a new technology arises, teams can evaluate their options rationally.

© 2017 Future Today Institute3

• New Ecosystems: Many of the areas we’ve included in this report during the past decade have moved from the fringe towards the mainstream. In the process entire new ecosystems have blossomed: autonomous vehicles, genetics, robotics and the like. We have grouped these together in this year’s report to help you gain a deeper understanding of their ecosystems.

• R&D Moves From Universities To Corporations: One observation we made while preparing our 2017 report: some of the unusual suspects we tracked on the fringes turned out to be R&D departments within very large, established corporations. This is because companies are courting academia now more than ever, and in some cases poaching entire research teams. Companies are successfully mimicking a university culture within their walls, with one big exception: money. They’re able to provide significantly more resources and exponentially higher salaries than what’s offered in academe.

• Government Policy: Both in the U.S. and elsewhere in the world, policy, privacy and security will be more complicated than ever in the coming year. Technology is changing faster than the government’s ability to legislate and regulate it—this will lead to complicated discussions and debates in the year ahead.

• More Trends Than Ever: Our biggest takeaway (perhaps yours too, if you took a peak at the very end of the report) is that there are many more tech trends to pay attention to in 2017 than in previous years. Technology begets technology. We are witnessing an explosion in slow motion.

Real trends worth your time and attention don’t have clever names. They don’t sound “trendy.”

EXECUTIVE SUMMARY


Our Trend Report this year is intentionally dense—there’s a lot here to digest. That’s because it’s meant as a practical resource for you and your organiza-tion. We don’t want you to skim through this during your lunch break. Instead, use it to listen for the signals talking and to advise your strategic thinking throughout 2017.

Don’t discount a trend simply because at first glance it doesn’t seem to relate directly to you or your field. Instead, think about these 159 trends and ask yourself the following questions:

01 How does this trend impact our industry and all of its parts?

02 Who are the drivers of change in this trend? Which companies, leaders, founders, startups, researchers?

03 How are companies/ agencies/ organizations in adjacent spaces addressing this trend?

04 Where does this trend create potential new partners or collaborators for us?

05 How are our competitors/ related agencies harnessing this trend (or failing to do so?)

06 Which of our customer segments—existing, former, potential, theoretical—does this trend address?

07 How will the wants, needs and expectations of our customers change as a result of this trend?

08 Will this trend create new competitors for us?

09 How does this trend inspire us?

10 How does this trend help us think about innovation?

This is a big report. We don’t want you to skim through this during your lunch break.

10 QUESTIONSHow to relate these trends back to your organization in 2017


Advertising, Public RelationsKey Trend Themes For 2017

Artificial Intelligence

Recognition

Digital Frailty

Video

Mixed Reality

Security

Privacy

Big Data

Drones

Automation

Internet Mobs and Trolls

Wearables

Pay Special Attention To These Trends In Our Report

01 Artificial Intelligence (whole section)

12 Hidden Bias in AI

13 Accountability and Trust

14 Bots

15 Deep Learning

16 Cognitive Computing

17 Smart Virtual Personal Assistants

18 Ambient Interfaces

19 Deep Linking

20 Consolidation in AI

24 Robot Companions

26 Ethical Manufacturing

29 Productivity Bots

33 Faceless Recognition

34 Bias in Recognition Algorithms

35 Adversarial Images

36 Ambient Proximity

37 Character Recognition and Analytics

38 Attention

39 Digital Frailty

41 Limited-Edition News Products

43 One-To-Few Publishing

47 Conversational Interfaces

48 Dynamic Listicles

50 Connected TVs

51 Cord Cutting

53 Streaming Social Video

54 Media Consolidation

56 Crowdlearning

57 Blocking the Ad Blockers

59 Leaking

60 The First Amendment in a Digital Age

63 Virtual Reality

64 Augmented Reality

65 360-degree Video

66 Holograms

67 Data Retention Policies

71 Glitches

75 Prize Hacks

79 Weaponizing Wikileaks

80 Anonymity

81 Differential Privacy

83 Trolls

84 Authenticity

91 Ownership

93 Organizational Doxing

98 VR Marketing

99 FOBO (Fear Of Being Offline)

100 Retail APIs

102 Sense and Avoid Technology

121 Internet Mob Justice

133 Head Mounted Displays

134 Smartwatches

137 Women/ Wearables

THE MOST IMPORTANT TRENDS FOR YOUR INDUSTRY AND ORGANIZATIONWe’ve created lists to help you find the most important tech trends that will matter most to you, your organization and your industry in 2017. For your convenience, industries are listed alphabetically along with the corresponding trends.



01 Artificial Intelligence

02 Real-Time Machine Learning


15 Deep Learning



22 Smart Dust

25 Collaborative Robots


32 Sharing Economy and Lendership


61 Synthetic Data Sets



69 Zero Day Exploits

71 Glitches

73 Open Source App Vulnerabilities

75 Prize Hacks


84 Authenticity

87 Eye in the Sky

88 Right to Eavesdrop/ Be Eavesdropped On

89 Drone Surveillance

103 Drone Lanes

106 Microdrones

107 Drone Delivery

108 Internet of Things

109 Intelligent Cameras

110 Open Source Systems

111 Adaptive Driving Systems

112 Vehicle-to-Vehicle Communications

115 Autonomous Vehicle Legislation

126 Molecular Programming

129 Synthetic Biology

131 Norms and Regulations (Biological)

148 Deep Learning For Food Recognition

149 Smart Farms

150 Terraforming

151 Cultivated Food and Beverage

152 Anthropocene and Climate

AgricultureKey Trend Themes For 2017


Robotics

Recognition

Augmented Reality

Security

Privacy

Big Data

Drones

Internet of Things

Automation

Self-Driving Vehicles

Genomic Editing

Deep Learning

Anthropocene and Climate






15 Deep Learning




21 Human-Machine Interfaces

24 Robot Companions


31 Nanodegrees






56 Crowdlearning



66 Holograms


68 Remote Kill Switches


70 Backdoors

71 Glitches


74 Selfie Security

75 Prize Hacks

76 Automated Hacking


86 Encryption Management





100 Retail APIs

103 Drone Lanes

104 Clandestine, Disappearing Drones

105 Autonomous Underwater Vehicles

106 Microdrones

107 Drone Delivery






113 Autonomous Testing Facilities

114 Solar Highways


123 City-Level Cyber Security

124 Smart City Systems

132 Biointerfaces


134 Smartwatches

136 Connected Fabrics

143 Thinkables


153 Space Exploration

154 Invisibility Cloaks

157 Internet of X

158 5G

InfrastructureKey Trend Themes For 2017


Robotics

Human-Machine Interfaces

Recognition

Mixed Reality

Security

Privacy

Big Data

Drones

Internet of Things

Automation


Smart Cities

Wearables







14 Bots





27 Universal Basic Income

28 Artificial Intelligence in Hiring


31 Nanodegrees





39 Digital Frailty



63 Virtual Reality




70 Backdoors

71 Glitches

72 Darknets

75 Prize Hacks



90 Private Networks

91 Ownership


95 E-Residents

96 Social Payments

97 Bitcoin and Blockchain


100 Retail APIs

101 Digital Associates

118 Old Laws Clash With New Technology


156 3D Printing

157 Internet of X

158 5G

Business AssociationsKey Trend Themes For 2017


Recognition

Digital Frailty

Security

Privacy

Big Data

E-Residents

Social Payments

Bitcoin and Blockchain

Automation







14 Bots






30 Adaptive Learning

31 Nanodegrees





38 Attention

39 Digital Frailty



59 Leaking



62 Torrents

63 Virtual Reality


65 360-degree Video

66 Holograms



69 Backdoors

71 Glitches

72 Darknets


74 Selfie Security

75 Prize Hacks




82 Digital Self-Incrimination

83 Trolls

84 Authenticity

85 Revenge Porn



91 Ownership

92 Uploading Photos To Law Enforcement Databases




157 Internet of X

158 5G

Colleges, Universities & SchoolsKey Trend Themes For 2017


Robotics


Recognition

Digital Frailty

Mixed Reality

Security

Privacy

Big Data

Internet of Things

Automation






14 Bots






63 Virtual Reality


65 360-degree Video

66 Holograms


75 Prize Hacks

83 Trolls


96 Social Payments


100 Retail APIs

101 Digital Associates

107 Drone Delivery



134 Smartwatches


137 Women/ Wearables

138 Kids/ Wearables

139 Pets/ Wearables

142 Earables

143 Thinkables

148 Deep Learning For Food Recognition

151 Cultivated Food and Beverage

156 3D Printing

157 Internet of X

158 5G

Consumer Package Goods & RetailKey Trend Themes For 2017


Mixed Reality

Security

Privacy

Big Data

Social Payments

Drones

Internet of Things

Wearables









31 Nanodegrees


59 Leaking




70 Backdoors

71 Glitches

75 Prize Hacks



80 Anonymity



83 Trolls

84 Authenticity



91 Ownership





Corporate BoardsKey Trend Themes For 2017


Robotics


Security

Privacy

Big Data

E-Residents


Automation







14 Bots

15 Deep Learning




22 Smart Dust

23 Soft Robotics







52 WebRTC

56 Crowdlearning


62 Torrents

63 Virtual Reality


66 Holograms




70 Backdoors

71 Glitches

72 Darknets


74 Selfie Security

75 Prize Hacks


77 Offensive Government Hacking

78 Cyber Mission Forces in the Field




83 Trolls


87 Eye in the Sky



90 Private Networks




103 Drone Lanes



106 Microdrones

107 Drone Delivery







114 Solar Highways


119 Digital Caliphate

120 Asking Tech Companies To Help Fight Terrorism


125 Precision Medicine


128 Neuroenhancers



132 Biointerfaces


134 Smartwatches

135 Wireless Body Area Networks


140 Tattooables

141 Ingestibles/ Implantables

142 Earables

143 Thinkables

144 Smart Thread

145 Bioelectronics

147 Touch-Sensitive Prosthetics


155 Quantum Computers

156 3D Printing

157 Internet of X

158 5G

DefenseKey Trend Themes For 2017


Robotics


Recognition

Mixed Reality

Security

Privacy

Big Data


Drones

Internet of Things

Automation



Genomic Editing

Wearables





14 Bots

15 Deep Learning





24 Robot Companions

56 Crowdlearning


63 Virtual Reality







127 Nanobot Treatments

128 Neuroenhancers


130 Running Out of Space For Genome Storage


132 Biointerfaces


134 Smartwatches


140 Tattooables


142 Earables

143 Thinkables

144 Smart Thread

145 Bioelectronics

146 Patient-Generated Health Data


156 3D Printing

157 Internet of X

158 5G

Doctors & Other Health Professionals Key Trend Themes For 2017



Recognition

Mixed Reality

Security

Privacy

Big Data

Internet of Things

Genomic Editing

Wearables






15 Deep Learning




22 Smart Dust

23 Soft Robotics

56 Crowdlearning








128 Neuroenhancers




132 Biointerfaces

134 Smartwatches


140 Tattooables


142 Earables

143 Thinkables

144 Smart Thread

145 Bioelectronics



156 3D Printing

157 Internet of X

158 5G

Drug Manufacturers/ Pharmaceuticals Key Trend Themes For 2017


Robotics


Recognition

Security

Privacy

Big Data

Internet of Things

Automation

Genomic Editing

Wearables

Bioelectronics





03 Image Completion

05 Natural Language Generation

08 Zero Knowledge Proofs

10 Algorithm Marketplaces

11 Pre-Trained AI Chips



14 Bots

15 Deep Learning




19 Deep Linking


31 Nanodegrees





56 Crowdlearning




70 Backdoors

71 Glitches


74 Selfie Security

75 Prize Hacks





95 E-Residents

96 Social Payments




FinanceKey Trend Themes For 2017


Recognition

Bots

Security

Privacy

Big Data

E-Residents

Social Payments


Automation







14 Bots



24 Robot Companions




31 Nanodegrees





39 Digital Frailty

40 Nutritional Labels For News



44 Journalism as a Service (Jaas)



56 Crowdlearning

59 Leaking


63 Virtual Reality


65 360-degree Video

66 Holograms



74 Selfie Security

75 Prize Hacks




95 E-Residents

96 Social Payments






Foundations, Philanthropists & Non-profitsKey Trend Themes For 2017


Robotics

Recognition

Digital Frailty

Mixed Reality

Security

Privacy

Big Data


Automation


Smart Cities







14 Bots

15 Deep Learning




19 Deep Linking



22 Smart Dust

24 Robot Companions








39 Digital Frailty




49 Real-Time Fact Checking

52 WebRTC


56 Crowdlearning


58 Natural Language Generation for Reading Levels

59 Leaking



62 Torrents

63 Virtual Reality


65 360-degree Video

66 Holograms




70 Backdoors

71 Glitches

72 Darknets


74 Selfie Security

75 Prize Hacks





80 Anonymity



83 Trolls

84 Authenticity

85 Revenge Porn


87 Eye in the Sky



90 Private Networks

91 Ownership



95 E-Residents


103 Drone Lanes



106 Microdrones

107 Drone Delivery






114 Solar Highways



119 Digital Caliphate



122 Overhauling Government Tech Infrastructure








157 Internet of X

158 5G

Human Resources

Government, Politics, Legal, PolicyKey Trend Themes For 2017


Robotics


Recognition

Digital Frailty

Mixed Reality

Security

Privacy

Big Data


Drones

Internet of Things

Automation



Genomic Editing





03 Image Completion

04 Predictive Machine Vision



09 Algorithmic Personality Detection



14 Bots

15 Deep Learning


19 Deep Linking


24 Robot Companions





31 Nanodegrees





63 Virtual Reality


65 360-degree Video

66 Holograms


70 Backdoors

75 Prize Hacks

80 Anonymity



83 Trolls





128 Neuroenhancers

© 2017 Future Today Institute

Key Trend Themes For 2017


Robotics

Recognition

Mixed Reality

Security

Privacy

Big Data

Automation

Mixed Reality

Security

Privacy

Big Data

Automation

19





14 Bots

15 Deep Learning





22 Smart Dust

24 Robot Companions







56 Crowdlearning

62 Torrents

63 Virtual Reality





70 Backdoors

71 Glitches

72 Darknets


74 Selfie Security

75 Prize Hacks





80 Anonymity



83 Trolls

84 Authenticity

85 Revenge Porn


87 Eye in the Sky



90 Private Networks

91 Ownership



96 Social Payments


103 Drone Lanes



106 Microdrones

107 Drone Delivery







114 Solar Highways







132 Biointerfaces



157 Internet of X

158 5G

Law EnforcementKey Trend Themes For 2017


Robotics


Recognition

Mixed Reality

Security

Privacy

Big Data

Social Payments


Drones

Internet of Things

Automation



Smart Cities





03 Image Completion







14 Bots









62 Torrents

63 Virtual Reality





70 Backdoors

71 Glitches

72 Darknets


74 Selfie Security

75 Prize Hacks





80 Anonymity



83 Trolls

84 Authenticity

85 Revenge Porn


87 Eye in the Sky



90 Private Networks

91 Ownership



95 E-Residents

96 Social Payments


103 Drone Lanes



106 Microdrones

107 Drone Delivery








Lawyers, Law Firms & LobbyistsKey Trend Themes For 2017


Recognition

Mixed Reality

Security

Privacy

Big Data

E-Residents

Drones

Internet of Things

Automation








03 Image Completion



15 Deep Learning




22 Smart Dust

23 Soft Robotics

24 Robot Companions


56 Crowdlearning


63 Virtual Reality







128 Neuroenhancers




132 Biointerfaces

134 Smartwatches



140 Tattooables


142 Earables

143 Thinkables

144 Smart Thread

145 Bioelectronics



156 3D Printing

157 Internet of X

158 5G

Medical, Health, Life SciencesKey Trend Themes For 2017


Robotics


Recognition

Mixed Reality

Security

Privacy

Big Data

Internet of Things

Genomic Editing

Wearables

Bioelectronics





03 Image Completion



06 Generative Algorithms For Voice

07 Generative Algorithms For Sound




14 Bots

15 Deep Learning




19 Deep Linking


22 Smart Dust






38 Attention

39 Digital Frailty



42 Artificial Intelligence For News


44 Journalism as a Service (Jaas)

45 Transparency in Metrics

46 Intentional Rabbit Holes




50 Connected TVs

51 Cord Cutting

52 WebRTC



55 CARv2.0

56 Crowdlearning



59 Leaking



62 Torrents

63 Virtual Reality


65 360-degree Video

66 Holograms



71 Glitches


75 Prize Hacks



80 Anonymity



83 Trolls

84 Authenticity


91 Ownership


96 Social Payments

103 Drone Lanes



157 Internet of X

158 5G

News, Journalism, Media, PublishingKey Trend Themes For 2017


Recognition

Digital Frailty

Accountability

Video

Mixed Reality

Security

Privacy

Big Data

Social Payments

Drones

Automation








14 Bots





31 Nanodegrees






75 Prize Hacks

83 Trolls

84 Authenticity


91 Ownership


157 Internet of X

158 5G

Professional ServicesKey Trend Themes For 2017


Robotics

Recognition

Mixed Reality

Security

Privacy

Big Data

Automation






14 Bots

15 Deep Learning



19 Deep Linking






31 Nanodegrees





51 Cord Cutting

52 WebRTC

63 Virtual Reality


65 360-degree Video

66 Holograms




70 Backdoors

71 Glitches

72 Darknets


74 Selfie Security

75 Prize Hacks





80 Anonymity



83 Trolls

84 Authenticity

85 Revenge Porn


87 Eye in the Sky



90 Private Networks

91 Ownership



95 E-Residents

96 Social Payments


103 Drone Lanes



106 Microdrones

107 Drone Delivery







156 3D Printing

157 Internet of X

158 5G

Technology Companies/ Manufacturers Key Trend Themes For 2017


Robotics


Recognition

Mixed Reality

Security

Privacy

Big Data

E-Residents

Drones

Internet of Things

Automation


Smart Cities

Space Exploration







14 Bots







31 Nanodegrees





39 Digital Frailty



56 Crowdlearning

63 Virtual Reality




75 Prize Hacks


80 Anonymity



83 Trolls

84 Authenticity




95 E-Residents



157 Internet of X

158 5G

Trade, Professional Associations, Interest GroupsKey Trend Themes For 2017


Recognition

Digital Frailty

Mixed Reality

Security

Privacy

Big Data

E-Residents

Automation








15 Deep Learning




24 Robot Companions




63 Virtual Reality


65 360-degree Video

66 Holograms



74 Selfie Security

75 Prize Hacks

83 Trolls

84 Authenticity



103 Drone Lanes

107 Drone Delivery



158 5G

Travel, EntertainmentKey Trend Themes For 2017


Robotics

Recognition

Mixed Reality

Security

Privacy

Big Data

Drones

Automation


Space Exploration





03 Image Completion







14 Bots

15 Deep Learning


19 Deep Linking


24 Robot Companions







31 Nanodegrees




63 Virtual Reality


66 Holograms


72 Darknets





95 E-Residents




158 5G

Work (Future of) Key Trend Themes For 2017


Robotics

Recognition

Mixed Reality

Security

Privacy

Big Data

E-Residents

Automation



The Future Today Institute’s forecasting model relies on quantitative and qualitative data. Our six steps alternate between broad and narrow scopes, which include: identifying very early stage fringe research, focusing on patterns, interrogating trend candidates, calculating a trend’s trajectory, writing scenarios and finally pressure-testing strategies and recommendations.

METHODOLOGY


HOW TO USE THE 2017 REPORTOur 2017 Trend Report reveals strategic opportunities and challenges for your organization in the coming year.The Future Today Institute’s annual Trend Report prepares leaders and organ-izations for the year ahead, so that you are better positioned to see emerging technology and adjust your strategy accordingly. Use our report to identify near-future business disruption and competitive threats while simultaneously finding new collaborators and partners. Most importantly, use our report as a jumping off point for deeper strategic planning.

Explaining why these trends matter. Rather than simply offering an overview of the trends that will matter in 2017, our annual report takes the additional step of explaining why and how these trends will impact your organization. In some cases, you will see very specific use cases and descriptive illustrations, so that you can more clearly envision the potential outcomes of these trends during the next 12 months.


You’ll find six important pieces of information with each trend in this report.

01 Key Insight

Short, easy explanation of this trend so that you can internalize it and discuss with your colleagues.

02 Examples

Real-world use cases, some of which will sound familiar.

03 What’s Next

What this trend means for you and your organization in the coming year.

04 Watchlist Notable companies, founders and researchers working in this trend space.

05 Years On The List

We’ve noted how many years we’ve been tracking the trend, even as it has evolved. This is an indication of how the trend is progressing.

06 Action Meter An easy-to-read graphic indicating where the trend is along it’s trajectory. It tells you whether the trend needs monitoring, should inform your strategy, or requires action.

We recommend using our 2017 Tech Trends Report as part of a formalized process to evaluate disruptive technologies throughout the year.


Needs Monitoring Informs Strategy Requires Action

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02

03

06

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HOW TO USE OUR REPORT

WHAT IS A TREND, EXACTLY?

Mapping the future for your organization begins with identifying early signposts as you look out on the horizon. In order to chart the best way forward, you must un-derstand emerging trends: what they are, what they aren’t, and how they operate.

At any moment, there are hundreds of small shifts in technology—developments on the fringes of science and society—that will impact our lives in the future. A trend is a new manifestation of sustained change within an industry sector, society, or hu-man behavior. A trend is more than the latest shiny object.

Fundamentally, a trend leverages our basic human needs and desires in a meaning-ful way, and it aligns human nature with breakthrough technologies and inventions.

All trends share a set of conspicuous, universal features:

• A trend is driven by a basic human need, one that is catalyzed by new technology.

• A trend is timely, but it persists.

• A trend evolves as it emerges.

• A trend can materialize as a series of unconnectable dots which begin out on the fringe and move to the mainstream.

Identifying something as a trend means connecting the dots, or relating changes in the present to what’s coming in the future. To map what the future holds, seek out the early adopters, the hackers, the developers with seemingly impossible ideas. It’s within these circles that meaningful changes begin. As the trend evolves, the work of these disparate groups begins to overlap, until it converges in a single point—be-fore perhaps evolving once again.



Because trends are a different way of seeing and interpreting our current reality, they provide a useful framework to organize our thinking, especially when we’re hunting for the unknown and trying to learn something about which we do not yet know how to ask.

There are ten modern sources of change in society with technology as the primary connector.

Therefore, if we want to forecast the future of anything, we would need to plot out the intersecting vectors of change—their direction and magnitude—as they relate to new developments in emerging technology.

These features are what make up a trend. Together they distinguish a trend from a fad, which will invariably pass. Trends are what help us to forecast the future.

Wealth distribution Education Government Politics Public health

Demography Economy Environment Journalism

Media (our individual and

collective use of social networks, chat services, digital video channels, photo sharing services

and so on)

01

06

02

07

03

08

04

09

05

10



The future is simultaneously 250 years, 3 decades, 1 months, 88 hours, 37 minutes and 14 seconds from right now. Forecast-ing the future requires thinking in contradictory ways. We must accept that the future is not predetermined—that we can both know what’s past the horizon and intervene to shape it—while simultaneously acknowledging that any number of variables, at any time, can influence an outcome. We must solve the paradox of the present by practicing ambidextrous thinking.

When it comes to technology, it is helpful to organize the evolu-tion of trends along six general time zones. They are not arbitrary; they follow the pattern of acceleration across various sectors of the tech ecosystem. For example, consider the evolution of cars:

Futures of Cars, 2017 - 2057Now: within the next 12 months. By the end of 2018, cars will be equipped with software updates and new sensors that perform more functions for the driver, such as parking and adaptive cruise control.

Near-term: 1 - 5 years. By 2022, most cars will be equipped with cross-path cameras to sense nearby objects and they will have adaptive cruise control for driving in stop-and-go traffic. They will offer many driverless functions—but you will still need to operate the car in neighbor-hoods and many city streets.

Mid-range: 5 - 10 years. By 2027, advanced Lidar and WiFi technology will transmit your vehicle’s location and will recognize other vehicles sharing the road. This will begin to enable cars to drive themselves on highways and many city streets.

Long-range: 10 - 20 years. By 2037, the highway system will have been upgraded to work in symbiosis with semi-autonomous vehicles. Human drivers will take over on smaller streets. On man-dated autonomous highway lanes, people will be free to read, watch videos or con-duct work.

Far-range: 20 - 30 years. By 2047, we may no longer own cars and cities might no longer operate buses. In-stead, automated buses could be subsidized thought taxes and offered at no cost. Those with the means to do so may subscribe to a transportation service, which op-erates vehicles that are fully automated and will take them to destinations as desired.

Distant: more than 30 years. By 2057, autonomous vehicles could be connected to a series of high-speed maglev trains, which may have started to supplant commercial air routes on the East and West coasts.


The future is simultaneously 250 years, 3 decades, 1 months, 88 hours, 37 minutes and 14 seconds from right now.

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Artificial IntelligenceSecond year on the list

Key Insight Many facets of artificial intelligence (AI) have made our list since we first started publishing this report a decade ago. For 2017, we have grouped them all under one trend.

What You Need To Know About AI Think about AI as the next layer of technology that will be integrated into everything you do professionally. Simply put, AI is a branch of computer sci-ence in which computers are programmed to do things that normally require human intelligence. This includes learning, reasoning, problem-solving, under-standing language and perceiving a situation or environment. AI is an extremely large, broad field, which uses its own computer languages and even special kids of computer networks WHICH are modeled on our human brains. The idea that we might someday create artificially intelligent, sentient robots was first sug-gested by prominent philosophers in the mid-1600s.

There are two kinds of AI: weak (or “narrow”) and strong (or “general”). When Netflix makes recommendations to you, or Amazon displays books you might like to read, that’s narrow AI. The H.A.L. supercomputer from 2001: A Space Odyssey, which was not only sentient, but decided it no longer had use for us humans, is a representation of artificial general intelligence.

For the past six decades, researchers have been modeling AI using our own hu-man brain as inspiration. Neural networks are the basic computer architecture that attempts to mimic some of what we know about how the human brain and central nervous system transfers signals.

A neural network is the place where information is sent and received, and a

program is the set of meticulous, step-by-step instructions that tell a system precisely what to do so that it will accomplish a specific task. How you want the computer to get from start to finish—essentially, a set of rules—is the “algo-rithm.”

Machine learning programs run on neural networks and analyze data in order to help computers find new things without being explicitly programmed where to look. Within the field of AI, machine learning is useful because it can help com-puters to predict and make real-time decisions without human intervention.

001 Deep Neural Networks (see also “Deep Learning”) Deep learning is a relatively new branch of machine learning, and it will soon be an invisible part of every organization. Programmers use special deep learning algorithms alongside a corpus of data—typically many terabytes of text, images, videos, speech and the like. The system is trained to learn on its own. While con-ceptually, deep learning isn’t new, what’s changed recently is the amount of com-pute power and the volume of data that’s become available. In practical terms, this means that more and more human processes will be automated. Including the writing of software, which computers will soon start to do themselves.

002 Real-Time Machine LearningIt is recently possible to use a continual flow of transactional data and adjust models in real-time. Potential use cases include: matching customers to the right product as they are looking at a website, re-writing content on a site to match the needs of each individual user, real-time fraud detection, and security measures such as authenticating someone based on her typing habits.

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HBO’s new series Westworld contemplates a world in which artificially intelligent humanoids are built for our amusement.


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006 Generative Algorithms For VoiceResearchers at MIT are studying how children learn new words in order to train computers on automatic speech recognition. As humans, we are able to master a new concept from just one or two examples; for machines, this is a more diffi-cult task when it comes to language. In the coming year, we expect to see more research emerging in this area.

007 Generative Algorithms For Sound MIT’s CSAIL researchers have trained computers to watch videos and predict cor-responding sounds in our physical world. For example, what sound is generated when a wooden drumstick taps a couch? A pile of leaves? A glass windowpane? The focus of this research is to help robots understand how objects interact with each other in the physical realm. But future versions of the algorithms could be used to automatically produce sound and sound effects for news videos, mov-ies and TV shows. It also raises the specter of audio fraud—what happens when computers are able to spoof our voices and natural sound?

008 Zero-Knowledge Proofs With all of the hacking scandals that have plagued us in the past few years, smart businesses and organizations are turning to zero-knowledge proofs, which allows one party to verify data without conveying any additional information (like how or why the mathematical statement is true). In essence, this eliminates the need for a company to store private identity data during the verification process. Ze-ro-knowledge proofs aren’t new, but deploying them to protect our credit cards

003 Image CompletionIf a computer system has access to enough images—millions and millions—it can patch and fill in holes in pictures. There are practical applications for amateur photographers: if the foreground of a mountain is out of focus, another version of the scene can be swapped in to generate the perfect picture. Image completion is also a useful tool for law enforcement and military intelligence officers—com-puters can now assist them in identifying who or what is in the frame.

004 Predictive Machine VisionResearchers at MIT’s CSAIL have trained computers to not only recognize what’s in a video, but to predict what humans will do next. Trained on YouTube videos and TV shows such as “The Office” and “Desperate Housewives,” a computer sys-tem can now predict whether two people are likely to hug, kiss, shake hands or slap a high five. This research will someday enable robots to more easily navigate human environments—and to interact with us humans by taking cues from our own body language.

005 Natural Language GenerationAlgorithms can transfer data into a narrative using natural language generation. Dozens of news and other organizations, including Bloomberg and the Asso-ciated Press, are using Automated Insights, which mines data and is capable of writing more than 2,000 stories per second. They will use natural language generation to produce stories about fantasy football, earnings reports and the like. Narrative Science employs its NLG system to build narratives out of big data sets and to help non-data science people make better sense of what’s happening within their organizations.

Artificial Intelligence cont.


In the near-future, we won’t write code for computers. Instead, we’ll train them like dogs.

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010 Algorithm MarketplacesMost organizations can’t staff a team of developers who have unlimited time to create, test and refine algorithms. As a result, communities of developers are of-fering up their algorithms in emerging algorithm marketplaces. Algorithmia and DataMapper are a sort of Amazon for algorithms, where developers can upload their work to the cloud and receive payment when others pay to access it. DataXu offers a marketplace for its proprietary algorithms. PrecisionHawk has launched a marketplace for predictive agriculture algos. A number of other networks, such as Nara Logics, MetaMind, Clarifai offer tools for developers to build deep learn-ing into any application. Look for even more niche marketplaces in 2017.

011 Pre-Trained AI ChipsA number of companies, including IBM, Google, Intel and Movidius, are working on extremely powerful chips, and some come pre-trained. In short, this means that the chips are ready to work on AI projects. Google’s chip is called a Tensor Processing Unit (or TPU), and was specifically built for the deep learning branch of AI. It is designed to work with the company’s TensorFlow system. For refer-ence, TPUs are what was used in the famous AlphaGo match between Goog-le’s DeepMind system and a world Go champion. Marketing pre-trained chips to businesses will speed up commercialization and as a result will further R&D.

and online identities is an emerging application. Irish startup Sedicii recently launched its zero-proof software, which promises to reduce fraud. Researchers at Microsoft and Princeton University are working on a zero-knowledge proof so that inspectors can identify something as a nuclear weapon without requiring them to take it apart, which would spread information about how to build one.

009 Algorithmic Personality DetectionMarketers will soon have access to algorithms that can assess your personality and predict your specific needs and desires. Nashville-based startup Crystal and IBM’s Personality Insights both use social data and will rewrite everything from emails to resumes based on each of your intended recipients. Meanwhile, some life insurance underwriters are attempting to assess your personality—via your magazine and website subscriptions, the photos you post to social media, and more—in order to determine how risky an investment you are. Some lenders have used personality algorithms to predict your future financial transactions. (The data show that if you look at two people with the same professional and personal circumstances, the one with a higher college G.P.A. will be more likely to pay off a debt.) Algorithms will harness your data in order to assess your predicted suc-cess at work, how likely you are to bounce around jobs and more.



Algorithmia is a marketplace for algorithms.

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Researchers at a number of universities—including Carnegie Mellon, MIT, Prince-ton, University of California-Berkeley, International Computer Science Insti-tute, among others—have started to discover unintended, but explicit bias in algorithms. In 2016, Google was shown to display high-income job ads to men six times more often than women, while searching for “C.E.O.” in Google Images returned 89% men. (As of October 6, 2016, the first instance of a woman was actually a marketing photo for the CEO Barbie doll.)

Part of the problem has to do with the building blocks of AI: computers are trained using a limited initial set of data, and the training programs are built by humans. Often, the training sets reveal unacknowledged bias hidden within us. So if the training data predominantly shows white male CEOs, algorithms won’t recognize people who look different. How can we push the limits of data and algorithms without accidentally creating future socio-economic, religious and ethnic divides?

012 Uncovering Hidden Bias in AI Every single day, you are creating unimaginable amounts of data, both explicitly (uploading and tagging photos on Facebook) or implicitly (searching online for cooking utensils, cars, or doctors). That data is mined and used, often without your direct knowledge or understanding, by algorithms. It is used to create ad-vertising, to help potential employers predict our behaviors, to determine our mortgage rates and even to help law enforcement predict whether or not we’re likely to commit a crime. In May 2016, ProPublica.org published an exceptional investigation on machine bias and the problem of using AI to predict future crim-inals. Their findings: so-called “risk assessment” software is increasingly com-mon in courtrooms across the nation, and it is used to inform decisions about everything from bond amounts to the length of a criminal sentencing. Perhaps unsurprisingly, the software is biased against black people. (We encourage you to read ProPublica’s full report: https://www.propublica.org/article/machine-bi-as-risk-assessments-in-criminal-sentencing.)

As of October 6, 2016, the first instance of a woman returned for “CEO” in a Google Images search was a marketing photo for the CEO Barbie doll.Artificial Intelligence cont.






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013 Accountability and Trust We will soon reach a point when we will no longer be able to tell if a data set has been tampered with, either intentionally or accidentally. AI systems rely on our trust. If we no longer trust the outcome, decades of research and technological advancement will be for naught. Leaders in every sector—government, business, the nonprofit world and so on—must have confidence in the data and algorithms used.

Building trust and accountability is a matter of showing the work performed. This is a complicated process, as understandably corporations, government offices, law enforcement agencies and other organizations want to keep data private. Committing to transparency in method would create trust without necessarily divulging any personal data used.

In addition, hiring an ethicist to work directly with managers and developers, as well as greatly diversifying the pool of developers to include people of different races, ethnicities and genders will solve for inherent bias in AI systems.


Trust and accountability are important trends within AI in 2017.

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Bots Second year on the list

Key Insight You’ve no doubt heard of a bot: a software application that’s been designed to automate certain tasks, such as scheduling or managing basic customer service requests. In the past year, bots have emerged from the fringe and have started to enter our mainstream vocabulary. There are now 12,000 Facebook Messenger bots available, as well as a number of platforms that make it easy for anyone to build a bot.

ExamplesIn the 1960s, Joseph Weizenbaum wrote a computer program called Eliza that was capable of simulating a conversation between a psychiatrist and patient. It offered up plausible responses to common questions. In March 2016, the world watched as @Tai.ai, a Microsoft experimental Twitterbot, went on an anti-Semitic, homophobic, racist rampage within 24 hours after its first tweet.

What’s NextMany brands you recognize (1-800-Flowers.com, Pizza Hut and Dutch airline KLM) are using chatbots for marketing and customer service. Disney partnered with bot developer Imperson to deploy character bots, including Miss Piggy.

Tai.ai was built on the same platform as Microsoft’s experimental Mandarin-lan-guage bot, Xiaoice. Both were capable of intimate conversations with users, be-cause the program is able to remember details from previous conversations and because it mined the Internet for human conversations in order to synthesize chat sessions. The key difference: Xiaoice was released in a country where cit-izens carefully guard their activity online, while Tai.ai was born into America’s

free-wheeling internet. During the recent campaign cycle, we witnessed the rise of botnets—networks of computers designed to send out spam. Fake social me-dia accounts, many of which originated in Russia, artfully tricked people into hav-ing arguments about everything from Donald Trump to immigration to taxes.

The intelligence community should deploy bots for surveillance and for digital diplomacy. HR managers can use bots to train employees. Meantime, as Slack continues to grow in scale and popularity, bots within that environment will help automate meetings and status updates and more, saving time and increasing productivity.

WatchlistRussia; Weibo; WeChat; Alphabet (Google); Snapchat; China; Microsoft; Chatfuel; Pandorabots; Twilio; Amazon; Facebook; Slack

The Tay.ai Twitter bot went on a homophobic, sexist, racist, anti-Semitic bender within 24 hours of its launch.

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We are training bots in our own image. When developing your bots in 2017, we recommend that you rate your work before deployment. Use this scale to rate your bot on its effectiveness—and to determine, in advance, whether or not you’ve accidentally encoded bias into your system. Rate your bot on a scale of 0 - 10, with 10 being the highest (and preferred) score

The Botness Scale

01 Is your bot’s purpose explicit? Will people interacting with your bot clearly understand what its purpose is after the first few interactions?

02 Does your bot perform its designated function well?

03 Is your bot easy to access, either on a designated platform or across platforms?

04 Is it intuitive and easy to use?

05 Does your bot help people learn something new, or does it effectively reinforce something that people already know?

06 Does your bot provide people with the necessary context to have a good conversation?

07 Does the corpus (the initial, base set of questions and answers) you’ve created reflect only one gender, race or ethnicity? If so, was that intentional?

08 Did you assign your bot a traditional gender, ethnic or racial identity? If so, does it reference any stereotypes?

09 Does your bot respond to gendered or sexist remarks? Does it respond to racial epithets or religious slurs? If it does respond, are the responses appropriate to people of the group targeted?

10 Does your bot help people learn about their own biases or broaden their worldviews?



Deep Learning Second year on the list

Key Insight Programmers use special deep learning algorithms alongside a corpus of data—typically many terabytes of text, images, videos, speech and the like. The system is trained to learn on its own.

ExamplesDeep learning is a relatively new branch of machine learning. The Oregon Trail was easy for anyone to play because a person created the game, and he only in-cluded straightforward choices and outcomes. But in real life, during 1810 - 1840, the Oregon Trail presented more threats than what was in the game: there were an infinite amount of variables to consider, which means an unknowable number of possible outcomes. This is a problem for deep learning. Theoretically, an artifi-cially intelligent machine could be trained to learn how to survive on the Oregon Trail, even with such a high number of details to consider. Meanwhile, in early 2016, Google’s AlphaGo—an AI program—beat a professional Go player 5-0. The great hope of those working in AI is that someday, deep learning will have advanced enough not just to make better decisions in a challenge like the Oregon Trail, or to beat a human at Go—but to interact with us such that they’re indistinguishable from other people. Except that their artificial neural networks are orders of mag-nitude more powerful than the biological neural networks inside our heads.

What’s NextDeep learning isn’t just used by Google, though researchers on the DeepMind team are working on a host of applications for neural networks. Internet searching will be aided by deep learning—we’ll have conversations and get to our desired answers far more quickly than we do today searching through pages of content. Chip designers at Fujitsu and Intel are using deep learning to design smaller, faster systems. Scientists at the Karlsruhe Institute of Technology developed a deep neural network that can automatically identify people’s faces using infrared cameras—law enforcement will soon be able to see as clearly in total darkness as they can in the bright daylight. DeepEar was developed by Bell Labs and is a neural network that listens via our smartphones without draining our batteries. Facebook is using this technology to automatically generate faceprints—which is like a fingerprint, but using our photos instead. (The U.S. doesn’t yet have biom-etric data protection laws.)

We recommend that you download your Facebook file if you haven’t already, as this will give you an indication of what data Facebook is storing and how it relates that information across user profiles. Qualcomm is developing neuromor-phic chips, which have been used in robots to help them recognize objects they haven’t seen before, or navigate themselves to a new location. In 2017, experi-mentation in deep learning will begin to lay the groundwork for all that’s to come.

WatchlistBaidu; IBM; Stanford’s AI Lab and Vision Lab; MIT’s CSAIL; Google; Amazon; Mi-crosoft; Fujitsu, Facebook; Karlsruhe Institute of Technology; Bell Labs; University of Toronto; University of California - Los Angeles, University of California - Berke-ley; NSA; Qualcomm

Google’s DeepMind challenge a champion Go player to a game—and won.

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Cognitive Computing Fifth year on the list

Key Insight This trend has evolved from a key idea in our 2010 trend report: anticipatory computing. Cognitive computing systems use natural language processing and artificial intelligence in order to understand our intentions.

ExamplesBy now, you will have heard of IBM’s Watson platform, a system that uses natural language processing and machine learning to enable people and machines to interact more naturally. Cognitive systems like Watson super-charge our human ability to think through complex problems. Watson is assisting doctors, scientists, engineers, lawyers and other professionals now in their everyday work. For ex-ample, in August 2016, doctors in Tokyo were treating a patient who met all of the criteria for acute myeloid leukemia, a blood cancer. After treatment, her re-covery was unusually slow, and doctors began to wonder if there was something else wrong. Yet their reading of the patient’s medical data kept pointing to acute myeloid leukemia. They fed the patient’s data into Watson, which crunched her genetic data against a larger corpus of data. Ten minutes later, Watson offered a set of new diagnoses, which included acute myeloid leukemia but also showed a strong possibility of a rare secondary leukemia. Doctors changed the woman’s treatment plan, and within just a few weeks she was in remission.

What’s NextLate in 2016, IBM launched the Cognitive Horizons Network, which is a collabo-rative network dedicated to accelerating the field of cognitive computing. Those schools include: Rensselaer Polytechnic Institute, Massachusetts Institute of Technology, the University of Illinois at Urbana-Champaign, the University of Maryland, Baltimore County, the University of Michigan, and the University of Montreal. AI researchers at member schools will share resources and work jointly on cognitive problems. Meanwhile, Watson is learning how to read and interpret medical images—a job that was previously reserved for highly-trained radiolo-gists. One interesting offshoot: a cognitive system could read all of the other data captured in a medical image, making the image far more valuable to a patient’s record. Watson and CVS have partnered to learn about patients and their medi-cal histories in order to red-flag problematic behaviors, potentially transforming the role of your local pharmacist. Working together with Watson, your local phar-macist may begin to offer you holistic advice and interventions. IBM is now devel-oping advanced data-centric supercomputing systems that will embed compute power everywhere data resides in a system, which means a convergence of an-alytics, modeling, visualization, and simulation, and driving new insights at very fast speeds. In 2017, IBM will make its big push into a number of fields, including finance, journalism, retail and healthcare, part of which includes better patient ac-cess to their own health and prescription history. Watson—and for the time being, your doctor—will see you now.

WatchlistIBM Research, Cognitive Horizons Network

IBM’s Watson is a cognitive computing platform.

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Smart Virtual Personal Assistants (SVPAs) Third year on the list

Key Insight Smart Virtual Personal Assistants use semantic and natural language processing, along with our data, in order to anticipate what we want or need to do next...even before we know to ask. You already have an SVPA in your phone, and you’ll have one in your kitchen or living room soon.

ExamplesIf you’ve ever used Siri, Google Now or Amazon’s Alexa, you’re familiar with SVPAs. They have nearly invisible interfaces and are being further designed so that you talk, conversationally, with them. Most of the earlier SVPA apps have now been acquired. Emu was acquired by Google, Donna was acquired by Ya-hoo, Cue was acquired by Apple...and the list goes on. When it was still ac-tive, Emu was a clever stand-in for a personal secretary. It would monitor the conversation and automatically make suggestions as two people texted. If you asked your friend to see a movie, Emu would immediately geolocate both of you, suggest a nearby theater and show films and times, then check your calen-dars for your availability. It would even display a preview for you to watch. Once it determined the best time for you to meet, it would help you purchase tickets and enter all the data into your calendar. And it did all of this inside a single mo-bile application. This illustrates what to expect soon. According to what we’ve learned from product teams throughout the tech industry, a new wave of virtual assistants will continue to surface in the coming year.

What’s NextSVPAs will become more pervasive in 2017. There are a number of devices launch-ing in the coming year. Watch for Alexa-like products from Alphabet and Apple. In addition to hardware, you’ll find a number of SVPA apps coming to market that will help you do everything from schedule appointments to feed you real-time information as you watch news programs. You’ll also see SVPAs hidden through-out other connected devices, such as your home thermostat, your refrigerator and your phone. Researchers at MIT, Stanford, and the University of Texas at Austin are building infrastructure so that our devices will be able to listen and watch: They’ll know the places we go, the people we interact with, our habits, our tastes and preferences, and more. Then they’ll use this data to anticipate our needs. Marketers, credit card companies, banks, local government agencies (po-lice, highway administration), political campaigns and many others can harness SVPAs to both surface and deliver critical information.

WatchlistStanford University; MIT; University of Texas at Austin; Amazon; Apple; Alphabet; Microsoft; Yahoo; Robin Labs; IBM.

Amazon’s Echo is an SVPA for your living room.

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Ambient InterfacesSecond year on the list

Key Insight Ambient music pioneer and visionary Brian Eno wrote in his liner notes for Music for Airports: “Ambient music must be able to accommodate many levels of lis-tening attention without enforcing one in particular; it must be as ignorable as it is interesting.” Our modern interfaces are becoming more and more like ambient music—able to do more for us with fewer direct actions, yet still able to captivate our attention.

ExamplesIf you’ve interacted with Google Now or Amazon’s Alexa, or if you own a smart-watch, you’ve used an ambient interface. It listens—figuratively and literally—and automatically delivers you the information you need to know, just as you need to know it.

What’s NextIn our modern age of information, the average adult now makes more than 10,000 decisions a day: some big, like whether or not to invest in the stock market, and some small, like whether to glance at your mobile phone when you see the screen light up. What makes ambient design so tantalizing is that it should require us to make fewer and fewer decisions in the future. Think of it as a sort of autocom-plete for intention. Our mobile devices and many of the wearables coming to market will be listening and observing in the background and will offer up either text, audio or haptic notifications as needed, and those will be decided by algo-rithm. In 2017, we expect to see even more ambient interfaces being embedded into productivity software and apps, tools used by law enforcement, customer loyalty apps, news apps and gaming systems.

WatchlistAlphabet (Google); Amazon; Apple; Microsoft; Spotify; Mumble; IFTTT; Samsung

Google Home’s ambient interface delivers you just the information you need, whenever you need it.

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Deep LinkingThird year on the list (non-consecutive)

Key Insight Deep mobile linking has been around since the beginning of smartphones. Deep mobile links make it easier to find and share data across all of the apps in your phone.

ExamplesThere are three kinds of deep links: traditional, deferred and contextual. Tradition-al deep links reroute you from one app or site (such as a link posted in Twitter) directly to the app, as long as you have that app installed. Deferred deep links either link straight to content if the app is installed, or to an app store for you to download the app first. In 2016, we saw the proliferation of deep linking through-out the Apple and Android operating systems. Contextual deep links offer much more robust information—they take you from site to app, app to site, or app to app, and they can also offer personalized information. For example, when you land at the airport, you might find that your airline app sends you a link to Uber. (You’ll find similar offerings within Google Maps.) Apple’s iOS10 enables quick switching and sharing between apps via deep links.

What’s NextThis interoperability signals a new shift in thinking, as many mobile app devel-opers have been hesitant to use deep links. With Google and Apple’s changes, app-to-app experiences should start to become more common. For example, Branch is a startup that helps developers deliver previews of their applications before users install them. We expect to see this trend develop as the deep linking ecosystem starts to take off in the coming year.

WatchlistButton; Google; Apple; Branch; MobileDeepLinking.org; Deeplink.me; Quixey; Appsfire; AdRoll; tapCommerce; Vungle; InMobi; MoPub; Vserv

Like Uber, many platforms are now offering deep mobile links.

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Consolidation in AIFirst year on the list

Key Insight All of the recent enthusiasm for AI has led to a number of startups—along with lightening-fast acquisitions. Some now worry that the still nascent field of AI is already under the direction of too few companies.

ExamplesIn the past year, Apple has bought Seattle-based AI startup Turi for $200 million, but it isn’t the only company shopping around. To date, the top acquirer of AI startups includes Google, Twitter, Apple, Intel, Salesforce, AOL and IBM, in that order.

What’s NextAs with any technology, when just a few companies dominate the field, they tend to monopolize both talent and intellectual property. This isn’t necessarily bad, but when it comes to the future of AI, we should ask whether consolidation makes sense for the greater good, and whether competition—and therefore access—will eventually be hindered as we’ve seen in other fields such as telecommunications and cable.

WatchlistAlphabet (Google); Apple; Microsoft; Intel; Salesforce; AOL; IBM; Facebook; Am-azon.

Consolidation has begun within AI.

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Human-Machine Interfaces Second year on the list

Key Insight Researchers are finding new ways to connect humans and mammals directly to computers. With these human-machine interfaces, people can communicate via thought alone. Which promises new options for those suffering from stroke and paralysis.

ExamplesAt the University of Washington’s Center for Sensorimotor Neural Engineering, researchers built a system allowing one person to transmit his thoughts directly to another person. Using electrical brain recordings and a form of magnetic stim-ulation, one researcher sent a brain signal to another person elsewhere on cam-pus, causing his finger to tap a keyboard. Meanwhile, researchers at the Center for Neuroengineering at Duke University have built a real-life Iron Man suit, al-lowing a young man suffering from complete paralysis of his lower body to walk out onto a soccer field and kick the first ball of the World Cup.

What’s NextThe team at Duke is now working on a so-called “Brainet,” which connects the brains of a group of mammals to harness and direct their neural activity. One successful experiment: to see if networking rats together would allow researchers to solve a basic forecasting problem that individual rats struggled to complete on their own. In every trial, the Brainet successfully solved the problem, and per-formance improved the more the rats worked together. This work has a practical and altruistic purpose: to help victims of stroke or traumatic brain injury regain their cognitive abilities and motor function. Rather than having to relearn, they need only reload those memories.

WatchlistDuke University’s Center for Neuroengineering; University of Southern California; University of Washington’s Center for Sensorimotor Neural Engineering; Johns Hopkins University; Carnegie Mellon University; Starlab; Case Western Reserve University; Penn State University; Johns Hopkins Applied Physics Laboratory; DARPA.

Dr. Miguel Nicolelis and his team of researchers at the Center for Neuroengineering at Duke University are researching how to connect our brains to machines. This brain-controlled car is being operated by a rhesus monkey, whose brains are similar to ours.

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Smart Dust First year on the list

Key Insight These are computers, no larger than a grain of dust, that are light enough they can suspend in the air. (Or in your brain.)

ExamplesFor years, researchers have been hard at work on miniaturization, as they try to shrink computers as much as possible, down to the size of sand or dust. Each particle-computer consists of circuits and sensors capable of monitoring the en-vironment, and even taking photographs. Scientists at the University of Califor-nia Berkeley developed what they call “neural dust,” which are microscopic com-puters that work alongside remote ultrasound to send and receive data about the brain. Meanwhile, researchers at the University of Stuttgart figured out how to print tiny 3D lenses—120 millionths of a meter in diameter, or about the size of a grain of sand.

What’s NextResearchers believe that this technology will dramatically change our approach to medical imaging. Rather than relying on our current endoscopic technology, which is bulky and invasive, a patient could simply inhale smart dust. Beyond medicine, trillions of smart dust particles could be released in the wind to meas-ure air quality or take photos. But we must also consider other use cases: would you know if you’d inhaled rouge smart dust on a windy day? In the farther-future, could this technology be used to track us surreptitiously?

WatchlistUniversity of Stuttgart; University of California Berkeley; Stanford University; Uni-versity of Washington; Purdue University; USC Robotics Research Lab; DARPA.

The University of Stuttgart’s multi-lens system next to a single doublet lens.

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Soft Robotics First year on the list

Key Insight This is a relatively new field of robotics research. Imagine robots that are squishy and can operate in unpredictable environments.

ExamplesScientists at the BioRobotics Institute at the Scuola Superiore Sant’Anna in Pisa, Italy, have been investigating soft robotics. Recently, they created a robot octo-pus, capable of replicating the animals’ agile motions. In order to replicate the bi-ology of an octopus, they built computer models using exact measurements and then experimented with a number of soft actuators to develop artificial muscles. Researchers at Worcester Polytechnic Institute have been working on a robotic snake.

What’s NextSoft robots mean that someday soon, we will be able to enter and explore envi-ronments previously unreachable by conventional methods: deep ocean waters, the terrain of Mars, and perhaps even the gushing rivers of blood inside our own bodies. This is just the beginning. Don’t expect to play with a squishy robot drone at your next pool party. However those who follow drones, robotics, infrastruc-ture and defense should have new prototypes to look at in 2017.

WatchlistScuola Superiore Sant’Anna; Worcester Polytechnic Institute; MIT Media Lab; Johns Hopkins Applied Physics Laboratory; DARPA.

This octobot is an example of a soft robot.

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Robot Companions First year on the list

Key Insight After many years being developed inside of R&D labs, we are now starting to see the first generation of robot companions emerge.

ExamplesMany countries, including Japan, Italy, and Germany, will soon face rapid demo-graphic shifts. In Japan, one in four people are now age sixty-five or older—there aren’t enough people working to support both retirees and children. Science and technology will eventually stand in for the lack of people: robots will assist with everything from elder care, to medical assistance, to everyday companionship. Unsurprisingly, this first generation of companion robots is being built in Japan: Toyota is launching its Kirobo Mini companion, while Sharp has already debuted its RoboHon. When SoftBank’s Pepper went on sale at the very end of 2015, the company sold all 1,000 units in under a minute.

What’s NextWithin a generation, there will not be enough people to make Japanese society work as it does today—but Japan isn’t alone in its demographic shift. Many in-dustrialized countries, including the U.S., could suffer the same fate. For those concerned that AI and robots will take away jobs, that doesn’t necessarily take into consideration that we already didn’t have enough citizens ready to do the work on their own.

Anyone interested in the future of robotics would be wise to look not to Silicon Valley, but instead to universities and R&D labs in Japan, where extensive re-search on the next generation of robot companions is already underway. Out

of necessity, robots—mechanical systems, artificial intelligence, and automated services—will act as productive, emotionally-intelligent stand-ins for a younger generation that was simply too small in numbers.

WatchlistSoftBank; Sharp; Toyota; MIT Media Lab; Buddy; Nanyang Technological Universi-ty; Sony; Tokyo University; Johns Hopkins Applied Physics Laboratory;

Pepper is a robot companion from Japan’s SoftBank.

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Collaborative Robots First year on the list

Key Insight Robots that communicate in real-time and cooperate on projects make a strong team.

ExamplesTeams of robots are now capable of working together, and they’re efficient, since not every single robot has to excel at every task. Researchers at Carnegie Mellon University have built collaborative robots that are designed to work together. In their recent work, a robot named Baxter is stationed at a table working on a project. Once completed, another robot on the team—CoBot—picks up the item and hands it to a human. Teams of collaborative robots can communicate to each other, on their own, about when to wait, when to move, to carry out an activity, or even to ask what to do.

What’s NextUse your imagination and you can probably see what’s on the horizon. Collabora-tive robots will play a key role in automating the tasks performed in warehouses, manufacturing plants, logistics and delivery services. They will also run opera-tions in conflict zones.

WatchlistCarnegie Mellon University; MIT’s Interactive Robotics Group; DARPA; Auton-omous Solutions; Energid Technologies; Boston Dynamics; Alphabet (Google); Amazon; ABB Robotics; Aethon Inc.; FANUC Robotics; EPSON Robotics; Seegrid; SoftBank Robotics Corporation; Toyota; ULC Robotics; VEX Robotics; Yamaha; University of Tokyo; Johns Hopkins Applied Physics Laboratory

Self-assembling swarming microbots developed at MIT.

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Ethical Manufacturing First year on the list

Key Insight Could robots bring the end of forced labor and lead a new era of ethical manu-facturing?

ExamplesRecent advancements in robotics are proving that soon, humans may no longer be required to perform labor-intensive manufacturing jobs. While this certainly means that people will be out of certain kinds of work, it does imply the end of bonded, forced and child labor—not to mention slavery—which unfortunately has become commonplace in places like China, the Philippines and Bangladesh. In October 2016, a Canadian court allowed a lawsuit brought by Eritrean workers against Nevsun Resources, a mining company: it was the first time in history that a tort claim for modern slavery went ahead in Canada. Meanwhile, in September, the Associated Press published a searing account of foreign fishing workers, con-fined and forced to work on U.S. fishing boats. The AP’s investigation revealed a disturbing present-day reality: men are forced to use buckets instead of toilets, suffer sores from bed bugs and don’t have enough food to sustain them.

What’s NextLook for a number of new advancements in robotics that further reduce the need for human labor, such as the Sewbo, which is similar to a traditional sewing ma-chine but also has a smart robotic arm, allowing it to both sew and assemble an item of clothing. Elon Musk’s giant Gigafactory will soon employ hundreds of robotic arms and “automated guided vehicles,” essentially mobile robots that transport items from one area to another. There could be models available for the future sooner than you might think. Manufacturing regions, like Ohio and Michi-gan, could find their workforces disrupted.

WatchlistNational Association of Manufacturers; Alliance For American Manufacturing; Te-sla; Sewbo; Carnegie Mellon University; MIT’s Interactive Robotics Group; Alpha-bet (Google); Amazon; ABB Robotics; Aethon Inc.; ULC Robotics.

Factories staffed with robots could mean the end of harsh working conditions.

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Universal Basic Income First year on the list

Key Insight An unconditional, guaranteed income for everyone within a country—a concept made popular in the 1960s—is being debated once again in the wake of automa-tion, advanced robotics and artificial intelligence.

ExamplesThe origins of universal basic income (UBI) date back to Thomas Paine who, in a 1797 essay, theorized that governments should pay citizens £15 a year. There have been a number of universal basic income (UBI) experiments. In the 1970s, the Ca-nadian province of Manitoba began sending UBI checks to all of its residents. An economist analyzed the program, which only lasted a few years, and discovered that life improved significantly: kids stayed in school, fewer people wound up in the hospital, and many reported that their quality of life overall was better. UBI has had its share of supporters throughout history, from Dr. Martin Luther King, Jr., to the Nixon Administration, to far-right economist Milton Friedman.

What’s NextFinland has just launched a two-year UBI pilot study. A randomly-selected group of 2,000 - 3,000 citizens will begin receiving a monthly stipend of 560 Euros (or about $600 dollars.) Y-Combinator, the storied Silicon Valley incubator of hot tech startups such as Reddit, Wufoo and Rapportive, is sponsoring a UBI program in Oakland, California. In June 2016, Swiss voters rejected a UBI initi-ative guaranteeing citizens around $2,500 a month. Critics of UBI argue that if citizens are simply handed a wad of cash each month, they won’t spend it on preventative health or nutritious food, and that they will be less inclined to work. Proponents say that our fast-approaching robotics era will render many out of work anyway—and that a UBI will help insure our country against an imminent implosion in the job market.

WatchlistStanford Center for Philanthropy and Civil Society; White House Council of Eco-nomic Advisors; American Enterprise Institute; Oxford University’s Carl Benedikt Frey and Michael Osborne; Finland; Netherlands; Norway; Sweden; Organization for Economic Co-operation and Development.

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Needs Monitoring Informs Strategy Requires Action A UBI would guarantee income for everyone.


Artificial Intelligence in Hiring First year on the list

Key Insight Researchers are finding that the usual data sources—test scores, GPAs and the like—aren’t reliable indicators of talent.

ExamplesArtificial Intelligence is being used to assess personal attributes like empathy, thoughtfulness, engagement, motivation and drive. Coupled with social media screening—looking at an applicants previous posts on Facebook, Twitter, Insta-gram, blogs and elsewhere online—emerging systems consider both personality and behavior when evaluating possible new hires. Companies like RoundPegg and Interviewed, which collect data and perform assessments on candidates, are being used by high-profile clients including ExxonMobil, Xerox and Razorfish.

What’s NextOne likely future benefit of AI-assisted hiring is that machines—theoretically, at least—can be more objective than people. However, as we start to rely more on these systems, we must also redouble our efforts to ensure that the algorithms and data used aren’t also subject to bias. After all, these systems were originally envisioned, architected and programmed by humans.

WatchlistMya A.I.; Recruit Strategic Partners; HackerRank; LinkedIn; IBM Watson; Alphabet (Google); Facebook; University of Oxford’s Martin Programme on the Impacts of Future Technology; Xerox; Razorfish; ExxonMobil; RoundPegg; Interviewed.

AI-assisted hiring could reduce bias and diversity workforces.

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Productivity Bots Second year on the list

Key Insight Productivity Bots will help assist workers and students perform tasks more effi-ciently.

ExamplesSlack is a popular hybrid instant message/ email system that lets you sort and tag, search, and choose to broadcast messages to your whole team or just to a few members. The average Slack user spends around 140 minutes (nearly two and a half hours) per weekday on the service, and much of the reason is because Slack bots can automate myriad productivity services on their behalf. For exam-ple: you can automatically retrieve and read news from multiple sources, set work and break timers, plan meetings and events for a few staff without spamming an entire team and collaborate on Google docs. Productivity bots are now offered in a number of different office apps, including Yammer, HipChat and Skype.

What’s NextSlack’s success has inspired numerous startups and competitors, including Mi-crosoft, which introduced its own product late 2016. We should expect deeper integrations across all platforms and services in 2017, which should promise even more increased productivity. Watch for more automated features within Trello, Dropbox, Google Drive, Heroku, Mailchimp and Zendesk, to name a few.

WatchlistSlack; Alphabet (Google); Yammer; HipChat; Skype; Trello; Dropbox; IFTTT; Hero-ku; Y Comibinator; Mailchimp; Zendesk; Microsoft.

Slack is a popular platform that now includes bot assistants.

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Adaptive Learning First year on the list

Key Insight Artificial Intelligence is causing a disruption in education. The “one size fits some” model will soon be replaced by individualized adaptive learning software.

ExamplesAdaptive learning software tailors the coursework for each student individually. Students are assessed in real time, so that concepts and skills are presented in a way that’s easiest for her to understand. Students are therefore able to work at their own pace. The machine learning techniques powering the software requires a large amount of data—which means many thousands of students—to be effec-tive. Geekie, an adaptive learning startup, is now being used in thousands of high schools across Brazil.

What’s NextThe number of startups in the adaptive learning space will continue to grow, es-pecially as more schools gain access to portable technology. In the near-future, computerized textbooks will adapt to each student. These systems will not re-place teachers, but rather enable teachers to more adroitly support each individ-ual student. There are opportunities for publishers to extract more revenue from their core offerings: schools and students might subscribe to books rather than buying them outright. However adaptive learning also stands to disrupt the text-book value chain, from book sellers, to printers, to recycling centers to logging companies.

WatchlistGeekie; DreamBox; Smart Sparrow; Knewton; Pearson; McGraw-Hill; Northwest-ern University; Stanford University; Y Combinator.

Adaptive learning software is being used to power digital textbooks.

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Nanodegrees First year on the list

Key Insight As technology—and tech-forward educational platforms—becomes more so-phisticated, new single-skill “nanodegrees” will be conferred.

ExamplesOne theory emerging from Silicon Valley is that our traditional, four-year post-sec-ondary degree system alone cannot serve our future workforce in the years to come. With the advent of automation and AI, we will need highly-specialized skills, the sort that aren’t offered within universities. Some prominent technolo-gists, including Stanford University professors (who’ve also worked at Alphabet) Sebastian Thrun and Andrew Ng, say that nanodegrees are necessary to help workers stay current. Courses, which could be completed in just a few months, are intended to be taken alongside a job. Perhaps unsurprisingly, the popular ed-ucation platforms Udacity, Coursera and edX all emerged from AI labs. Rather than attempting to completely overhaul our educational system, nanodegrees, which can be earned at a pace and during a time that works best for each indi-vidual, are proving to be a reasonable way to keep up with technology.

What’s NextExpect to see more platforms emerge, as well as new pricing models. Now that nanodegrees have started to catch on, we will see fewer free courses. In the next few years, platforms and course providers will need to think through their busi-ness models. We should also start asking questions about future digital divides—should there be a more egalitarian way to help everyone better their skills?

WatchlistStanford University; MIT; Alphabet (Google); edX; Coursera; Udacity.

Udacity recently introduced its “nanodegree” program.

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Sharing Economy and Lendership Third year on the list

Key Insight Rather than buying to own products, consumers are paying to temporarily lease them. And they’re making money on the side too, by sharing.

ExamplesPlatforms are quickly replacing brick-and-mortar retailers. The appeal of having access to the latest dress/movie/song, along with the ability to re-borrow it, in-creasingly trumps consumers’ desire to actually own and store it in their clos-ets. A down economy has helped sharing platforms gain millions of users. What started as basic transportation (Uber, Lyft) and housing platforms (Airbnb) has blossomed to include municipal services (MuniRent, Kitestring, Life360), food (EatWith, LeftoverSwap), professional services (TimeBanks, CloudPeeps), logis-tics (Boxbee, shyp, Postmates), telecom (fon, Reclaim), energy (Mosaic, vande-bron) and beyond.

What’s NextThe sharing and lending economy will continue to grow in 2017. A recent AARP study showed that more than half of older Americans who lost their jobs in the past few years cited that age discrimination is the primary reason they haven’t been able to find new work, so they’re eager to become microentrepreneurs in the lending and sharing economy. Niche industries that must pay for and maintain expensive equipment, such as farmers, are also eager to monetize year-round. FarmLink is a startup connecting farmers in one harvesting region to farmers in another region to help spread capacity throughout the year. Impermanence will increase pressure on CMOs to tell a different story about the value of ownership—or to develop new business models to support this shift in consumer buying. Meanwhile, new regulatory frameworks, legislation and licensing provisions will become more prominent in the coming year, which could impede further growth.

WatchlistCrowd Companies Council; Facebook; Etsy; Rent The Runway; Airbnb; Snap-goods; WeWork; SpaceAway; LendingClub; Funding Circle; Sparkbox; FarmLink; Toys Trunk; Uber; Lyft; MuniRent; Kitestring; Life360; EatWith; LeftoverSwap; TimeBanks; CloudPeeps; Boxbee; shyp; Postmates; fon; Reclaim; Mosaic; vande-bron; and many others.

Postmates is just one of the sharing platforms that will be available in 2017.

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Faceless Recognition Second year on the list

Key InsightTechnology has made it possible to recognize who you are, even without a clear image of your face.

ExamplesGerman researchers have discovered how to create thermal faceprints by taking heat maps of our faces and using machine vision to recognize patterns. Their technology can accurately identify a face—and in under 35 milliseconds, regard-less of the amount of lighting or the facial expressions people make. (See Trend 20, Deep Learning.)

What’s NextSan Diego-based KnuEdge built a military-grade platform capable of recognizing our individual voices, even in a noisy environment. Founded by NASA’s former Chief Administrator and its Chief Technology Officer, KnuEduge recently hired world-class voice impersonators to see if they could fool the system, but the technology prevailed every time.

MIT researchers have learned that WiFi can now identify you just by bouncing signals around—your unique shape and posture are used to reveal who you are, even in a crowded room of people. Emerging research has shown that WiFi can be used to recognize what a person is saying or writing with a pen—simply by analyzing the WiFi signals altered by our bodies. Which means that soon, we’ll see through walls.

WatchlistKnuEdge; MIT Media Lab; DARPA; Alphabet (Google)

KnuEdge is a military-grade platform capable of recognizing our individual voices, even in a noisy environment.

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Bias in Recognition Algorithms Second year on the list

Key Insight We are discovering that machine learning algorithms, meant to help identify peo-ple for a number of different reasons, aren’t as objective as we’d planned.

ExamplesDuring 2016, we saw a number of cases in which the algorithms got it wrong: they misidentified innocent people as criminals and predicted that certain city blocks were likely to see a spike in violent offenses or drug trafficking. All of these cases had one thing in common: they involved black people. Investigations from a num-ber of universities, media organizations and activist groups revealed bias in the software. For example, the PredPol predictive policing system, which is used by police departments around the U.S., recommended time and time again that de-partments concentrate their efforts on neighborhoods that were overwhelmingly poor and black. The problem has to do with how arrest data is gathered, and how individual police departments have historically monitored their local communi-ties. The model didn’t include a rigorous check on bias in the initial data sets.

What’s NextWhile you won’t see a complete reversal of how these systems work in 2017, you can expect to see more investigations into bias.

WatchlistPredPol; HunchLab; National Institute of Justice; Hitachi’s Visualization Predictive Crime Analytics; a police department near you.

PredPol’s predictive policing system.

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Adversarial ImagesFirst year on the list

Key Insight In short, an adversarial image is a photo with a tiny modification, usually one that’s imperceptible to humans, that is created in order to help computer scien-tists adjust machine learning models. They are also a security threat.

ExamplesIn order for machine learning systems to learn, they must recognize subtle dif-ferences. For example, a computer scientist might slightly alter an image of a lla-ma—using something as tiny as a few scattered pixels—and fool the system into miscategorizing the image as something completely different, such as a shoe or a cup of coffee. When that happens, an adjustment is made to the system and it continues training.

What’s NextAdversarial images can also be used to knowingly and purposely trick a machine learning system. If an attacker trains a model, using very slightly altered images, the adversarial examples could then be deployed out into other models. There are implications for companies that use images as secondary passwords (such as Bank of America’s sign-on system), for search engines (Google, Bing) and for any service that automatically tags our photos (law enforcement databases, Facebook).

WatchlistGoogle’s Inception v3 algorithm; Stanford University; University of Chicago; Ima-geNet database.

Extra information can be added to an image to fool algorithms.

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Ambient ProximityFourth year on the list

Key Insight New technologies can be programmed to push or receive information to/ from our mobile devices—and also our bodies—tethering us to an always-on informa-tion network.

ExamplesYou’ve no doubt heard about beacons, which are tiny devices that can be pro-grammed to push (or receive) information to/from mobile phones using Blue-tooth. We are located on nearby networks, as sensors use our personal informa-tion and collect data about our experiences. These beacons become aware once you’re near them. All of this will get more exciting once beacons are connected to the emerging Internet of Things, which will network data from everyday items to enable entrepreneurs to make smarter real-time decisions. For instance, beacons placed on an in-store display could report how many customers stop to look at a particular running shoe, and how many try on that shoe or merely skip over it and look at a different one instead. A new Internet protocol (IPv6) is emerging and will power our Internet of Things over WiFi, so that soon, everything we own will have its own unique identifier.

What’s NextDoorStat collects and analyzes a wide array of customer demographics, including gender, age, ethnicity and even mood, in real time. This allows retailers to observe how shoppers behave while inside of a store and to make adjustments, such as moving merchandise to other locations or deploying staff who have more (or less) outgoing personalities. Placemeter quantifies the volume and movements of pedestrians, cars and bicycles, offering retailers an instantaneous snapshot of how much pedestrian traffic walks by a storefront, how many of them actually walk into the store to look at products, and ultimately how many make purchas-es. In 2017, expect to see more uses of ambient proximity in retail, security, and in places where people congregate.

WatchlistPolytechnical University (China); MIT; University of New South Wales (Austral-ia); Oxford University; BlipTrack, Gimbal, Estimote, Google’s Eddystone, Amazon, PayPal, Qualcomm.

WiFi and NFC-powered beacons can recognize us and then deliver information we can use while shopping.

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Character Recognition and AnalyticsSecond year on the list

Key Insight Emerging predictive analytics tools wrangle your data, behavior and preferences in order to map your personality—and predict how you’re likely to react in just about any situation.

ExamplesIBM Watson and Twitter offer a tool that mines Twitter feeds and weather data to identify consumers who are likely to fire off angry tweets if their cable service is disrupted. Those complaints aren’t empty threats: IBM’s data shows a correla-tion between disgruntled tweets and customer loss. IBM’s technology can scan individuals’ social media data and analyze their personalities to predict responses to an email or an ad. Recruiting startups, dating sites and school application plat-forms are all starting to experiment with personality recognition software. Nash-ville-based startup Crystal culls thousands of public data sources to help you learn about someone’s personality before calling or emailing them. It even offers a kind of spell check for sentiment, autocorrecting phrases and making recom-mendations (“keep the message under 200 words, otherwise this recipient might ignore it”) so that the message resonates better with your intended recipient.

IBM Watson’s Personality Insights API analyzed Oprah Winfrey’s tweets to create her profile.

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The Future Today Institute’s Attention Matrix is a tool to help measure whether your strategy will command the attention of your desired audience.

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AttentionThird year on the list

Key InsightAs technology has evolved, media organizations, marketers and advertisers have adapted their existing content for the screens of our ever-changing devices. However multiple studies show that our attention is continually split between what we’re doing in the real world and what we’d like to be doing online. As the two become more intertwined, capturing our attention is becoming more diffi-cult than ever.

ExamplesMaking sure that content fits correctly on a screen is only solving part of the challenge—what about content fitting our needs and behaviors as both change throughout the day? In order to capture someone’s attention, you must consider a number of variables: where is she right now? What’s she likely to be doing in the next 60 seconds? What’s relevant to her in the next few minutes? What need can you fulfill for her at this moment?

What’s NextWe believe that any organization that publishes any kind of content for any rea-son—whether that’s a news organization, a social network, a brand or a branch of the government—must focus less on the device a customer is holding and more on what the customer herself is doing. Soon, content creators will work alongside algorithms to syndicate different versions to different devices depending on a user’s individual needs, given that those needs will change throughout her day.

WatchlistFacebook; Alphabet (Google); Chartbeat; Washington Post; New York Times; Na-tional Public Radio; Financial Times; Refinery29; Buzzfeed; Mic; Vocativ.


The Internet Archive is saving some—but not all—of our content.

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Digital FrailtySecond year on the list

What’s NextDuring the past election, candidates relied heavily on social media to get their ideas out, and to debate each other in a public space. Recently, many of those tweets and Facebook posts were deleted by candidates and their staffs. Cur-rently, the United States does not have a policy on archiving social media posts. Should a governor, senator or president’s social media posts become part of an official archive?

While some content can be retrieved via the Internet Archive, it is only taking snapshots of content at a time. Libraries archive printed material, but there is no central repository for all of the digital content we are now producing. Perhaps we don’t need to save every listicle and quiz. What will a future society look like if our current media landscape goes dark? Do we have an obligation to preserve the digital conversations shaping society? Should we be working harder to en-sure that digital archives aren’t lost? These are questions we will be asking (and hopefully answering) in 2017.

WatchlistFacebook; Twitter; Alphabet (Google); Snapchat; Instagram; Tumblr; Yahoo; NewsCorp; Bloomberg; Disney; Comcast; Amazon; AT&T; Verizon; ESPN; Netflix; General Electric; BuzzFeed; PRX; PRI; Vox; NPR; Internet Archive; newspapers and magazines everywhere.

Key InsightIn the past two years, we’ve seen the first widespread cases of important journal-ism being erased from the web because of media consolidation or because sites were no longer being maintained. Digital Frailty is the phenomenon in which those digital assets published to a news organization’s website are impermanent or easily broken.

ExamplesPerhaps not every Facebook post should be saved in perpetuity, but might we need to look back on this moment in time and reflect on how our language—how the very way we communicate—was shaped by our Instagrams, our Snaps, and our tweets? Will our future historians look back, marveling at the amount of anthropological data we were simultaneously creating—and destroying? If this past election season taught us anything, it’s that Twitter helped to shape public opinion and the outcome of the election, but many controversial tweets posted by candidates running for office, were deleted by their campaigns.

Meanwhile, several news organizations have moved to digital-only publications as a cost-cutting measure. One of the best digital journalism projects remains Rising From Ruin, an award-winning project by MSNBC. It tells the story of Katrina’s af-termath through the lenses of two small communities in Mississippi that weren’t covered by any other media outlet. It included a series of videos, maps, interac-tive elements, a forum for residents—and since it only exists as a website, there is no other way to see the stories. When Microsoft pulled out of its joint venture with NBC, the project went offline. It’s recently available again, but for how long?


In this age of technology, we need a nutritional label for news.

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Nutritional Labels For NewsFirst year on the list

Key InsightNow that news organizations are relying on data, algorithms, and machine learn-ing for various aspects of news gathering and publishing, they should commit to transparency.

ExamplesThere are too many instances of bias in algorithms to list. Just as consumers ex-pect to see a byline on stories, because it creates a chain of accountability, they will soon expect to know how stories were built. Reporters aided and augmented by smart systems should explain what data sets and tools they used. Meanwhile, stories that were written in part or entirely by computers should reflect that an algorithm was responsible for the piece of content being read/ watched.

What’s NextIt is in the public’s best interest, and in the best interest of newsrooms, to create a nutritional label of sorts for stories, explaining which technologies and datasets were used. Whether a label or simply a few sentences below each story, we ex-pect to see more transparency in how stories were reported in 2017.

WatchlistTow Center for Digital Journalism; Columbia Journalism Review; news organiza-tions everywhere.


The New York Times introduced an experimental limited-edition SMS product for the Olympics.

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Limited-Edition News ProductsSecond year on the list

Key InsightSome organizations have begun to experiment with temporary products: limit-ed-run newsletters, podcasts that only last a set number of episodes, live SMS offerings that happen only during events.

ExamplesLimited-edition news products doesn’t necessarily mean creating a bunch of la-bor-intensive one-offs. Rather, they can be templates that your organization can use, iterate on and redeploy again and again. Whether it’s a planned news event (like the 2016 Election), an annual conference (CES, SXSW), a season (basketball, football, winter weather), or a big story that has a defined beginning and end, limited-edition news products are starting to be used by news organizations.

What’s NextIn 2017, expect to see more temporary podcasts, newsletters and chatbots that are deployed specifically for just one event. This is a revenue and outreach oppor-tunity, as they are vehicles for targeted, short-run advertising.

WatchlistMedia organizations; content marketers.


Michael Ferro, chairman of tronc, said in 2016 that his company would use AI to create 2,000 videos a day.

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Artificial Intelligence For NewsSecond year on the list

WatchlistResearcher and academic Meredith Broussard at NYU; Washington Post; Face-book; New York Times; Narrative Science; Automated Insights; researcher Andre-as Graefe at the Tow Center For Digital Journalism

Key InsightIn 2017, we will continue to see a number of machine learning and AI applications being used to assist reporters, editors, producers and publishers.

ExamplesSince 2013, we’ve included AI-powered robot-assisted journalism and contextual awareness as part of this report. Early experiments at the LA Times and at start-ups such as Narrative Science and Arria have proven that bots can transform raw data into narratives, crafting stories that seem as though they’ve been written by a human. In 2016, Tribune Publishing renamed itself tronc; company chairman Michael Ferro then appeared on a CNBC show and said that tronc would focus on producing its content using AI in order to create 2,000 videos a day.

What’s NextThe challenge with declaring AI in newsrooms a fait accompli is that we are only at the very beginning of the artificial intelligence era. In the next 24-36 months, object recognition, natural language algorithms, generative language, machine learning and compute power will coalesce to make it possible for computers to identify what’s in photos, text and videos, extract meaning, and automatically generate multimedia stories—but we’re not quite there yet today. Our research shows that in the coming year we will see new innovations and experiments in how AI can be used in newsrooms.


Backchannel is a new breed of website with a highly engaged niche audience.

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One-To-Few PublishingSecond year on the list

What’s NextWe anticipate seeing more and more niche networks launch, whether they are individual newsletters or podcasts. We also expect to see more niche-focused digital magazines in 2017. Smaller sites like Backchannel, Nautilus, Pacific Stand-ard, Bitter Southerner, New Inquiry and Aeon produce exceptional content and command very attentive audiences. Our research shows that there is profit to be made, even though audiences may be smaller in size. As many of the one-to-few startups have proven in the past 24 months, an influential network with sticky engagement shows why dedicated attention matters more than a bunch of clicks, and that’s the metric that will matter most in the near future. Advertisers are taking notice.

WatchlistREDEF group; The Information; PRX; TinyLetter; Mailchimp; Nautilus; Pacific Standard; Bitter Southerner; New Inquiry; Aeon; Backchannel; Skype; Garage Band; SoundCloud; Libsyn; Stitcher; Auphonic; SpeakPipe; Twilio; NPR; PRI.

Key InsightNewsletters, podcasts and niche networks that captivate smaller audiences made a huge comeback in 2015-16. What’s next is an expansion to capture more niche audiences.

ExamplesSuddenly, it seems like everyone—from world leaders, to your next-door neigh-bor—has a podcast, newsletter or both. This is due in part to services like Mailchimp, TinyLetter (owned by Mailchimp), Skype, Google Hangouts, Garage Band, SoundCloud, Libsyn, Stitcher, Auphonic, SpeakPipe and a host of afforda-ble smartphone microphone attachments. In 2016, we watched new niche media empires take root: Jessica Lessin’s The Information publishes in-depth stories on tech and business. Former MTV chief digital officer Jason Hirschhorn expanded his MediaREDEF newsletter in a full-blown news aggregation brand, attracting in-vestor funding and launching REDEF.com along with several new topic-focused newsletters.


In the near-future, journalism could be offered as a broader service via the cloud.

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Journalism as a Service (JaaS)First year on the list

What’s NextHow could you rethink news deployed as a service that would include different kinds of parcels: news stories; vetted and fact-checked mini-biographies for other sites and digital services (to replace Wikipedia); verified, searchable databases of people and organizations. An AI-powered service that automatically generates a short report of the opinions on a particular subject, along with a list of quoted experts. A calendar plug-in that summarizes the most important news events to pay attention to during the week. All of these services could work outside of the social media landscape, which means that news organizations would not have to share revenue or give away their content for free, but could charge for access.

WatchlistNews Corp; McClatchy Corporation; CNN; Advance Publications; iHeartMedia; Discovery Communications; Grupo Globo; Asahi Shimbun Company; Microsoft; Hearst Corporation; Axel Springer; Mediaset; ITV; BBC; Fuji Media Holdings; New York Times; Washington Post; Alphabet (Google); Amazon Web Services; Twilio; Comcast; 21st Century Fox; Bertelsmann; Viacom; CBS Corporation; Baidu; tronc; Hubert Burda Meda; Gannett; PBS; NPR; PRI; PRX; Yomirui Shimbun Holdings; Time Inc.

Key InsightNews organizations can become an indispensable modern information layer that powers all facets of our daily lives across all devices—and in the process unleash a sustainable revenue model.

Examples“Software as a Service” is a licensing and delivery model, where users pay for on-demand access. It’s a model that we believe could work for news, and in the near-future might be an inevitability. The central challenge within news organiza-tions is that there are immediate, acute problems—but reasonable solutions will require long-term investment in energy and capital. The tension between the two always results in short-term fixes, like swapping out micro-paywalls for site-wide paywalls. In a sense, this is analogous to making interest-only payments on a loan, without paying down the principal. Failing to pay down the principal means that debt—that problem—sticks around longer. It doesn’t ever go away. Transition-ing to “Journalism as a Service” would enable news organizations to fully realize their value to everyone working in the knowledge economy—universities, legal startups, data science companies, businesses, hospitals, and even big tech giants. News organizations that archive their content are sitting on an enormous cor-pus—data that can be structured, cleaned and used by numerous other groups.


Metrics will become more transparent in 2017.

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Transparency in MetricsSecond year on the list

WatchlistNielsen; Chartbeat; YouTube; Instagram; Snapchat; Facebook; Twitter; Alphabet (Google); all content-producing organizations.

Key InsightWhile most companies that publish content on the web are obsessed with met-rics, historically they’ve kept audience data hidden from staff. We anticipate a sea change in 2017.

ExamplesMetrics are neither easy to find nor easy to understand for many working inside of content organizations. In September 2016, Facebook apologized for display-ing incorrect numbers of video plays to advertisers and publishers, and said that it had been showing incorrect metrics for two years as it attempted to challenge YouTube. Earlier in the year, current and former Facebook staff alleged they were instructed to suppress conservative news from the site’s “Trending Topics” area. It goes without saying that metrics can influence editorial and business decisions, not to mention how the public interprets the popularity of a story. Most large news organizations have hired audience engagement and analytics managers as go-betweens.

What’s NextPublishers and advertisers will question the validity of metrics that they, them-selves, cannot verify. Anyone creating content needs to understand the ebb and flow of traffic and how one piece of content fits into the broader scope of the or-ganization. We expect to see news and other content organizations develop new models to bring transparency in metrics to staff—without jeopardizing editorial integrity.


Apture was an early experiment in layering contextual information on websites.

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Intentional Rabbit HolesSecond year on the list

What’s NextWe haven’t seen a similar contextual service launch since Apture went offline, though the Washington Post began experimenting with what it calls a “Knowl-edge Map” the summer of 2015. Its “Confronting the Caliphate” series offered special highlighted phrases that when clicked would reveal a column with addi-tional information. The feature works on mobile as well. Media organizations are trying to keep people on their sites, so we anticipate seeing renewed interest in Apture-like services in the coming year.

WatchlistWashington Post; Alphabet (Google); Mother Jones; NPR; Facebook; tronc; Mc-Clatchy Corporation; News Corp; Advance Publications; BBC News; Guardian; Mi-crosoft; Axel Springer; Vox; Mic.

Key InsightFor the past decade, the predominant view on digital content has been that shorter is better, with links that don’t cause the user to bounce off a website. But sometimes stories need to be longer, and they need those additional links for context. In 2017, publishers will experiment with new tools in order to lead readers down intentional rabbit holes.

ExamplesIn 2007, a startup called Apture tried to solve the bounce problem by allow-ing users to search and explore content without leaving the page. Highlighting a word or phrase could bring up a box with layers upon layers of information, as a sort of digital rabbit hole. Editors could manually insert additional informa-tion, or Apture’s algorithm would surface related content from trusted partners. It was a tremendous innovation—a news story with a lot of complicated terms and subjects that could offer heady subset explainers as well as historic videos, dis-senting viewpoints, detailed information about sources and more. Why would a reader leave the page when a smart editor had already anticipated and answered all of her questions? The entire Apture team was acquired by Google in 2011.


CNN created an experimental conversational news bot for Messenger.

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Conversational InterfacesFirst year on the list

WatchlistChatfuel; Pandorabots; CNN; BuzzFeed; Amazon; Google Now; Washington Post; New York Times; Facebook; McClatchy Corporation; News Corp; BBC News; Guardian; Microsoft; Axel Springer; Vox; Mic.

Key InsightWe are entering an era of conversational interfaces. You can be expected to talk to machines for the rest of your life.

ExamplesIn the late summer of 2016, CNN deployed a conversational news bot on Face-book Messenger that you could talk to about the Olympics, while BuzzFeed released a bot to help with their reporting on the Republican and Democratic National Conventions. Whether it’s Google Now on your phone, or a device like Alexa, beginning in 2017 you and your devices will have conversations about the news.

What’s NextConversational interfaces can simulate the conversations that a reporter might have with her editor, as she talks through the facts of a story. Bottable interfaces and platforms, such as Pandorabots and Chatfuel, will start to replace standard search and FAQ’s. Meanwhile, journalists will engage in conversations with ma-chines to assist in reporting. IBM Watson’s various APIs, including Visual Recog-nition, AlchemyLanguage, Conversation and Tone Analyzer can all be used to assist reporters with their work.


This listicle became the gold standard for many journalists in 2013.

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Dynamic ListiclesFirst year on the list

Key InsightA listicle is a short-form of explanatory writing that uses a list as its structure. Dy-namic listicles are that same content made interactive via chatbots.

ExamplesIn 2013-2015, listicles were everywhere. One of the most popular New York Times stories during that period was “52 Places to Go in 2014.” Listicles are still the bread-and-butter of newer startups like Upworthy, BuzzFeed and Vox. Because of the structured nature of listicles, they are perfect material for chatbots.

What’s NextIn September, in her annual presentation at the 2016 Online News Association conference, Future Today Institute founder Amy Webb discussed the emergence and promise of dynamic listicles. They can be used for a number of different sto-ries: elections, breaking news events, public health epidemics, sports and more. News outlets of all sizes and journalists working inside of various organizations are now starting to experiment with them.

WatchlistWorld Bank; State Department; Russia Today; CNN; BuzzFeed; Washington Post; McClatchy Corporation; New York Times; Vox; Refinery29; Upworthy.


Google recently added a Fact Check tag to its Google News stories.

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Real-Time Fact CheckingSecond year on the list

WatchlistIBM Watson; Alphabet (Google); Facebook; Twitter; various news organizations; various activist and political groups.

Key InsightBuoyed by new technologies and our recent election cycle, real-time fact-check-ing will be a priority in 2017.

ExamplesDigital tools have made it easy to report on a live event and publish in real time, but adding context—such as whether or not a source’s statement is factually ac-curate—usually happens after. In 2009, the Tampa Bay Times won a Pulitzer for its PolitiFact project, which fact-checked the presidential election. PolitiFact is now an independent journalism website where reporters and editors fact-check statements made by the government, political candidates and advocacy groups. In 2011, MIT student Dan Schultz launched Truth Goggles, which originally en-abled users to fact-check stories on the Internet. Truth Teller was mechanized, transcribing videos using speech recognition, and it eventually pivoted into a broader annotation tool. In 2016, the presidential debates were fact checked by a number of groups, including National Public Radio (NPR), the Washington Post, and even Hillary Clinton’s own staff. The efforts were people-powered.

What’s NextLate in 2016, Google introduced a fact-check tag to its Google News service: readers can see fact checks next to trending stories. As we saw in this most re-cent election cycle, inaccuracies and falsehoods quickly spread on social media masquerading as the truth. News organizations have a tremendous opportunity to use AI along with social media data and their own article databases, to build tools for real-time fact checking, adding a critical editorial layer that’s both good for the public interest and good for building brand reputation.

VideoSixth year on the list

Key Insight U.S. adults now spend close to an hour a day watching online video, and in-creasingly we’re using our mobile phones to access that content. But not all adults prefer video. An October Pew Research Center survey found that more Americans prefer to watch their news (46%) than to read it (35%) or listen to it (17%). But the demographics might surprise you: Americans age 50 or older prefer video, while the majority of 18 to 29-year-olds (42%) prefer reading the news. Still, advertising and marketing budgets are flowing freely to the agencies creating video—and to the platforms distributing it. Video ad spending topped $5 billion in 2016.

050 Connected TVs TVs that connect to the internet certainly aren’t new. What’s changed is penetra-tion in average households and the availability of streaming apps that bypass the standard list of cable and public broadcasting channels, such as Amazon Prime Video, Hulu, YouTube, iPlayer (UK-only), All 4 (UK only), Playstation Now, Crack-le, HBO GO, and of course, Netflix.

051 Cord CuttingThanks to the Connected TV trend, more and more people are ending their cable subscriptions. What’s new is that cord cutting now extends to subscribers drop-ping their expensive internet services. According to Pew Research, last year 13% of adults used only their smartphones to connect to the internet, while only 67% of adults have home broadband connections. The cord cutting trend should be at the forefront of conversations within Comcast, Time Warner Cable and Charter

Communications, for whom broadband subscriptions had been filling the widen-ing cable TV subscriber gap.

052 WebRTC WebRTC is the real-time communications technology powering Google Hang-outs. WebRTC can be used to connect your smartphone to the articles you’re reading on your desktop or tablet, displaying different components depending on what offers the best user experience. If a video won’t display well on your current device, you could be offered a different version automatically. Because WebRTC works from the browser (Firefox or Chrome), it’s also part of one of the other trends we’re continuing to watch: connected machines. Rather than bridging computers to networks, which must route and relay information along various channels, WebRTC and similar peer-to-peer technologies help computers to talk to each other without obstruction. This may seem like a subtle change in Internet architecture, but consider the implications: you would no longer need a third-party operator, like Skype, to video conference with a friend. Games would load and play faster. Pandora and Spotify wouldn’t need to buffer.

053 Streaming Social VideoFacebook, Snapchat, Instagram and Twitter all offer live streaming video servic-es—to anyone, for free. This means that for the first time in history, no technical knowledge or specialty equipment is required to broadcast the news. As a result, we are seeing a number of newsworthy events now appearing, completely unfil-tered, across social media channels: funerals, arrests, political rallies, conference speeches, encounters with public officials.

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Digital video will continue to grow in 2017.



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Google recently added a Fact Check tag to its Google News stories.

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Media ConsolidationSecond year on the list

WatchlistViacom; Time Warner; News Corp; Discovery; Bloomberg; Disney; Comcast; Amazon; AT&T; Vox; Vice; HBO; Netflix; BuzzFeed; Facebook; Twitter; Alphabet (Google).

Key InsightWe are starting to see a handover of sorts: the shrinking of traditional media com-panies just as newer media organizations are consolidated under single owners.

ExamplesTwo oft-repeated rumors in 2016 were that Apple wanted to buy Netflix and Time Warner, and that either Disney or News Corp. would buy Vice Media. The fact that so many people were ruminating about the acquisitions does highlight just how much consolidation is underway. Within the past two years, Univision won the bankruptcy auction for Gawker Media Group (and killed Gawker.com after the sale). AT&T, which owns DirecTV, considered bids for Starz, Paramount Pictures, and in the end, won Time Warner. Re/code became part of Vox, which became part of NBC, which a while back became part of Comcast. Verizon ac-quired AOL. The Financial Times was acquired by Nikkei (for a staggering $1.3 billion). Will BuzzFeed be next? Will Amazon acquire Vox? Will Bloomberg buy the Atlantic? Will Facebook and Twitter merge? Or will Facebook eat the whole media landscape?

What’s NextThe next 24 months will be about rapid product creation and monetization in a rush for investment and exits. By the year 2021, it’s possible that AT&T, Verizon, Comcast, Charter and Amazon will have replaced CBS, Viacom, the New York Times, Hearst and Conde Nast as the biggest news and entertainment media brands in the U.S.


IBM’s News Explorer helps reporters and researchers see connections between keywords.

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Computer Assisted Reporting v2.0First year on the list

WatchlistIBM Research; Alphabet (Google).

Key InsightComputer Assisted Reporting (or CAR, as its known by news industry profes-sionals) is an investigative journalism technique. Reporters find, clean and mine public records and documents, crunch data and uncover hidden stories. Aided by machine learning algorithms and AI, this next iteration of CAR, or CARv2.0, will augment the skills of journalists and allow them to analyze data and connect dots.

ExamplesIt’s one thing to find and mine public data—analyzing what’s there, and connect-ing the seemingly unconnectable dots, is another challenge entirely. Cognitive computing systems are allowing journalists to combine what they find in the data and then see the connections between facts, keywords and concepts. In this way, they can reveal interconnected relationships between people and organizations that they might not have otherwise seen.

What’s NextNews organizations will soon have access to new CARv2.0 tools from IBM’s Alchemy News API, including its News Explorer. Investigative teams will incor-porate machine learning techniques into their current workflows to help them discover context and meaning within the data. In 2017, we will be watching Pro-Publica especially, which has been doing a stellar job of building and using tools for investigative reporting.


Waze is a platform that can also be used for crowdlearning.

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CrowdlearningFirst year on the list

WatchlistAlphabet (Google); Apple; Microsoft; Investigative Reporters and Editors (profes-sional association); the National Institute for Computer-Assisted Reporting; vari-ous U.S. government websites; various state and local government websites; the websites of government agencies worldwide; various news organizations.

Key InsightYou’re familiar with crowdsourcing: asking the public to contribute content or to assist with on-the-ground reporting on an issue. Crowdlearning is querying our passive data—our mobile and online activity, our public health records, our loca-tions—to learn or understand something new.

ExamplesIn June 2016, the evening after citizens in the United Kingdom voted for Brexit, Google revealed sobering search data: people in the UK were Googling “what is the EU.” This passive data told an interesting story, and it’s just part of what we’re now able to learn from the crowd by monitoring various networks. Our smartphone ownership has reached critical mass, and so has our use of various networks. Our data not only follows us around, it’s often available for anyone to search, collect and analyze.

What’s NextGood crowdlearning sources are already available to us, and they include Health-Data.gov, Google’s busy times data for businesses and public spaces, Waze, Wikipedia and more. We anticipate that more news organizations—as well as marketers, activists and other groups—will start harnessing data in creative ways. That’s because our thinking results in behavior (like searching for “what is the EU?”). Our behavior results in data. And that data can be used to learn something about us.


Many people use ad blockers to improve their experience or to protect their privacy.

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Blocking the Ad BlockersFirst year on the list

WatchlistInteractive Advertising Bureau (IAB); retargeting companies (Criteo; AdRoll); creative optimization companies (AdExtent; Ad Ready); agency trading desks (Cadreon, Xaxis); exchanges (OpenX, doubleclick, Facebook Exchange); media planning; ad networks (Alphabet, AOL, Amazon, Facebook); targeted networks; mobile-specific networks.

Key InsightAd blockers are software that automagically remove ads from webpages. Typi-cally, they are browser (Chrome, Firefox) extensions. Soon, publishers will deploy their own ad blocker-blocking tools.

ExamplesOften, people who use ad blockers are doing so either because ads slow down a site’s loading time, or because the ads served are offensive, inappropriate for kids, or aren’t safe for work. Last year, German publisher Axel Springer released a new system that prevented readers from loading the Bild news site until they turned off their ad blockers. In December 2015, Forbes followed suit—so did Wired in February 2016. All of the publishers showed a note instructing readers to whitelist them in the blocking software—but there are still ways of getting to their content (RSS, “reading mode,” or incognito/ private mode within browsers).

What’s NextInternet researchers have discovered that readers aren’t likely to whitelist sites—it’s not that they object to advertising, but rather to seeing inappropriate ads, or to being tracked by the code that marketers use. According to internet tracking service Alexa, Axel Springer’s Bild bounce rate skyrocketed from 2% up to 40% and time spent on site down 6%. The other sites have fared no better. Publishers will need to spend time in 2017 developing a different strategy for ad blocking, whether that’s allowing readers an incentive for displaying ads, or allowing them to choose what kind of ads to show. Which also means that publishers will need to work closely with ad serving companies and online advertisers to ensure that the right kinds of ads are being shown.


NLG can be used to help readers of all levels engage with a story.

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Natural Language Generation for Reading LevelsFirst year on the list

WatchlistArria NLG; Narrative Science; Expect Labs; Automated Insights; Department of Computing Science, University of Aberdeen; School of Science and Engineering, University of Dundee; Research Center on Information Technologies (CiTIUS), University of Santiago de Compostela, Spain; School of Informatics University of Edinburgh

Key InsightNatural Language Generation (NLG) is a processing task, where computers gen-erate the kind of language humans would use in a designated situation. NLG can be used to rewrite content for a variety of different reading levels.

ExamplesIn 2015 and 2016, many companies—including Credit Suisse, Deloitte, and a num-ber of news organizations—were already using Narrative Science, an NLG pro-vider. A basic set of data was processed with an NLG algorithm to produce a readable story, which sounded no different than if a human had written it.

What’s NextAs news organizations search for new revenue streams, and as marketers try to expand their global reach, NLG will be used not just to write stories—but to create different versions for audiences with varying reading skills. That’s because the basic corpus—the data that makes up the story—wouldn’t change, but the vocabulary and amount of detail could be adjusted. For example, a single story about the results of Berkshire Hathaway’s quarterly earnings could be rendered in many different ways: for finance professionals, for high school economics class-es, for beginning English as a second language learners, and for MBA students in non-English speaking countries.


The International Consortium of Investigative Journalists spent a year reporting on a massive cache of 11.5 million leaked records known as the Panama Papers.

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LeakingFirst year on the list

WatchlistWikiLeaks; journalism organizations and professional associations; political lead-ers; government agencies; lawyers; C-suite executives.

Key InsightThe Panama Papers were leaked by a law firm in 2016.

ExamplesThe most famous leak in modern history happened when former National Se-curity Agency contractor Edward Snowden leaked thousands of sensitive gov-ernment documents. U.S. Army Private Chelsea (formerly Bradley) Manning up-loaded a mountain of classified military and diplomatic documents to WikiLeaks, which has become the politically-embattled bastion for leakers. In October 2016, the U.S. government officially accused Russia of hacking into the Democratic National Committee and releasing sensitive emails. Meanwhile, the International Consortium of Investigative Journalists—a collaboration between 370 journal-ists from 76 countries—spent a year reporting on a massive cache of 11.5 million leaked records showing the offshore holdings of 140 politicians from around the world, 12 current and former world leaders, and more. The records, known as a the “Panama Papers,” were sent from a little-known law firm in Panama.

What’s NextWe expect to see more coordinated leaking efforts in the year ahead. In 2017, governments, banks, and corporations will be targeted. Organizations should de-velop risk management plans in advance; meanwhile, journalists should develop collaborative partnerships and workflows ahead of the next leak. We also see an opportunity for data journalists and for those with specialized skill sets, adept at organizing and parsing structured data. Their particular talents will be in greater demand in the years ahead.


Will bots have their day in court in 2017?

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The First Amendment in a Digital AgeFirst year on the list

WatchlistACLU; Jack Balkin, Knight Professor of Constitutional Law and the First Amend-ment at Yale Law School; Margot Kaminski, Assistant Professor, Moritz College of Law, The Ohio State University.

Key InsightIt may seem odd to include the Bill of Rights, which were ratified 225 years ago, in an emerging tech trends report. But recent discoveries in how our technology renders speech will result in First Amendment challenges in the years to come.

ExamplesThe Random Darknet Shopper was an art project and automated shopping bot. It was programmed to spend $100 in bitcoin every week on a random purchase within a specific online marketplace. However, in 2015 it bought 10 ecstasy pills and a falsified Hungarian passport. Meantime, in March 2016, Microsoft’s Tay.ai bot went on an anti-Semitic, homophobic, racist rampage. The bot was de-commissioned within 24 hours, but screenshots of its automatically-generated tweets are all over the internet. Legal scholars are already starting to study the free speech of bots, and how the First Amendment applies to them. Is the speech of a bot protected? If not, who’s libel? The bot? The bot’s well-meaning develop-er? The brand?

What’s NextThe problem isn’t just limited to the U.S. In 2015, a bot programmed by Am-sterdam-based Jeffrey van der Groot autonomously wrote and tweeted a death threat, which resulted in Dutch police having to figure out whether or not a crim-inal charge was even possible. In 2017, we will see more internet trolling, social media bullying, bias in code, chatbots that act with autonomy, and AI agents, and as a result we anticipate legal challenges worldwide in the next few years.


IMAGE: Emily — can you find something that looks like data?CUTLINE: Synthetic data sets could help programmers build software without raising privacy concerns.

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Synthetic Data SetsSecond year on the list

is working on datasets that can be shared by researchers all over the world. There are applications for synthetic data sets across numerous fields, from bioinformat-ics to macroeconomics to international relations to data-driven newsgathering.

WatchlistDataONE; U.S. Census; Purdue University; Duke University; University of New Mexico; U.S. Geological Survey; ESA Data Registry; Knowledge Network for Bio-complexity; SANParks Data Repository; U.S. National Science Foundation

Key InsightIn the wake of privacy scandals, researchers are starting to experiment with syn-thetic data sets to perform meaningful analyses. This would increase the value of datasets that everyone uses—such as the Census—while protecting their confi-dentiality.

ExamplesA number of agencies collect detailed information for the purpose of generat-ing statistical models. For example, the U.S. Census Bureau gathers a wealth of information, such as age, gender and income. It also collects similar data on businesses, including annual payroll and employment. While this information is vitally important to researchers, allowing everyone access to it presents a priva-cy challenge. For example, programmers need data sets to create and test new algorithms. But the numbers matter—so creating a statistically identical set of 1000 people without divulging their exact details has been a difficult task. Dur-ing the past few years, a number of new approaches have been tried, including the experimental Synthetic Longitudinal Business Database (SynLBD) from the Census Bureau.

What’s NextEven synthetic data still needs to be verified. While some researchers argue that synthetic datasets aren’t useful beyond testing algorithms and computer mod-els, we think that increased privacy concerns will lead to the creation and use of more sets like the SynLBD. The Data Observation Network for Earth (DataONE)


Project Malestrom is a web browser built on torrent technology.

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TorrentsSecond year on the list

WatchlistBitTorrent

Key InsightTorrent files include information on how to download a larger file using the Bit-Torrent protocol. BitTorrent is a sidestep around centralized servers, instead mov-ing data across the Internet in a more distributed way.

ExamplesPeople use torrents for all kinds of reasons, from blocking an ISP’s ability to see your location on the network to sharing large files. BitTorrent makes it easier to distribute those large files without eating up lots of bandwidth.

What’s NextIn 2016, BitTorrent launched BitTorrent Now, a video streaming service and news platform. Torrents themselves have applications beyond peer-to-peer file sharing. Think of torrents as a new kind of Internet that’s hosted in the crowd rather than the cloud. In 2015, BitTorrent released a public beta of Project Maelstrom, a web browser built on the same underlying technology. Some argue that a distributed browser system could prevent an ISP from throttling certain sites or users. Mael-strom also allows content to be published that doesn’t actually live on a server—rather, your browser would connect to others online who are also viewing the site or who have viewed it recently. This could thwart would be denial-of-service at-tacks, which can take down a server. Torrent sites would be distributed between hundreds of thousands of browsers. Though what if that content was meant to harass someone instead? Or if it was incorrect? Or if a virus was embedded? It’s fascinating to think of the future, alternate Internet.

Mixed RealityFourth year on the list

Key Insight Mixed Reality (MR) combines the physical and digital realms and encompasses a number of technologies: augmented reality (AR), virtual reality (VR), 360-de-gree video and holograms.

What You Need To Know About MR AR, VR, 360-degree video and holograms aren’t new. But in the year ahead, we’ll see more devices being made available to consumers at affordable prices—and we’ll see a number of new content providers building out stories and experienc-es for each platform.

063 Virtual Reality Virtual Reality (VR) is a computer simulated environment. As a tethered experi-ence, VR is experienced wearing a pair of goggles, and it can stimulate sensations of being physically present in the scenes a user is viewing. VR can be experienced untethered as well, by slipping a mobile phone into a special mask. In 2016, a number of headsets went on sale, and we expect to see more from Oculus, Sony, HTC, MergeVR and Google in 2017. Also new for the coming year: easier ways to shoot and render VR video.

064 Augmented RealityAugmented Reality (AR) doesn’t simulate an entirely new environment, but rath-er overlays information right onto your field of vision. But you need a lens and screen of some kind, whether that’s a mobile phone or a pair of glasses. In 2016,

90s favorite Pokemon made a comeback in the form of a mobile AR app called Pokemon Go. It’s massive popularity is catalyzing renewed interested in mobile AR integrations. Meanwhile, in the fall of 2016 Snapchat announced Spectacles, and while comparisons to Google’s failed AR Glass headset are easy to make, we urge you to resist the analogy. Snapchat’s glasses are primarily for shoot-ing video, but they necessarily include a personal dashboard, with AR included. Meantime, Magic Leap, which continues to raise investment funding, launched its developers platform—and it will be using a new kind of lightfield chip. Magic Leap projects light directly into the user’s eye instead, which makes it seem as though digital objects exist in the real world.

065 360-degree Video360-degree video is created with a special camera system capable of recording 360 degrees of a scene simultaneously. Once the video is rendered, viewers can use a mouse, their fingers, or gesture to watch the video from any perspective or angle. In 2016, YouTube and Facebook offered 360-degree videos, and we expect more platforms, including PlayStation, to offer it in the year ahead.

066 HologramsAt the end of 2015, holographic display startup LEIA released its SDK and a big-ger screen for a glasses-free viewing experience. Expect to see LEIA’s displays in everything from smartphones to watches to connected cars in 2017-2018. Also pay attention to consumer reaction to Microsoft’s Hololens technology in the coming year.

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Snapchat will offer its Spectacles AR glasses to the public in 2017.



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Cinematic VRVR created with video and images from the real world. (The alternative is com-puter-generated graphics.)

Eye trackingA system that can read the position of the user’s eyes while using VR. Eye track-ing software allows a user to aim correctly with her head while in a simulation.

Field of view (FoV) What a user can see in her visual field while in a simulation. The viewing angle for an average, healthy human eye is about 200 degrees, so a field of view close to or greater than that is optimal, because it creates a true sense of being within an environment.

HapticsIn addition to a VR headset, hand-held controllers are often used. Some are equipped with haptic feedback, which gives the user the sensation of touching something in the simulated environment or receiving touch-back reactions.

Head mounted display (HMD)This is the headset you’ve seen people wearing. It typically includes a strap both around and over the head, which secures the screen to your face. Some HMDs include built-in headphones as well as sensors for head tracking.

Head trackingSome HMDs are equipped with special sensors that track the exact movements of the user’s head. The sensors then send feedback to the system, which moves the images and audio a user experiences in her field of vision in real-time.

In-ear monitors (IEM)These are earbuds that work with head mounted displays that don’t offer built-in headphones.

LatencySometimes, the system isn’t capable of showing the images in exact synchroni-zation with the user. When that happens, a user moves her head, but the images she’s seeing lag behind a few fractions of a second. This lag is a reason why some people experience “simulation sickness.”

PresenceWhen a user feels as though she’s fully immersed within a simulation, like she’s actually there, she’s achieved “presence.”

Refresh rateHow quickly the images are updated. Higher refresh rates cut down on latency and provide a more realistic simulation. Ideal refresh rates are above 60 frames per second.

Room scaleThis is the tethered version of VR that offers users the capability of walking around a room and interacting with virtual items, as they walk around in the physical world. So if you take a step in the real world, you’re also taking a step in the virtual simulation. For this to work, rooms need to be mapped in advance.

Social VRWhen two or more people are wired in to a VR simulation and able to share the experience by observing each other, interacting or participating in joint activi-ties.

StitchingThe process of combining video from different cameras into one, spherical vid-eo suitable for VR. This typically requires a tremendous amount of editing to fill in gaps, reorient scenes and seamlessly meld video streams so that the simula-tion looks authentic.

VR faceWhen a user has been in a simulation, a few things happen: the head mount-ed display tends to leave a temporary imprint on the skin, not unlike a pair of swimming goggles. Users also tend to relax into a slack-jawed look, with their mouths slightly agape.

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Virtual Vocabulary: A mini-glossary for the virtual reality terms you’ll need to know in 2017.


SecurityFourth year on the list

Key Insight A lack of planning and oversight led to significant cyber attacks—on govern-ment, businesses and individuals—in the past year. We predict even more so-phisticated attacks in 2017.

067 Data Retention Policies Many organizations—from financial institutions to universities, hospitals, veteri-narians, churches, Fortune 500 companies and beyond—store data for compli-ance, business or customer convenience. In the year 2017, every organization will need to address best practices in data retention, with an eye toward security. You would be surprised to know how few organizations have responsive data reten-tion policies that are updated according to security issues—and for that matter, how many organizations don’t even have policies at all.

068 Remote Kill SwitchesMid-2016, both Alphabet (Google) and Apple readied kill switches, capable of re-motely wiping out all of the information on a smartphone. If someone steals your phone, you’d have the ability to render it—along with all of your data—complete-ly useless. While these aren’t yet available to consumers, kill switches would be useful for the enterprise and for government agencies. The benefit would come with a cost, however. Kill switches would mean that nobody could gain access to what’s inside a lost or stolen phone—not even law enforcement.

069 Zero-Day ExploitsItalian spyware maker Hacking Team (HT) had been selling commercial hacking software to law enforcement agencies in countries all over the world—until it got hacked. Data leaked from HT, along with a massive dump of 400 gigabytes of in-ternal emails, revealed a number of zero-day exploits. In the hacking community, zero days are prized tools because they are undisclosed vulnerabilities that can be exploited. Once the flaw is revealed, programmers have zero days to do any-thing about it. The HT breach helped to shine a light on a growing zero day mar-ketplace, with some exploits being sold for as much as $500,000. Just because HT was exposed doesn’t mean that the marketplace for zero-days has dried up. On the contrary, this software will be in greater demand in 2017.

070 BackdoorsIn the wake of the deadly San Bernardino attack in December 2015, the FBI and Apple found themselves debating so-called “backdoors” in public. The FBI de-manded that Apple unlock the assailant’s phone, and Apple refused, arguing that creating a software update to allow a backdoor would endanger the privacy of us all. While they sound malicious, backdoors aren’t necessarily bad. Often, de-velopers intentionally install them into firmware so that manufacturers can safely upgrade our devices and operating systems. The challenge is that backdoors can also be used surreptitiously to harness everything from our webcams to our per-sonal data. In 2017, government officials will be advocating for a set of “golden keys,” which would allow law enforcement to break through the security using backdoors. Opponents argue that the simple act of creating a backdoor would

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In 2016, Apple and the FBI fought over backdoors.



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072 DarknetsMany people confuse the deep web—hidden parts of the Internet that aren’t usu-ally indexed by search engines—with darknets, which are niche spaces promising anonymity often for illegal activities. There were ongoing, international pre-emp-tive strikes against darknet operations in 2015 and 2016. In the coming year, we’ll see additional layers of protection for those wanting to access darknets, while law enforcement will receive training on how to navigate the dark web. For gov-ernment and law enforcement, the challenge of training is that it is static. Those accessing darknets are typically also the ones building them.

073 Open Source App Vulnerabilities In recent years, we have seen some devastating breaches in open-source pro-jects: Heartbleed and Shellshock. Hackers exploited vulnerabilities that had exist-ed for a long time but had been left unchecked and full of bugs. In the aftermath of Heartbleed, Dell, Google and other companies donated funds to help shore up OpenSLL. The Linux Foundation launched a Core Infrastructure Initiative to help stave off the next wave of attacks. Still, many organizations use open source tools, and in 2017 they must perform weekly–not occasional–security checks.

074 Selfie SecurityIn 2011, the Future Today Institute forecasted that within five years, we would see the advent of two or three-factor authentication using a combination of bi-ometrics and gestures instead of passwords. Our timing was correct: in an effort to combat weak passwords (and weak password encryption), some companies

leave ordinary people vulnerable to everyday attacks by even unskilled hackers. It turned out that by May 2016, law enforcement had gotten into the phone, with-out Apple’s help. While the case is officially settled, the issue isn’t going away—expect to hear more about backdoors and golden keys in the coming year.

071 GlitchesGlitches are problems that don’t have an immediate, obvious cause but nonethe-less can cause frustrating problems. In 2013, technical glitches caused a three-hour stop at the Nasdaq. In 2016, a glitch grounded the entire Southwest Airlines fleet, and it took several days for the airline to get back on schedule. Technical glitches halted trading at the New York Stock Exchange recently. Glitches cause temporary outages—and big headaches—for streaming providers such as Dish’s Sling TV, which interrupted service during the premiere of Walking Dead spinoff Fear the Walking Dead. Glitches at Netflix have caused outages as well as strange mashup summaries for different films. A favorite: “Inspired by Victor Hugo’s nov-el, this Disney film follows a gentle, crippled bell ringer as he faces prejudice and tries to save the eyes of individual dinosaurs.” In many cases, glitches have to do with degraded network connectivity or a miscalculation of the bandwidth need-ed. But a lot of times, glitches have to do with newer technologies, which we are learning break in unexpected ways.

DARPA’s new Cyber Grand Challenge asks hackers to build systems that can hack faster than humans.

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in our homes and offices (climate controls, locks) and more. Security expert Bri-an Krebs says that the “market for finding, stockpiling and hoarding (keeping secret) software flaws is expanding rapidly” and went so far as to advocate for a compulsory bounty program. In response, a number of white hat (good hacker) bug bounty programs are becoming popular. HackerOne is being used by Slack, Twitter, Square and MailChimp. Friendly hackers hunt down potential vulnerabil-ities and get paid for their work.

076 Automated HackingThanks to advancements in AI, one of the big trends in security is automated hacking—in short, software that’s built to out-hack the human hackers. The Pen-tagon’s research agency DARPA launched a Cyber Grand Challenge project in 2016, with a mission to design computer systems capable of beating hackers at their own game. While it can take several months or even years for humans to spot malicious code or vulnerabilities, DARPA hopes that smarter automated sys-tems can reduce the response time—and fix—to just a few seconds.

077 Offensive Government HackingIn the wake of several hacking attacks against the U.S. government and elected officials in 2016, the Obama administration signaled out Russia as a persistent threat. Some elected officials argued that the two agencies responsible for cy-berwarfare—the U.S. Cyber Command and the National Security Agency—will likely split and start playing offense, especially as artificial intelligence becomes a focus for U.S. cyber strategy. Meanwhile, look for a buildup of highly-skilled ex-perts joining the effort to meet emerging threats in 2017.

will be using two-factor sign-ons that sidestep passwords entirely. Apple was recently granted a patent for “low threshold face recognition,” which would help our phone cameras identify us, even if we’ve just dyed our hair blue. MasterCard is using with selfie-scans: at the checkout, users have to hold up their phones to take a photo. Since launching its fingerprint scanning tools in 2013, Apple has had success with biometric security—and little customer protest. So MasterCard is following suit, using a combination of fingerprint scans and our faces, as a two-factor biometric authentication. We expect to see more companies moving away from standard passwords in the coming year. But it does raise an interesting question about the security of biometric databases. It’s easy to change your pass-word if you get hacked. How would you replace your face, eyes or fingerprints?

075 Prize HacksThe past two years have been dramatically successful for hackers. 2017 will bring an onslaught of new technologies (and their payment systems)—not to mention new geopolitical and corporate realities. The governments in the U.K. and U.S. will be transitioning power just as political tension escalates between established democracies and their would-be detractors. Corporate scandals in 2016—Wells Fargo employees creating millions of phony accounts, Volkswagon’s software that misreported data to the Environmental Protection Agency’s emissions trackers—have stoked the ire of many consumers. Cybercriminals tend to be mo-tivated by these events. They will target larger, more prestigious prizes: banks, corporations, governments, financial institutions, universities, health and medical records, marketing databases, our taxes. To date, attacks that have made big headlines have been about hackers taking data—but exploits can also mean infil-trating the computer systems in our cars, in our infrastructure (airplanes, trains),

During the past election cycle, WikiLeaks became weaponized.

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078 Cyber Mission Forces in the FieldIn the summer of 2016, the U.S. military began deploying its Cyber Mission Force. These are units of civilians and military personnel, and they are charged with protecting our national infrastructure and our military networks from cyber in-trusions. Some of the units also support combat missions. We expect that the force could be in build-out and training mode in the next year and fully capable towards the end of 2018.

079 Weaponizing WikiLeaksWhat happens when a government leaks a cache of sensitive information on WikiLeaks, with the intent of destabilizing another nation? WikiLeaks becomes weaponized. In July 2016, WikiLeaks published 20,000 emails from the Demo-cratic National Committee. By fall, the Obama Administration named Russia as the source of the hacked data, citing Russian President Vladimir Putin’s desire to influence the U.S. presidential election. Given the rising political and social ten-sions within the U.S., Europe, Russia and Middle East, we are sure to see more leaks in the coming year.

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AdwareSoftware that automatically generates online ads; it can also include spyware that tracks your browsing habits. It’s because of adware that many people are turning to ad blocking software. (see the earlier “Blocking the Ad Blockers” trend.)

AnonymousA collective of hackers, best known for its use of the Guy Fawkes mask and dis-tributed denial of service (DDoS) attacks. Anonymous typically uses the hash-tag #Ops when announcing a new campaign. Past ops included a takedown of the Church of Scientology and the Westboro Baptist Church.

AttributionResearching and tracking back the origins of an attack.

BackdoorDevelopers intentionally install backdoors into firmware so that manufacturers can safely upgrade our devices and operating systems. The challenge is that backdoors can also be used surreptitiously to harness everything from our web-cams to our personal data.

Black hatA malicious hacker; someone who hacks for personal gain.

BotBots are automated programs that performs a simple task. Some—simple chat-bots, for example—are completely harmless. Other bots can be programmed to repeatedly guess passwords so that a hacker can break into a website.

BotnetA botnet is a group of computers that are being controlled by a third party, and are being used for any number of nefarious purposes. For example, malware in-stalled on your computer can run, undetected, in the background while hackers use your machine as part of a large spamming network.

Brute force attackThis type of attack is a laborious, methodical process where a hacker uses soft-ware to automatically guess every password it can to gain unauthorized entry into a network or computer.

BugA flaw or problem in a program that can be harmless or might allow hackers to exploit a system.

CompilerA program that translates source code into executable machine language. Compilers are used to surreptitiously allow hackers into various systems with-out changing the source code, making it easier for them to get into a computer or network without being noticed.

Cookie A small file sent from your computer’s web browser to a server. Cookies help websites recognize you when you return, and they also help third parties track audience.

CrackingA basic term that describes breaking into a security system. Anyone “cracking” a system is doing so maliciously.

CryptoCryptography (or “crypto”) is the art and science of encrypting data—as well as breaking encryption.

Deep web/net and Dark web/ netThe deep and dark net/web are actually two different things, though they’re often conflated. The deep net or deep web is the vast trove of data that isn’t indexed by search engines. Spreadsheets, databases and more that are stored on servers make up this space. The dark web/ net is made up of sites that are in-visible unless you know how to use a special network, such as Tor, which knows how to find the dark side. Once there, you’ll find what you might expect: pirated software and content, job ads for hackers, illegal drugs, human trafficking, and worse.

Hacker Terms and Lingo You Need To Know For 2017


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Denial of service attack (DoS)This is when a hacker sends so many requests to a website or network that the traffic temporarily overwhelms the servers, and the site or network goes down.

Distributed denial of service attack (DDoS)This is a DoS using a battalion of machines.

DEF CONThis is a big, annual conference for hackers that attracts people from all over the world. Discussions range from highly technical and academic to those about policy. It takes place in Las Vegas every August.

Digital certificate These authenticate and approve the identity of a person, organization or ser-vice.

DoxingWhen hackers root out and publish personally-identifying information about someone online.

DumpThe term for a trove of data released by hackers.

Dumpster divingOrganizations and individuals who don’t consistently use a shredder are open-ing themselves to dumpster diving, which is exactly what it sounds like: hackers go through garbage looking for any information that will help with an exploit.

EncryptionUsing special code or software to scramble data so that it cannot be read by a third party, even if it is intercepted.

End-to-end encryptionWhen an encrypted message is scrambled on both ends, as it is sent and again as it is received.

ExploitThe general term for leveraging a vulnerability in a piece of code, software, hardware or computer network.

FirewallA system of software and hardware that’s designed to prevent unauthorized access to a computer or computer network.

Grey hatHackers are just like the rest of us. Some have malicious intent, others just want to fight the bad people, and some...have a certain tolerance for moral flexibility. Gray hats will use the tools and sensibilities of a black hat in the pursuit of jus-tice.

HackerThis term means different things to different people. People who tinker with code, to purposely manipulate it, are hackers. Some are good, and some are bad. In popular culture, “hacker” has taken on a distinctly negative connotation.

HactivistSomeone who hacks for social or political reasons.

InfoSecThis is an abbreviation for “information security.” Companies and professions that work within cybersecurity are known as InfoSec.

IRCInternet relay chat protocol (IRC) has been around forever. It’s the communi-cation system used to have conversations and share files, and it’s still used by hackers.

JailbreakA way of removing the restrictive manufacturer’s code from a device so that you can reprogram it to function as you desire.



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KeysThe code that, just like a physical key, is used to lock or unlock a system, en-crypted message or software.

LulzA play on “lol” or “laughing out loud,” black hats often use the term “lulz” to justify malicious work. LulzSec (“lulz security”) is yet another offshoot of Anon-ymous, and it was credited with the massive Sony Pictures hack.

MalwareAny software program that’s been designed to manipulate a system, by stealing information, augmenting code or installing a rogue program. Rootkits, keylog-gers, spyware and everyday viruses are examples of malware.

Man-in-the-middle (MitM) attacksThis occurs when a hacker impersonates a trusted connection in order to steal data or information or to alter communications between two or more people.

MetadataThis is the data that explains what’s in another set of data, such as a jpeg photo, or an email, or a webpage.

Password managersThese are third-party tools that you entrust your passwords to. Just remember one master password, and use it to unlock a database of all your other pass-words, which should allow you to use a completely different password for every site and service you use. While managers are a good idea in theory, many are cloud-based. If a hacker gains access to your password manager, you’re in big trouble. If you do use one, make sure to use complicated password at least 36 characters long with lots of special characters, numbers and capital letters.

PayloadThe part of a computer virus that is responsible for the primary action, such as destroying data or stealing information.

Penetration testingThe practice of trying to break into your own computer or network, in order to test the strength of your security.

PGP PGP stands for “Pretty Good Privacy,” and you’ve probably seen a lot of PGP numbers showing up in Twitter and Facebook bios lately. PGP is a basic method of encrypting email (and other data). In oder to receive and read the message, your intended recipient must use a private key to decode it.

PhishingWe’ve all seen a phishing attack at least once. They usually come in the form of an email from a trusted contact. Once you open the message or attachment, your computer, your data and the network you’re on become vulnerable to at-tack.

PlaintextThis is text without any formatting. In the context of cybersecurity, it also refers to text that isn’t encrypted. Sony Pictures storing its passwords and email ad-dresses in a basic Excel spreadsheet is an example of plaintext.

PwnedSouth Park fans will remember Cartman using this word. It’s geek speak for “dominate.” If you’ve been hacked, you’ve been pwned.

RATRATs are Remote Access Tool. If you’ve used a remote login service to access your office computer while away from work, you’ve used a RAT. But RATs can be malicious, too. Just imagine a hacker using a RAT to take over your worksta-tion.

RansomwareThis is malware that allows a hacker to break into your computer or network and then take away your access until you pay a specified fee or perform a cer-tain action.



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Root The root is the central nervous system of a computer or network. It can install new applications, create files, delete user accounts and the like. Anyone with root access has ubiquitous and unfettered access.

RootkitRootkits are malware designed for root access. Often undetected, rootkits start running when you start your computer, and they stay running until you turn your machine off.

Shodan In Japan, a “shodan” is considered the first degree (read: lowest level) of mas-tery. In cyberspace, Shodan is a search engine for connected devices, allowing hackers access to baby monitors, medical devices, thermostats and any other connected device. It’s intended to help people learn how to secure their devic-es, but obviously it can also be used against them. (see http://shodan.io)

SniffingWhen you were a kid, if you drove around your neighborhood looking for open WiFi networks, you probably used a little device or a special computer pro-gram. Those are examples of sniffers, which are designed to find signals and data without being detected.

SpearphishingA more targeted form of phishing to smaller groups, typically within social net-works or work environments.

SpoofingIn general, anytime data is changed to mimic a trusted source, it’s being spoofed. Changing the “From” section or header of an email to make it look as though it was sent by someone else. Black hats spoof emails by impersonating people you know, and then launch phishing attacks.

Token A small physical device that allows a trusted, authenticated user to use a ser-vice. Tokens are stronger than passwords alone, since they require both the password and the physical device to gain access.

Tor The Onion Router, otherwise known as “Tor,” was originally developed by the U.S. Naval Research Laboratory to route traffic in random patterns so as to con-fuse anyone trying to trace individual users. The Tor Project is the nonprofit now in charge of maintaining Tor, which is used by both white and black hackers, as well as journalists and security experts.

VerificationEnsuring that data, and its originators, are authentic.

VPNVirtual Private Networks, or “VPNs,” use encryption to create a private channel for accessing the internet. VPNs are necessary when connecting to public net-works—even those at airports, hotels and coffee shops.

VirusMalware intended to steal, delete or ransom your files. Mimicking the flu, this type of malware spreads like a virus.

White hatNot all hackers are bad. White hats work on highlighting vulnerabilities and bugs in order to fix them and protect us.

WormWorms are a certain kind of invasive malware that spreads like a virus.

Zero-day exploitsIn the hacking community, zero days (also written as “0day”) are prized tools because they are undisclosed vulnerabilities that can be exploited. Once the flaw is revealed, programmers have zero days to do anything about it.



PrivacyFifth year on the list

Key Insight Ongoing breaches have continued to dismantle the public trust. According to a September 2016 Pew Internet and Society Report on the State of Privacy in America, 86% of Americans say that they have taken intentional steps to remove or mask their digital footprints, because they are concerned about protecting their privacy. They exhibited a deep lack of faith in organizations—from credit card companies, to email providers, to search engines and government agen-cies—promising to safeguard their privacy. According to the report: “While half of those surveyed said they felt confident they understood how their informa-tion would be used, 47% said they were not, and many of these people felt con-fused, discouraged or impatient when trying to make decisions about sharing their personal information with companies.”

080 AnonymityAnonymity is one of the digital trends we’ve been tracking as it has evolved dur-ing the past several years. The world needs anonymity, as it enables whistleblow-ers to come forward, and it shields those who otherwise might be persecuted for their beliefs. Digital anonymity allows us to band together in times of need, whether that’s to raise money for a good cause or to push back against injustices. However, just as we had predicted earlier, anonymity also means it’s easier to leak sensitive information, troll social media users, and leave disparaging or libelous comments all over the internet. In 2015, we forecast that most anonymous shar-ing apps won’t survive—indeed, Secret shut down, while Yik Yak came under fire for allowing cyber-bullying and for failing to prove that users real identities really are being protected. In 2017, our desire to post content anonymously won’t abate, even as our desire for verification grows.

081 Differential PrivacyThis is a technique that collects a vast amount of data from us, and then employs an algorithm to scramble that data so that it cannot be traced back to each indi-vidual. Differential privacy is typically used alongside machine learning to study a large group in order to spot emerging trends. Early in 2016, Apple announced that it would be using differential privacy, which may have sounded initially like a new security system. It is, in a sense—Apple will be studying our data to shore up its operating system and networks. What the company learns will eventually trickle back down to users. In the coming year, we expect to see more companies using differential privacy.

082 Digital Self-IncriminationIt is increasingly difficult not to be found. Technology is now much further ahead of the average person’s ability to understand it. One in five Americans owns a wearable device, but many do not know that by simply connecting the wearable to a network, they’re being monitored by a third party. Recently, a woman’s Fitbit data was used to unravel rape charges against her boss when it was discovered that she was awake and walking around during the time she claimed to be asleep. Privacy experts are raising questions about collecting our data and surreptitious-ly surveilling our movements. In the coming year, we expect to see growing de-mands for digital consent agreements and increased transparency.

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Many people are increasingly concerned about their digital privacy.



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086 Encryption ManagementWhat should encryption look like in 2017? We’ve seen dozens of big attacks in the past 24 months, and yet many of the organizations we entrust with our data are either not using encryption or are using tools that are out of date. Hackers know this, so we should expect more attacks in the coming year. While encrypting data makes it harder to hack, encryption can also make it harder for staff or consum-ers to make legitimate use out of the data. In 2017, companies will need to devote serious resources into shoring up their digital security, or risk losing multiple mil-lions of dollars cleaning up after a breach.

087 Eye In The Sky

Since January 2016, Baltimore police have been using “wide-area surveil-lance” run by Ohio-based Persistent Surveillance Systems. Aircraft carrying high-resolution cameras fly over the city continuously for up to 10 hours at a time, photograph a 30-square-mile radius, and then send that information back down to analysts on the ground. This technology allows police to surreptitiously track any person or vehicle within the area. The ACLU and a number of privacy experts have asked for a review of the system, citing the infringement of consti-tutional rights. So far, the system is being used in a number of cities throughout the U.S. We expect a wider-scale debate in 2017, about whether we should allow government agencies unfettered access to watch over us using “eye in the sky” systems.

083 TrollsThis most recent political season brought the worst out in us. Trolls from both sides of the aisle went into attack mode, posting hateful images, messages and videos all over the internet. This behavior started to become normalized the fall and winter of 2016, which means darker days are still ahead. There may be a tiny bit of light: a subsidiary of Google named Jigsaw launched mid-2016. In 2017, Jig-saw will be releasing a set of tools called Conversation AI, which are intended to use machine learning to identify the language of abuse and harassment.

084 AuthenticitySometimes a trend becomes so powerful—like digital anonymity—that it causes a fork, a divergent trend. In 2017, we expect to see new networks and servic-es launch that offer verification and authenticity, proving that the content and sources are reliable and accurate, even if they are anonymous.

085 Revenge PornIn October 2016, a 14-year-old girl brought suit against Facebook in Ireland. She was the victim of revenge porn: her parents said that the girl had been black-mailed, and the photo was posted to shame her. Although it was removed by Facebook several times, the photo was repeatedly posted by her attacker and not permanently blocked. That same month, another revenge porn victim, an Italian woman, killed herself. In the U.S., there is no national law banning revenge porn, and it’s not technically illegal in 25 states. Even with new and proposed leg-islation throughout Europe, revenge porn cases will be on the rise in 2017.

Google launched Jigsaw to combat trolls and nefarious actors.

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091 OwnershipWho owns all those videos you’re uploading to YouTube? Through its advertising program, a lot of individual people and organizations make substantial money from the videos they upload to YouTube, but there is nothing preventing some-one from copying that video and uploading it to Facebook or another platform. Because of the inherent sociability of outside platforms, videos may garner mil-lions of views—without any renumeration going back to the original content cre-ator. In 2017, as we continue to upload troves of personal data to social networks, photos and video sharing sites, wearable services and elsewhere, we will continue to question who owns the rights to our data.

092 Uploading Photos To Law Enforcement DatabasesThe FBI’s Next Generation Identification Interstate Photo System, or NIG-IPS, is a giant database storing more than 30 million photos to support criminal inves-tigations. Machine learning algorithms are deployed to find and compare those photos to people who are thought to commit crimes. There’s a privacy concern, however: not everyone in the database is a criminal. If you have a driver’s license from the states of Delaware, Utah, Tennessee, Texas, Michigan and Illinois (in ad-dition to many others), you’re in the database too. NGI-IPS will continue to grow and be used by law enforcement in 2017.

088 Right To Eavesdrop/ Be Eavesdropped OnAs we connect more and more devices to the Internet of Things—fitness trackers, mobile phones, cars, coffee makers—those devices are having extended interac-tions with each other and the companies who make them. Our devices aren’t just talking to each other anymore. They’re talking to one another, learning about us, and starting to talk about us. Increasingly, consumers are being left out of the conversation, unable to listen in and make sense of how their data is exchanging hands. A debate over consumer rights will heat up in 2017: should consumers be given the right to eavesdrop on what their own devices are saying?

089 Drone SurveillanceSoon, drones will be smaller and they’ll make far less noise. Coupled with emerg-ing camera technology, drones will be capable of capturing photos and video from 1,000 feet away—and identifying who we are—without our knowledge. In-terconnected drones will enable the mass tracking of people at concerts, vehi-cles on the highway, and shoppers during the busy 2017 holiday season.

090 Private NetworksIn reaction to the ongoing flood of Facebook and Twitter posts and, at least in part, to security breaches early on at Snapchat, private networks will gain mo-mentum during the coming year. Some to watch: Alively, a private network to share videos; Nextdoor, a network for neighborhoods; and MeWe, which offers private social networking and file sharing.

Privacy cont.

The FBI’s Next Generation Identification Interstate Photo System, or NIG-IPS, is a giant database storing more than 30 million photos to support criminal investigations.

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Organizations should prepare themselves for hackers posting private staff information online.

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Organizational DoxingSecond year on the list

Key Insight“Doxing” is mining and publishing personal information about a person—organi-zational doxing is when this happens to an entire company. It’s a term introduced by security expert Bruce Schneier.

ExamplesIn the wake of the Edward Snowden leaks, we’ve seen a number of data dumps. WikiLeaks has published troves of data. Hackers broke into Hacking Team, pub-lishing a massive amount of internal data. Sony has been breached, and so have various branches of the U.S. government.

This isn’t about stealing credit card information, but rather about making public the personal details of individuals, either to protest against policies, to embarrass companies or to blackmail companies into paying big ransoms to hackers.

What’s NextBecause of the success hackers had in 2016, we can expect more organizational doxing in the year ahead. Every organization ought to shore up security and to develop a risk management plan should they find themselves doxed. We strongly recommend reading the “Organizational Doxing and Disinformation” blog post by Bruce Schneier: https://www.schneier.com/blog/archives/2016/09/organiza-tional_1.html.

WatchlistSchneier on Security; Anonymous; Russia; China; major news organizations; cor-porations; government agencies


In the coming year, we will continue to create a surplus of data—and we will have too few data scientists to manage it all.

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DataSeventh year on the list

atives, make smart decisions, collaborate on security and surface insights. One obstacle: knowing how to find and hire the right kind of data scientist.

“Data scientist” used to be a job that no one wanted, and in 2017 it will be one of the most sought-after positions. Now, we’re predicting a shortage in Data Scien-tists in 2017 and beyond. There just aren’t enough skilled data scientists to fulfill all the work available—some estimates show a 50% gap between upcoming supply and demand. Industries including pharmaceuticals, finance, insurance, aerospace, foundations, government and travel will see a faster for employees with analytic skills. Some universities, seeing workforce needs changing, will launch new grad-uate programs and centers in data science. Ethics and diversity will hopefully be a mandatory part of those programs, so that our future data scientists are aware of possible algorithmic discrimination and problematic data training sets.

WatchlistGovernments around the world; Universities; Kaggle; IBM’s Watson; Nutonian; Cloudera; Google; EMC; Palantir Technologies; MongoDB and many other com-panies

Key InsightData is a very large trend category with numerous stakeholders, applications and emerging ideas. There’s a lot to monitor in 2017.

ExampleIn the coming year, Big Data will continue to be a buzzword and a trend through-out many industries and fields. From collecting it to parsing it and making it eas-ier to search, we will continue to see lots of developments in 2017. Businesses will want access to analytics tools in order to make important business decisions, while government agencies will rely on data to determine funding for various programs. Consumers have become more aware how much personal data they’re creating—and who has access to it.

What’s NextRegardless of their size and scope, organizations should begin to think about the upcoming uses for large data sets. For example, private practice doctors must begin using electronic medical records for patient care, which presents hurdles (how to migrate from paper record-keeping to cloud-based digital systems) as well as opportunities (the ability to track trends in patient care, not to mention federal compliance). There are frustrations, however. Those collecting data now have a bunch of numbers that answer “what,” but not “why.” They still need some-one to interpret the data and help them find meaning in it.

Large organizations (public, private, foundations, nonprofits, universities, govern-ment agencies) should create a Chief Data Officer position and bring on board a person or a team of people who have the unique skills to champion data initi-


Estonia’s e-residency program has become a popular model for other countries around the world.

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E-residentsFirst year on the list

WatchlistEstonia’s e-residency program

Key InsightE-residency is now being offered in Estonia, making it easier for entrepreneurs to incorporate and run a business free of the usual legal and tax headaches.

ExampleEstonia, which borders Russia to the east, Latvia to the south and sits across the Baltic Sea from Finland, has been operating most of its government services on-line for the past 15 years, from tax filing to contract signing to filling prescriptions and even voting. With a population of just 1.3 million people, Estonia figured out early on how to operationalize digital tools to service its citizens. Recently, Estonia began offering resident status to entrepreneurs—without adding a requirement that they actually take up residence in the country. As part of this beta program, e-residents pay 100 euro and apply online at e-resident.gov.ee, and then need to travel to a local Estonian embassy for an interview. Once approved, e-residents gain access to a number of services—not to mention an EU company and EU bank accounts. This generates revenue for the Estonian government while reduc-ing costs and paperwork for entrepreneurs around the world.

What’s NextWith the Brexit referendum passed, e-residency could provide a smart solution for UK-based entrepreneurs, who will soon find it difficult to work with EU com-panies and hire EU citizens. The program has become so popular that Estonia is now advising other governments, including Lithuania, the Netherlands, Japan and Singapore, on how to create their own e-residency programs. We anticipate more countries starting to launch their own e-residency programs in 2017.


Venmo is a popular peer-to-peer (P2P) payment system.

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Social PaymentsSeventh year on the list

WatchlistFacebook; Snapchat; Line; Uber; WeChat; Kakao Talk; Venmo; Square; Amazon; Ingenico; BOKU; PayPal; Fastacash

Key InsightSocial payment systems offer the ease of seamless transactions, but they’re also budding social networks in their own rights. Meantime, established players have convinced us to share status updates, so why not money?

ExamplesIn 2016, Facebook added payment and merchant services, right within its con-sumer app. Uber started offering more than just rides—its seamless payment gateway now works for food and flower deliveries. Popular peer-to-peer pay-ment service Venmo is now owned by PayPal. Unlike PayPal, Venmo doesn’t charge transaction fees. It allows friends to pay each other or to easily split bills. When you make a payment to a friend, you can tag it with whatever you’d like. Which has made Venmo’s social feed become a popular network itself. Just like a Facebook feed, Venmo shows photos of friends and what they’ve been spending their money on. Venmo is the fastest-growing mobile payment system around.

What’s NextRight now, social payments have primarily been about splitting taxi fares or din-ner bills. Fastacash is a fintech startup that allows peer-to-peer payments via platforms we already use. This kind of backend technology will soon allow Snap-chat, Line, WeChat and others to facilitate easy payments pose a threat to tra-ditional payment processors, who earn revenue through fees. In 2017, we expect to see deeper third-party integrations with P2P APIs to allow us not just to pay each other, but to pay our bills, make charitable donations and potentially shop in virtual marketplaces. That said, social payment networks are probable targets for hackers.


=Some are calling the blockchain the future “Internet of Trust.”

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Bitcoin + Blockchain Fourth year on the list

intermediaries in most transactions, even those outside of finance. In June 2016, the International Monetary Fund called blockchain the future “Internet of Trust,” but also warned that setting standards now is imperative: “It is typical of a new innovation cycle that different companies come up with different ways to do something, leading to a patchwork of technological approaches...this could undo years of effort to integrate the financial industry globally.” We expect 2017 to be a year of acceleration for the blockchain and associated technology.

WatchlistBTC; Kraken; BTCC; ABRA; XAPO; CITI; ING; HSBC; RBS; Bank of America; UBS; Ripple; Peercoin; Coinbase; Coindesk; Boost VC; Greylock Partners; Robocoin; Coinsetter; SecondMarket; Digital Asset Holdings; BTCS

Key InsightBitcoin is a digital currency, and it promises complete anonymity while using a crowd-regulated public ledger system. The blockchain is a public ledger of trans-actions.

ExamplesBitcoins are mined using powerful computers and scripts, but it’s a competitive process. While bitcoin isn’t the only digital currency, and its volatility rules it out as a safe long-term investment, we are now seeing bitcoin being used by more businesses worldwide. In this digital currency system, bitcoin is the protocol par-ticipating on the blockchain public ledger—and it’s that platform that we find more promising. Blockchain is the transaction database that’s shared by every-one participating in bitcoin’s digital system.

What’s NextVirtually everyone agrees that bitcoins probably aren’t the blockchain’s killer app. The blockchain is a sort of distributed consensus system, where no one person controls all the data. Some say that the blockchain will soon herald a new kind of Internet. The cryptography team at Blockstream recently launched its first prototype “sidechain,” which functions as a separate ledger with its own code. Sidechains allow for easier authentication. Blockstream and the sidechain pro-jects that follow will turn the blockchain into a universal platform that can be used for anything requiring signatures or authentication. It will therefore enable people to participate in “trustless” transactions, eliminating the need for an inter-mediary between buyers and sellers. But it potentially eliminates the need for all


Ikea offers a VR marketing experience.

TREND 098



VR Marketing First year on the list

WatchlistReverge VR; BBH; Goodby Silverstein & Partners; VirtualSKY; Leo Burnett; BBDO; Facebook; Droga5; Ogilvy & Mather; Razorfish; Weiden+Kennedy; Circos VR; GS-D&M; VML; Critical Mass; Three One Zero; Valve; Wevr; Alphabet (Google); Leap Motion; Innerspace VR; StartVR; Epic Games; Survios

Key InsightEmerging research suggests that virtual reality storytelling, when it’s done well, rewires all of us—we are likely to develop new belief biases as a result. Marketers will have big new opportunities in 2017 to use VR to influence consumers.

ExamplesFor more than a decade, scientists have been studying “virtual reality expo-sure therapy,” which has been used extensively to treat veterans suffering from post-traumatic stress syndrome. Because VR is completely immersive, it can closely simulate nearly any scenario. Patients, guided by trained therapists, are embedded into VR stories that represent a trauma they’ve experienced. Over time, this therapy results in new neuropathways—beliefs, attitudes and reactions are changed, for better or for worse. This presents an interesting opportunity for marketers.

What’s NextBoth BMW and Volvo have created apps allowing would-be buyers to test drive one of their cars. But unlike the usual test drive with a nagging salesperson trying to convince you to buy the upgraded sport mode package, you instead interact with the vehicle on gorgeous open roads, in the best possible weather, all by yourself. Spend enough time with the apps, and your belief bias will shove your logical mind into the back seat. You might start to think that inside one of those cars, every day is a traffic free holiday where you have the driving skills of Formula One superstar Lewis Hamilton. This, of course, highlights an impend-ing ethical challenge. As VR headsets come to market in 2017, brands will have a unique opportunity to tap directly into our minds, persuading us through im-mersive storytelling.


Do you suffer from FOBO?

TREND 099



FOBOFirst year on the list

Key InsightIf you’re the kind of person who feels uneasy when your phone runs out of bat-tery or when you can’t get a decent WiFi signal, you’re suffering from FOBO, or the “fear of being offline.”

ExamplesProfessional psychological associations around the world, from the U.S. to Aus-tralia, are now encouraging their members to consider FOBO as a source of anx-iety for both young people and adults. While social media addiction is not yet recognized with a diagnostic medical code, emerging research shows that social media—and FOBO—have created new neural pathways causing us to feel varying levels of anxiety when we’re prevented from checking social media. The conten-tious, vitriolic presidential election caused our collective FOBO to spike during the summer, fall and winter of 2016, as we waited to see not just what the candi-dates would do and say next—but how our friends would respond.

What’s NextPsychologists and mental health professionals warn that our FOBO and suscep-tibility to digital distraction isn’t going away anytime soon. This is good news for anyone in marketing—we are a captive audience, growing weaker by the day. In 2017, both marketers and consumers should think about how our current addic-tion will affect our ability to unplug in the longer-term.

WatchlistSocial networking sites; mobile device manufacturers


Walgreens is one retailer now offering a suite of APIs.

TREND 100



Retail APIsFirst year on the list

Key InsightRetailers are making their data available to developers in the form of APIs in order to provide consumers and partners a host of new services.

ExamplesApplication programming interfaces, or APIs, are tools for building software ap-plications. Retailers are using APIs to help customers and partners discover them more easily online, learn about products and services and to interact with the customer even when she’s not shopping. Home furnishings retailer Wayfair has released an API so that developers can build a 3D library—the goal is to help the company’s expansion into virtual and augmented realty. In October 2016, Mas-tercard debuted a developer platform with 25 APIs to make it easier for startups and developers to integrate its payment services. Through its API program, Wal-greens works with more than 275 partners.

What’s NextWe anticipate many more retailers building up their API offerings in 2017. Retail-ers need to expand their reach beyond brick and mortar stores, and also beyond the traditional e-commerce site.

WatchlistCVS; Walgreens; Mastercard; Wayfair; Zendesk; MuelSoft; Walmart; Hershey’s; Amazon; Lowes; Home Depot


The MemoryMirror assist shoppers just as a sales associate would.

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Digital AssociatesFirst year on the list

Key InsightWhether augmented reality mirrors or roaming robot salespeople, a new fleet of digital associates will help consumers shop in 2017.

ExamplesNew smart mirrors are helping shoppers in the fitting room—suggesting which colors match a pair of pants, how to accessorize outfits and even showing alter-nate colors and patterns of an item being tried on. Nordstrom, Top Shop and Nieman Marcus have piloted the technology so far. Meanwhile in Japan, Soft-Bank’s Pepper robot has been taking orders at Pizza Hut.

What’s NextDon’t expect these digital assistants to completely supplant the human sales-force in 2017. That being said, any digital tool that makes the in-person shopping experience easier and more enjoyable for consumers is likely to court investment, not to mention brand loyalists.

WatchlistMasterCard; SoftBank; IBM; Lowes; Keonn; Oak Labs; eBay Enterprise; Memory-Mirror


DronesFifth year on the list

Key Insight You’ve probably seen at least one in the wild. Drones are now available in an array of sizes and form factors, from lightweight planes and coptors to tiny, ma-chines no bigger (or louder) than a hummingbird. Soon, they’ll include powerful sense and avoid technology, and the ability to fly on their own.

102 Sense And Avoid Technology Robots harnessing neural networks and artificial intelligence can make inferences and decisions when programmed to do so. That’s because of sense and avoid technology. In 2017, drones will be programmed to navigate along the path of GPS waypoints—and they’ll make decisions midair about the best path to take and when to avoid objects like buildings, trees and mountains. Or other drones, for that matter.

103 Drone LanesTwo drones inadvertently prevented firefighters from putting out a rapidly spreading California wildfire, which crossed over onto a freeway and destroyed a dozen vehicles. Currently, the FAA does not allow drones to fly near the airspace of airports—but while there are no-fly zones, there aren’t no-fly circumstances. Meantime, news organizations hope to use drones for reporting in the public in-terest, while commercial operators like Amazon want to begin drone deliveries. Law enforcement agencies in North Dakota will begin flying drones armed with anything from tear gas to Tasers, thanks to a new law passed late 2015. From the Valley to DC, everyone will be talking about whether or not the airspace should

be regulated for hobbyists and commercial drone pilots, which will prompt dif-ficult conversations between technologists, researchers, drone manufacturers, businesses and the aviation industry, since each has an economic stake in the future of unmanned vehicles. We anticipate the sky being divided soon: hobbyist pilots will have access to operate UMVs in the 200 and below space, while busi-nesses and commercial pilots will gain exclusive access to 200 - 400 feet zone overhead.

104 Clandestine, Disappearing DronesIn 2016, DARPA funded new research in drones capable of making deliveries—and then disappearing into thin air. The agency’s Vanishing Programmable Resourc-es (VAPR) program has already shown that it’s possible to program a small chip to shatter on command. What’s coming in 2017 is sort of like Snapchat for drones.

105 Autonomous Underwater Vehicles (AUVs)Researchers at MIT have developed underwater drones with cognitive capabil-ities, called AUVs. After giving them a series of parameters—how far to stray, how far above the seafloor to move, what to explore and the like—these drones can function on their own. If something unforeseen happens which impedes the drone’s ability to complete its designated task, it can decide whether to continue or to return to base. AUVs can be used for a host of purposes, from environmen-tal mapping and texting, to military support. Some have suggested that in the future, AUV’s might be used for more nefarious purposes, like transporting illegal goods.

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Drones like these are now available to anyone.



109


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106 MicrodronesMicrodrones will autonomously navigate through tiny spaces to investigate col-lapsed buildings or areas with hazardous materials. In October 2016, the U.S. Army asked for bids to supply short-range microdrones, capable of reconnais-sance and still small enough to fit in a soldier’s uniform pocket. In 2017, these small robots will likely be built and tested for widespread use.

107 Drone DeliveryTowards the end of 2016, commercial drone deliveries launched. U.S.-based Zipline brought its drone delivery system to Rwanda, where it delivered vital blood supplies. UPS, Amazon and DHL all tested their own fleets of drones. Leg-islation will soon catch up with the technology. We anticipate that aviation au-thorities will start to act in 2019-2020, at which point commercial drone delivery will finally take off in earnest.

DARPA’s disappearing delivery vehicles.

Drones cont.

What’s coming next is sort of like Snapchat for drones.

110


The Internet of Things will continue to grow in 2017.

TREND 108



Internet of ThingsFifth year on the list

What’s NextSecurity will be top of mind in 2017. The current IoT system isn’t secure, but we knew that even before the October hack. There will be calls for increased security and regulation in the coming year, when the IoT nears an inflection point—and development starts to outpace our ability to secure it. This opens up opportuni-ties for security experts, however it signals what will likely be increased pressure on IT managers.

WatchlistAlphabet (Google); Amazon; Apple; Honeywell; IFTTT; GE; Intel; Cisco; IBM; Qual-comm; Sony; Samsung; LG; Hadoop; Arduino; SmartThings; AT&T; Verizon; Erics-son; Atmel; Dragon Innovation; littleBits

Key InsightMillions of smart digital devices, from the traffic light outside your home to the phone in your pocket to your HVAC system are talking to each other, monitoring your activity and automating tasks in order to make your life easier. These devices and their protocols make up the Internet of Things (IoT).

ExamplesBy some measures, there will be 25 billion connected devices and machines on-line within the next five years. It’s an incomprehensible number of things: thermo-stats, lights, fitness trackers, cameras, industrial printers, coffee machines, televi-sion sets, robots, cars, traffic lights, parking meters...the list goes on. The explosion is due to a sharply decreased component cost. The prices of sensors, bandwidth and processors has dropped significantly over the past decade, while ubiquitous WiFi and smartphones have opened up a new gateway for the everyday consum-er. In order to connect to the Internet and to each other, each device needs its own unique address. (We started running out of those a long time ago, which is why so many company names and their web addresses tend not to contain vow-els.) Internet Protocol Version 6 (IPv6) is helping to expand the IoT so that there are enough usable addresses to go around. International standards organizations are working on a future open standard, just as HTTP and FTP play critical roles in how we move content around on the web today. But about security? In October 2016, some of the world’s largest websites—Reddit, Twitter, the New York Times—were temporarily down because of an IoT attack targeting DVRs.


Frames from a moving camera recorded by the Swiss Federal Institute of Technology in Zurich, Switzerland, show how UW technology distinguishes among people by giving each person a unique color and number, then tracking them as they walk.

TREND 109



Intelligent Cameras Third year on the list

WatchlistUniversity of Washington; Microsoft; Camera Culture Research Group at the MIT Media Lab; Institute of Anthropomatics & Robotics at the Karlsruhe Institute of Technology; National Instruments; Electronic Frontier Foundation; Austrian Insti-tute of Technology; University of Birmingham

Key InsightCameras themselves are getting smarter. They can now connect with each other on a network for a variety of reasons, from monitoring traffic to creating immer-sive videos.

ExamplesEngineers at the University of Washington have developed a system of net-worked cameras that can automatically track people as they move. Combined with facial and object recognition algorithms and artificial intelligence, smart cameras will provide unprecedented security opportunities. They will be used in our cars, bringing us one big step closer to hybrid-autonomous vehicles, where drivers will choose to take control of the wheel or allow the car to drive itself dur-ing stop-and-go traffic.

What’s NextWe will continue to see this experimental technology taking shape in 2017. In addition to recognizing our faces, similar technology can be used to measure us in infrared—using heat to visualize us in the night. Recognition algorithms will do more than spot people, they’ll be capable of distinguishing between animals, objects and sudden movements, too.


CarsFirst year on the list

Key Insight In 2016, major auto manufacturers played a dangerous game of chicken as each progressively shortened its timeline for the launch of its self-driving car fleet. If press releases are to be believed, you might think that at midnight on January 1, 2020 our cars will suddenly drive themselves. While some of the required technology will be ready by then, we are still a few more years away from what the National Highway Transportation and Safety Administration (NHTSA) calls Level 4 Full Self-Driving Automation. Level 4 vehicles are designed to perform all driving functions and monitor roadway conditions for an entire trip—with the driver providing navigation input but not expected to be available for control at any time during. That’s because there are external events, such as establishing and funding a new federal agency, or working through licensing and regula-tions, that could hold up progress for several years. Other events—the availa-bility of components, public attitudes toward autonomous vehicle accidents, and the like—will also impact momentum. We are in transition—the last years of human driving.

One thing we are certain of: in the U.S., there will eventually be a need for a new federal agency to address autonomous vehicles, something like a Federal Au-tonomous Vehicle Agency (FAVA). It will be charged with working alongside the twelve existing agencies concerned with transportation, from highways to aviation. Meantime, Japan and the EU have been working on a plan to use a common GPS system, which would speed the deployment of self-driving cars in both areas.

110 Open Source Systems Online learning platform Udacity launched an open source self-driving car pro-ject in 2016. Udacity co-founder is Sebastian Thrun, who had previously launched Google’s self-driving car program. The project isn’t about increasing competition in the marketplace, but rather about advancing the skills of our future workforce. While Udacity’s program isn’t accredited, it does promise to teach all of the skills required to work within the burgeoning field of self-driving vehicles. As more people start experimenting with open source systems in 2017, we will need to think through security implications not just for those vehicles, but for others they share the road with.

111 Adaptive Driving SystemsMotorcycle injuries have increased in the past few years, and the reason has to do with age. Nationwide, 39% of motorcycle owners are 51 to 69, according to the Motorcycle Industry Council, and at that age reaction time is slower than op-timal. Yamaha’s Motobot is designed with an aging population in mind: Yamaha has partnered with SRI research institute to create a motorcycle that can drive on its own. The technology being developed will eventually be used to help assist motorcyclists on the road—when they’re not able to act fast enough, the system will take over. Adaptive systems, which help drivers stay in their lanes, prevent them from driving too closely to another car, and parallel park, will be deployed into new vehicles in 2017.

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113

Uber’s fleet of self-driving cars will start to transport us in 2017.


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115 Autonomous Vehicle Legislation2017 will be an important year for state and federal regulation. By October 2016, eight states and the District of Columbia authorized the operation of autono-mous vehicles: Utah, California, Nevada, Florida, Louisiana, Michigan, North Da-kota and Tennessee. We anticipate more states being added to that list in 2017, either through legislation or executive order.

112 Vehicle-to-Vehicle (V2V) CommunicationsCars are able to broadcast their exact positions, speed, acceleration, steering wheel position, momentum, brake status and a host of other information to all of the other vehicles sharing a road within a set distance. Collectively, the cars use this information and analyze it in real-time, to make decisions about how and when to move. Building a V2V network does pose a challenge: it would need to be unfailingly reliable, fast and secure. Some cars equipped with transmitters will be on the road in 2017.

113 Autonomous Testing FacilitiesIn the past 24 months, major car manufactures have opened testing facilities in California, Michigan and Pennsylvania. Outside of the U.S., manufacturers in Sweden, Germany, Japan and China are rushing to set up their own facilities. In 2017, regulators will work to establish a national testing center with a single set of standards and practices.

114 Solar HighwaysResearchers have been working on roads capable of producing their own energy. Think of them as smart, modular systems: LED lights illuminate lines and mark-ings, heating elements keep ice melted, and microprocessors communicate data about whether any section of the road needs repair. Idaho-based Solar Roadways will install its technology in a portion of Route 66 as part of Missouri’s Road to Tomorrow initiative. In Poland, city planners are experimenting with solar-pow-ered, glow-in-the-dark bike lanes. Made from luminophores, which are made of small phosphor crystals, they absorb sunlight during the day and illuminates a brilliant blue at night.

Yamaha’s Motoman and humaniod driver.

Cars cont.

114

We are in transition—the last years of human driving.

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116 Flying CarsIn 2016, Bloomberg Businessweek reported on Google co-founder Larry Page’s secret flying car factories, breathing new hope into a very old tech myth. Fly-ing cars have been a persistent, trendy theme within popular culture on and off for more than a hundred years. Waldo Waterman’s Arrowbile was the first to leave the street for the sky in 1937. Three years later, Henry Ford remarked confidently, “Mark my word: a combination airplane and motorcar is coming.” Aviation publicist Harry Bruno clarified, saying that cars of the future would look like tiny “copters”; when school let out, they would “fill the sky as the bicycles of our youth filled the prewar roads.” In 1949 Life magazine featured the Air-phibian, an aerocar that could fly from a backyard airstrip to LaGuardia Airport and then transform into a convertible-like vehicle capable of driving to Times Square. The dream of flying cars continued into the twenty-first century and up to the present day as people built new prototypes with vertical take-off and landing capabilities, super-strong carbon fiber bodies, ducted fan propulsion, and cheaper flight-stabilizing computer systems.

117 Drink DrivingOnce we are ensconced in our fully self-driving cars, and we are no longer re-quired to manage any driving operations, we’ll be free to work, play games.....and drink? That may seem audacious, but cars could come equipped with “booze cruise control,” allowing the driver to both drink and be driven. Alcohol manufac-turers, bars, restaurants and clubs could all benefit from drink driving, as could our tax collectors.

Trend or Trendy?We’ll leave these two for you to decide.



In WarGames, Matthew Broderick played a hacker who brought the U.S. and former Soviet Union to the brink of nuclear war.

TREND 118



Old Laws Clash With New TechnologySecond year on the list

What’s NextIn a democracy, new policies and laws require discussion, debate and various parts of a government to collaborate. It’s a slow process by design. Both the Trump Administration and our newly-elected officials will need to reconcile pro-cess with progress in 2017 and beyond, as they evaluate existing policies and determine how technology should be regulated. Without meaningful discussion about the long-range implications of legislation, lawmakers could cause drastic (if untended) consequences for their constituents in the decades to come.

WatchlistGovernment agencies; business leaders; legal scholars; law enforcement; technol-ogy and privacy advocates; media organizations; everyday citizens

Key InsightTechnology is now moving faster than government’s ability to legislate it. As a result, countries around the world are learning the hard way what happens when old laws clash with new technology.

ExamplesIn the U.S., the Computer Fraud and Abuse Act (CFAA) was enacted shortly af-ter lawmakers showed a clip of the 1984 movie WarGames during testimony—it was an iconic scene about the brink of nuclear war with Matthew Broderick, as a teenage hacker. The CFAA’s broad language makes it illegal to break a website’s terms of service (TOS). But these days, most of us break the TOS of the services we use without even realizing it. Every time that coworker Facebooks an inspi-rational message she found online, she’s technically breaking the law. The CFAA was used to threaten the late internet activist Aaron Swartz with 35 years in prison for allegedly stealing a trove of academic papers with the intent of making them available freely to the public. Meanwhile, there are a host of technologies for which we have questions but no answers—can law enforcement use the Fourth Amendment to compel a company to jailbreak a device? Does the Fifth Amend-ment mean that sources of personal data, such as fitness trackers, can’t be used to self-incriminate someone in court? Does the Thirteenth Amendment extend to sentient, artificially intelligent agents?


A #catsofjihad post.

TREND 119



Digital CaliphateFirst year on the list

What’s NextThe rise of a digital caliphate poses an existential challenge for the world’s most important technology companies, all of whom operate out of countries with democratic laws. To thwart the rise of a digital caliphate would necessarily involve censoring content. The Trump Administration and our newly-elected officials will face a serious challenge in 2017, and will need to prioritize their strategic digital thinking to deal with this emerging threat. On the other hand, democratic nations could work together—there is a way to kill an idea, and that’s by spreading one that’s more compelling.

WatchlistGovernment agencies; technology leaders; media organizations; ISIS; legal schol-ars; law enforcement; technology and privacy advocates

Key InsightA “caliphate” is a physical Islamic state led by a caliph, a political and religious leader who is deemed the successor to the Islamic prophet Muhammad. In June 2014, the Islamic State of Iraq and Syria announced the formation of a geograph-ic caliphate, with Abu Bakr al Baghdadi—the head of ISIS—as its caliph. However, much of ISIS’s most significant work happens in the digital realm. More concern-ing than the extension of physical borders held by ISIS is the digital spread of its ideas—borders are easy to break. A digital caliphate is hard to stop.

ExamplesISIS has risen to prominence because the organization commands social me-dia unlike any other. The Islamic State has developed a magnificently powerful brand—with recognizable characters, plot lines and all the trappings of effective propaganda. It has also routinely fooled social media platforms into allowing its content to resurface, again and again. ISIS understands how to start and stoke a viral campaign—just look up the #catsofjihad hashtag. And its media operations are decentralized—making it difficult to turn off the fire hose. On average, ISIS releases three dozen new pieces of content every day—videos, photos, text posts, tweets, audio clips—in lots of different languages, making it more prolific than many news organizations.


Tashfeen Malik and Syed Farook killed 14 people and seriously injured 22 in a terrorist attack in San Bernardino, California.

TREND 120



Asking Tech Companies To Help Fight TerrorismFirst year on the list

Key InsightThe strength of terrorism groups has much to do with their mastery of digital tools and social media. Now, government agencies are asking for their help in fighting back.

ExamplesIn 2016, the White House met with the leaders of large technologies asking them to help “disrupt” ISIS’s online presence and activities. Some of the ideas being discussed both within the U.S. and other governments include loosening encryp-tion, and filtering and censoring content, and making it easier for law enforce-ment to gain access to the devices and accounts of accused terrorists.

What’s NextTechnology companies will find themselves in many more conversations about the spread of terrorism via their tools and networks. In 2017, they will likely be asked to have new conversations with the Trump Administration. But the ques-tions—and answers—are complicated. Better to think through policy and proce-dure in advance, so that decisions don’t have to be made under duress.

WatchlistGovernment agencies; technology company leaders; legal scholars; law enforce-ment; technology and privacy advocates; media organizations; everyday citizens


TREND 121



Internet Mob JusticeSecond year on the list

What’s NextInternet mob justice doesn’t follow a set playbook—there are no rules to be bro-ken, and there is no system for determining culpability. The prevailing notion, that the crowd is always right in its judgement, shouldn’t mean that the crowd is jus-tified in its reaction. The internet was architected to be abstract and open, with few rules governing our behaviors. But this means that we are all, potentially, in danger. In 2017, we will no doubt see new cases of mob justice, which will lead to fresh calls for regulation, and which could ultimately lead to the social construct of the Internet being completely undone.

WatchlistThe FCC; the ACLU; the EFF; law enforcement; Facebook; Twitter; Snapchat; You-Tube

Key InsightInternet mobs are threatening real-world citizens with harassment, violence and death.

ExamplesIn 2015, it was Cecil the lion. In 2016, when a four-year-old boy crawled into a gorilla enclosure at the Cincinnati Zoo, officials killed a gorilla named Harambe to protect the child. In a torrent of social media posts, some argued that Harambe was trying to protect the child, rather than harm him. A petition with thousands of signatures demanded that the boy’s parents be held accountable for the death of Harambe, and called for an investigation into the safety of the child’s home, citing parental negligence. But perhaps the most obvious example of internet mob justice was the 2016 U.S. political zoo—vitriol was spread everywhere, as supporters from both sides of the aisle went on attack. Fox Business Network’s Lou Dobbs tweeted the home address and phone number of a woman accusing Donald Trump of sexual assault. In June 2016, the internet mob spilled over into the real world when Trump’s supporters were chased down the street by demo-crats after a Hillary Clinton rally in San Jose. Increasingly, activism is turning into digital vigilantism. The legal system is being sidestepped entirely—while the tools enabling Internet shaming grow ever more ubiquitous and easy to use.

Cincinnati Zoo officials killed a gorilla named Harambe to protect a child in 2017.


A worker loads an 8-inch floppy disk into her terminal.

TREND 122



Overhauling Government Tech InfrastructureFirst year on the list

WatchlistFederal Chief Information Officer; Office of Science and Technology Policy; Gov-ernment Accountability Office; Department of Defense; IRS; State Department; Department of Transportation; Department of Justice; Department of Health and Human Services; the FCC; Department of Housing and Urban Development; De-partment of Energy; Department of Homeland Security; Environmental Protec-tion Agency; Office of Management and Budget; elected officials and lawmakers

Key InsightParts of the federal government rely on comically old technology, which is very difficult to maintain.

ExamplesIn 2016, the Government Accountability Office (GAO) published the findings of its technology audit: the Department of Defense is using a 53-year-old system and 8-inch floppy disks as part of its nuclear program. The State Department uses a 26-year-old system to track visa information for 55,000 foreign nationals—software that was decommissioned by the vendor who built it. Old software, ma-chines and systems are expensive to maintain. Plus there aren’t many technicians who have enough institutional knowledge to make necessary fixes, which means re-hiring retired employees at high contract wages.

What’s NextThe problem isn’t just about legacy systems. The Trump Administration and our newly-appointed government officials will need to prioritize tech infrastructure in upcoming budget planning and funding proposals in order to keep pace with the changing nature of technology. Government IT professionals will need to spend additional time and money shoring up existing systems as they continually review new tools, like Slack, smart TVs and wearable devices, all of which could become sources of vulnerabilities.

© 2017 Future Today Institute121 © 2017 Future Today Institute

Established by Article II, Section 2 of the U.S. Constitution, the Cabinet is tasked with advising the President on a number of subjects, from transportation to defense. The Cabinet includes the Vice President, the Attorney General, and the leaders of our 15 executive departments—the Secretaries of Agriculture, Commerce, Defense, Education, Energy, Health and Human Services, Home-land Security, Housing and Urban Development, Interior, Labor, State, Trans-portation, Treasury, and Veterans Affairs.

As artificial intelligence, robotics and genomics move away from the fringe and to the mainstream, some of our cabinet members will play a bigger role in advising our newly-elected President and the people chosen to lead each department. Here’s who will matter most—at least when it comes to technol-ogy—in 2017.

Secretary of StateFrom digital diplomacy, to multinational standards on genomics, to bots and beyond, the Secretary of State will need to have a firm grasp on the frontiers of emerging technologies. This position will require technical savvy and the ability to draw upon well-informed outside experts who aren’t motivated by politics.

Secretary of DefenseThe near-future of warfare will require collaboration between the hacking community, roboticists, those at the FCC managing the spectrum, AI re-searchers and data managers.

Secretary of AgricultureSome of the most promising new technology involves edited seeds, which will not only impact U.S. farmers and big agricultural companies, but those abroad as well. In the next few years, governments will need to develop norms and protocols for how this technology is used.

Secretary of Health and Human ServicesSoon, AI will start to disrupt our workforce, and during that transition, many people will find themselves out of a job. This will require HHS to retool its public assistance programs—as well as to develop a strategy for how to lev-erage the highly-skilled workers who are too young to retire.

Cabinet Positions That Will Matter The Most In 2017

Secretary for TransportationThe next four years will be pivotal for the auto manufacturing industry and for autonomous vehicles. Collaboration between industry and government will be essential as this technology moves from the fringe towards the mainstream.

Secretary of EnergyAmerica is now the largest exporter of energy, and has caused economic insta-bility of other countries around the world. Climate change is upon us. The DoE will have to spend the next several years negotiating energy consumption and pollution with other countries.

Secretary of EducationThere are a number of new challenges facing schools, from a growing digital divide, to adaptive learning. How to manage standardized testing, and how to set national standards, will be influenced by technology in the years ahead.

PROPOSAL: WE NEED A DEPARTMENT OF THE FUTURE

Years ago, the now-shuttered Office of Technology Assessment was charged with researching, forecasting and advising Congress on matters of emerging technology. During its existence, the OTA released more than 750 prescient studies ranging from robots in the workplace, to bioterrorism, to acid rain and climate change. We are building and deploying new technologies at an unprecedented rate. For the first time in our country’s history, advancements in science and technology have outpaced our lawmakers’ ability to respond in a measured, responsible way.

During the 2016 election cycle, candidates talked only about technology as it relates to jobs, the economy and better access to government services. That addresses our current problems, not our future ones. It is time for a Depart-ment of the Future and a Secretary of the Future, who would advise the next President on the social, economic and geopolitical implications of emerg-ing science and technology—as those implications relate to all other depart-ments, agencies and offices within the government. Such an office would co-ordinate research, lead scenario mapping and long-range planning.


Minneapolis City Hall will continue to build its local cybersecurity operations in 2017.

TREND 123



City-Level Cyber SecurityFirst year on the list

legesKey InsightWith more local government services moving online, cities and towns will need to hire qualified cybersecurity managers.

ExamplesCities with high-profile residents like Minneapolis (home to many Fortune 500 companies, including Target), New York City (home to celebrities and financi-ers), Arlington (the Pentagon) have been actively seeing cybersecurity experts to fill new positions. We expect this trend to continue, especially as civil tensions increase. This represents a fundamental change in our behavior, with cities and city infrastructure likely targets in 2017.

What’s NextThere is a significant talent shortage—those who have the right skills set and ex-perience tend to take much higher-paying jobs in the private sector. As a result, cities will need to carve out enough budget to pay for staff. And they’ll need to do it quickly: cybercrime won’t wait for local city and town budgets to pass.

WatchlistLocal city and town agencies; local business leaders; local universities and col-


Melbourne, Australia is investing in a host of smart cities technologies.

TREND 124



Smart City SystemsFirst year on the list

WatchlistDepartment of Transportation; White House OSTP; IBM; cities worldwide

Key InsightCities are being urged to rethink how they use technology in order to bring more services to citizens, save money, and make daily life a little more pleasant.

ExamplesIn 2016, 78 cities applied for the Department of Transportation’s “Smart City” challenge, which would award them $40 million in federal grant money to up-grade their urban transit systems. DoT selected Columbus, Ohio, as the winner for its proposal to deploy self-driving electric shuttles, launch smart cards to provide free car-sharing services, and develop a connected traffic light system to reduce traffic jams throughout the city. The City of Melbourne (Australia) has launched a Smart City Office, which includes open data projects, a 24-hour pedestrian counting system and city-wide free public WiFi. IBM’s Smarter City Challenge is providing select cities access to Watson APIs and pro bono consulting services.

What’s NextSmart Cities are attractive to businesses, startup communities and young people looking for a permanent place to call home. We anticipate more competitions and grants to be made available in the years to come—as well as new public-pri-vate partnerships.

Genomic EditingSecond year on the list

What You Need To Know About Genomic EditingBiology is one of the most important technology platforms of the 21st century. Genomic editing is a quickly-developing, game-changing field promising to in-fluence the future of life on our planet. Mapping the human genome has been a long and difficult process. Recently, sequencing technology has become more accessible and affordable to research labs, which would enable them to work to-wards personalized medical treatments for vexing diseases like cancer. Six years ago researchers unveiled a gene editing technique called CRISPR-Cas9, which allows scientists to edit precise positions on DNA using a bacterial enzyme. New technologies make CRISPR gene editing more affordable. The implications are tremendous. Mosquitoes carrying malaria could be edited so that they no longer carry the disease through future generations, and so that millions of humans in high-risk regions no longer suffer from the disease. There are therapeutic possi-bilities in human medicine as well. Editing our genetic code could mean eradicat-ing certain genetic diseases—like cystic fibrosis—so they can’t be passed along to babies. Liver cells could be edited so that they lower the bad cholesterol levels in families that have inherited mutations.

We will see a number of companies further develop biological technologies. However, this is another example of an emerging technology that’s developing faster than our ability to have meaningful conversations for the future, which is why there are so many incendiary op-eds and headlines. This technology does warrant meaningful planning. We probably shouldn’t be working toward a day when a baby’s eye color or athletic ability can be edited into her embryonic DNA. However these treatments and cures deserve a deeper, more informed discussion about our future, as they could alter life for millions of people around the world. 2017 should prove to be a pivotal year, as U.S. government funding for genomic editing projects could be reconsidered by newly-appointed government officials.

Language MattersGene-edited vs. GMO: gene-edited means that an organism’s native genome has been edited, while “genetically modified organism” (GMO) means that for-eign DNA sequences have been introduced into an organism.

Gene drive: this is the practice of pushing the inheritance of desired genes through generations in order to permanently alter the entire population of an organism


This is a new approach to personalized treatment and prevention, allowing doc-tors to design a treatment strategy using our own genes as guides. In the future, there would no longer be a single medication for all, but rather an individualized treatment for each one of us individually. Backed by the National Institutes of Health and $130 million in federal grants, precision medicine is being rigorously studied by universities, health and pharmaceutical researchers, the insurance industry and government.

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The CRISPR editing process.



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stick on to your head—and a mobile app syncing you to your smartphone. It delivers low-grade electric pulses to influence either your sympathetic (fight or flight) or your parasympathetic (rest and digest) nervous system. Rather than waiting to get home and unwind with a glass of wine after work, you could instead program your headband to kick on during your commute home and arrive pre-relaxed.


Synthetic biology is a emerging field that builds new life: replacement organs and soft tissue, as well as entirely new kinds of organisms never before seen on Earth. Synthetic biologists at Ginkgo Bioworks unveiled a bio factory in the fall of 2016, and it will be creating new lifeforms in the coming year. So far, it has created brewer’s yeast with genes from an orange tree—but it’s planning on creating new kinds of pesticides and laundry detergent, too. The University of British Columbia-Okanagan is developing realistic human hearts that can be used for surgical trainees. Meanwhile, researchers from around the world are hoping to build a functional human genome from base pairs by the year 2026.

130 Running Out Of Space For Genome Storage

By 2025, researchers at the University of Illinois at Urbana-Champaign esti-mate that we may be out of data storage space for human genomes. As preci-sion medicine, CRISPR and gene therapy technologies continue to advance and improve, our storage needs will explode along with the computing power and requirements for acquiring, distributing, analyzing, encrypting and safeguarding our genomics data.


In 2017, researchers will be working on building programmable devices out of our DNA, RNA and proteins. These molecular programs would allow doctors to “talk” to our cells in order to diagnose complex diseases, or to test new thera-peutic treatments. A team at Harvard University’s Wyss Institute is researching this fantastical-sounding technology for its practical uses, like curing cancer.


Tiny robots capable of delivering medicine to only a specific area of the body, or assisting with micro-surgery, are on the horizon. Researchers at the Univer-sity of California San Diego proved in 2015 that a nanobot, propelled by gas bubbles, successfully delivered medicine inside of a live mouse without causing injury. This technology will eventually make its way into us, too, as research con-tinues in 2017.

128 Neuroenhancers

In the coming year, a number of computer devices meant to augment our bi-ology will be made available to the public. Some promise to help you become more productive, while others are meant to boost your mood. The Emotiv Epoc+ and Emotiv Insight and mobile EEG devices monitor your brain activity and analyzes cognitive performance. Doppel, which is worn on the wrist, uses electric pulses to augment your energy. The pulsations, which you dial in based on your needs, are supposed to have a similar effect on your brain as music does. The Thync Kit is a series of electrodes and a triangular device that you

Genomic Editing cont.

Nanobots will deliver targeted therapies to patients.

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131 Norms and RegulationsIn 2016, we learned that Chinese scientists were already testing CRISPR-Cas9 on humans. Sichuan University began testing modified cells on people with lung cancer. In Guangzhou, researchers from Sun Yat-sen University published the results of their tests on human embryos. All of these stories raised concerns for ethicists and biologists in other countries. Meanwhile, the shift in the White House and Senate comes at a critical time. In 2017 and beyond, there will be a call for global norms—but developing a global agreement detailing how we should ex-periment with and use emerging biological technologies will be a complicated process.

The Ginkgo Bioworks automated biology factory.

Genomic Editing cont.

Biology is one of the most important technology platforms of the 21st century.

126


This Lexus concept car uses a driver’s biometric data to glow every time the driver’s heart beats.

TREND 132



BiointerfacesFourth year on the list

WatchlistDesign Lab; Lexus; Carnegie Mellon; Microsoft; University of Michigan; Uni-versity of Pennsylvania’s Nano/Bio Interface Center; the Center for BioInterface Research at Georgia Tech

Key InsightPressure-sensitive fabrics, optical sensors and bio-acoustic sensing arrays are transforming your hands, arms and legs into control pads.

ExamplesResearchers at the Design Lab in Berlin have developed a glove that has embed-ded pressure sensors, which could soon give the gift of limitless communication to deaf-blind people, who currently rely on a system of tactile (hand-to-hand) sign language. Software translates the sign language alphabet into digital text and is connected to the Internet—meaning that anyone will be able to commu-nicate freely with people who are deaf-blind. Meantime, sales of smart TVs with gesture control have increased year over year. Some auto manufacturers, such as BMW, have introduced gesture controls into their flagship models.

What’s NextBiointerface and gestural interfaces aren’t intended to compete with touchscreen environments, but are instead meant to help us communicate and operate our devices in new ways. The next iteration of gestures is to combine them with more sophisticated technologies. We expect to see more wearable interfaces—with smartphone touchscreens as remote controls—in the coming year. We’ll also see new interfaces in cars, which will allow drivers to use gesture to control the dash-board and will use in-seat sensors to determine whether a driver is falling asleep. Lexus recently released a concept car video showing how cars might recognize and react to our emotions. For many designers, the next evolution in tangible interfaces remains the ability to make traditional interfaces disappear entirely, instead allowing us to make small gestures and use our voices to control the ma-chines in our lives.

WearablesFifth year on the list

Key InsightAs of December 2016, the Future Today Institute is tracking 462 wearable devic-es, in various stages of development—from fringe experimentation to mass-mar-ket sales. More than half are dedicated to fitness or biometrics, while others are intended for gaming, work and medical monitoring.

As of now, nearly all wearables require a smartphone or computer to see and report data, adjust settings and archive information. Those coming to market in 2017 will continue to service our fitness and lifestyle needs with our mobile phones as a hub. Still, there are several trends to consider in this space:


Virtual reality headsets are wearable devices. What’s next: they will soon collect your biometric data and other personal information in order to provide added functionality. The HTC Vive tracks your movement, while controller sticks send haptic signals to your brain as you work your way through simulated environ-ments.

134 Smartwatches

There are a variety of smartwatches and smart wristbands that act as second screens for your mobile phone. With the debut of the Apple Watch, advertisers, marketers, journalists and everyone else who’s even tangentially connected to the content business was motivated in 2016 to capture wrist real estate, building apps and products that combine location, news or deals with notifications. The future of smart watches is certainly promising, however we don’t think that they

will be ready for meaningful content delivery in 2017. Instead, look for more ro-bust lifestyle, fitness and entertainment applications.


Wireless Body Area Networks (WBANs) communicate information from your wearable devices back to medical servers, app manufacturers and your home computer. Sensors, such as devices to monitor your heart rate or oxygen level, collect data and send it back to a central hub (most often, your smartphone) which then relays the information to a medical team or health care monitoring service. There are a lot of benefits: rather than moving into an assisted living facility or spending a lot of time in the hospital, patients can instead move back home while being provided with virtual care. While some of the established medical devices use strong encryption algorithms, many new wearable devices don’t. They’re sending a lot of unencrypted, unsecured personal data – including our locations – across the Internet. The U.S. Department of Homeland Security has been investigating several cybersecurity cases related to WBANs, and we anticipate WBAN security growing as a trend in the coming year.


A new breed of weavables—textiles woven with sensors and other technolo-gies—will provide haptic feedback to help us navigate cities as we walk. They will also automatically adjust to cold or heat, keeping our body temperatures consistently comfortable. IBM Watson partnered with Marchesa on a high-tech, connected dress worn by model Karolina Kurkova at the annual Met Gala.

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IBM Watson and Marchesa co-designed a connected dress for the 2016 Met Gala.



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Navigate Paris is a location-enabled jacket, which helps the wearer get around Paris without burying her nose in her smartphone. CuteCircuit makes dresses that can change colors via smartphone. Biofabricate is growing fabrics in a lab. Near-future projects in the works include drug-releasing medical textiles and fabrics that regulate moisture in our skin.

137 Women

There are still relatively few wearables specifically designed with women in mind. In 2016 we saw some partnerships between popular designers and wear-able tech companies, and we expect to see more soon. But for women, it isn’t just about design. Wearables that help track women’s health issues and person-al safety stand to grab significant market share in the coming year.

138 Kids

We will see more wearables designed for kids in 2017, as developers are creating wearables for parents who want to monitor their infants and young children. Several smartwatches, such as the HereO and Kidswatcher allow parents to track their children’s coordinates, send them messages and make calls to the device. The iBitz is a pedometer that incentivizes kids by rewarding them with virtual coins to use in Disney’s Club Penguin. Sproutling collects real-time data on infants, reporting their body temperature, heart rate, body movements, and sleep patterns as well as room temperature, humidity, and light.

Google’s Project Jacquard attaches conductive yarn to circuits and connectors.

Wearables cont.

139 Pets

Is your dog lazy? That’s a question on the minds of some entrepreneurs who are designing wearables for pets. The WonderWoof is a bluetooth-enabled bowtie that tracks your dog’s steps and sends the information to your smartphone. FitBark Tracker monitors a dog’s activities and provides analytics on play and sleep. Trackimo and Verve Retrieve are real-time GPS trackers for pets, and they work both indoors and outside. Expect more features in 2017, like the abil-ity to schedule a geofence that will send you alerts when your pets wander too far away.



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143 Thinkables

Thinkables will soon allow more adventurous gamers to control games using only their thoughts. The 4D Force platform detects brain waves, capturing EEG/ EOG/ EMG signals and converting them into signals a computer can un-derstand. RENDS 133 - 143

Here Come The –ablesIn the coming year, expect to see a number of wearables, which promise to keep you alert, healthy and balanced.

140 Tattooables

Medicine will start to look very different. Tatooables are going to clinical trials soon. Researchers at the University of Tokyo, Stanford and the University of California at San Diego are all working on electronic second skins. MC10 has al-ready created microscopic, organic semiconductors and carbon nanotubes that stretch and flex and can be powered wirelessly.

141 Ingestibles/Implantables

In the coming year, we’ll see several new ingestible and implantable nanobots and other wireless medical devices that deliver drug therapy, monitor our vital statistics, stimulate our brains, help manage pain and bladder control and more.

142 Earables

In-ear computers, otherwise known as earables, will be here soon. For example, Apple recently filed a patent on earbuds that can be used to monitor tempera-ture, perspiration and heart rate during exercise or sports—those earbuds could also be used to control electronic devices (like our phones) using head gestures. The current AirPods don’t offer that much functionality, of course, but we antici-pate some of these bio-features being added in the next 24-36 months.

Ingestible origami robots developed at MIT’s Computer Science and Artificial Intelligence Laboratory can unfold itself from a swallowed capsule and then crawl across the stomach wall to patch a wound.Wearables cont.

130


Smart Thread can be used in sutures to heal—and report on—wounds.

TREND 144



Smart ThreadFirst year on the list

Key InsightIn 2017, you’ll be hearing more about “smart thread,” which doctors can use to monitor patients after surgery.

ExamplesResearchers at Tufts University have embedded nano-scale sensors and elec-tronics into surgical thread, that can be used for suturing. Think of it as a sort of temporary, smart system that connects to a smartphone or other medical device and reports on your glucose levels, diagnoses an infection and alerts hospital staff if your body is chemically out of balance.

What’s NextSmart thread is just coming out of experimentation, but initial tests results show that it can be successfully used as a diagnostic device.

WatchlistTufts University; Harvard-MIT Division of Health Sciences and Technology; Har-vard University’s Wyss Institute


Alphabet’s Verily Life Sciences is helping to bring a new branch of health science to the mainstream.

TREND 145



BioelectronicsFirst year on the list

Key InsightBioelectronics is a new scientific field in which tiny implantable devices are used to treat a variety of ailments.

ExamplesAlphabet’s Verily Life Sciences is partnering with a number of companies, from GlaxoSmithKline (GSK) to 3M, to propel bioelectronics forward. IBM Research is building micro-machined structures that mimic human cells in saliva, blood and urine. Already, Verily and UCLA developed a wearable microscope that can be used to detect certain kinds of cancers.

What’s NextJust as complex computer networks can be analyzed and fixed by isolating spe-cific nodes—bioelectrical engineers believe that the human body can be similarly addressed to stimulate our immune system, slow the progression of disease and extend human longevity.

WatchlistAlphabet (Google); Verily Life Sciences; IBM; GSK; 3M; AstraZeneca; University of California Los Angeles; Novartis.


The doctor will see you—and your smartphone—now.

TREND 146



Patient-Generated Health DataFirst year on the list

WatchlistValidic; HumanAPI; Vivify; Strava; Qualcomm; Tactio; Alphabet; insurance compa-nies; Medicare; Medicaid

Key InsightPatients are creating a trove of data that could contribute to their healthcare pro-vider’s overall assessment. The doctor will see you—and your smartphone—now.

ExamplesBecause of the Affordable Care Act (ACA), Americans have been creating a trove of patient-generated health data that can be used by researchers. The ACA requires that doctors and health care providers collect a tremendous amount of patient data, beyond height, weight, blood pressure and temperature. If patients contributed all of the other data being collected by their devices—such as their average daily activity, daily resting pulse rate, number of hours slept, and the like—health care providers could treat us more holistically. New software from companies like Validic allow doctors to collect this other data and incorporate it into their medical records—as long as patients give their consent.

What’s NextAs of December 2016, when the Trend Report was first published, the fate of the ACA was in question. To comply with the ACA, the health care industry spent billions of dollars to overhaul the electronic medical records systems it uses. If the ACA is overturned or significantly altered, that could mean big changes to the way that health care providers are required to collect, maintain and distribute your personal health data.

If health care providers continue to collect the same amount of patient data (or more) as they are required to do today, that would provide artificially intelligent and cognitive computing systems the data needed to assist doctors with pre-ventative care and healthy lifestyle plans.


In the near-future, prosthetics will both move and communicate the sensation of touch.

TREND 147



Touch-Sensitive ProstheticsFirst year on the list

Key InsightResearchers are developing new prosthetic limbs that restore not just move-ment—but touch as well.

ExamplesNeuroscientists at the University of Chicago are experimenting with touch-sen-sitive robotics and rhesus monkeys, whose neural-sensory biology is most similar to humans. They successfully simulated the sensation of touch by stimulating certain areas of the brain.

What’s NextThis research lays the groundwork for human testing—in the near-future, similar technology will be incorporated into prosthetic arms that will transmit the basic sensation of touch back to the brain.

WatchlistNational Academy of Science; FDA; University of Chicago; Duke University’s Center for Neuroengineering; University of Southern California; University of Washington’s Center for Sensorimotor Neural Engineering; Johns Hopkins Uni-versity; Carnegie Mellon University; Starlab; Case Western Reserve University; Penn State University; DARPA


Microsoft researchers are studying image recognition via deep learning techniques.

TREND 148



Deep Learning For Food RecognitionFirst year on the list

Key InsightDeep learning is being used to help identify food for a number of reasons: to help computers have more robust conversations with us about what we’re eating, to calculate the number of calories in a dish, and to spot spoiled or tainted food.

ExamplesHow many calories are in that salad? Rather than estimating and doing the math yourself, new computer models will be able to calculate the nutritional value of your meal before you take your first bite. Deep learning—a branch of artificial in-telligence—is an approach to building and training a neural network to think more like we humans do. Researchers at the University of Massachusetts are using deep learning for computer-assisted dietary assessments, while scientists at Mi-crosoft have already incorporated their deep learning prototypes for recognizing popular Asian and Western foods into Bing local search.

What’s NextThis technique can be used to find and sort bad products on food assembly lines, and it can help growers better identify crop disease. In 2017, research into deep learning for food recognition will mean a number of opportunities for agricultural companies, farmers, food manufacturers, restaurants and those watching their diets.

WatchlistMicrosoft; Prospera; IBM; Alphabet (Google); University of Massachusetts; Apple; Carnegie Mellon; University of Tokyo; Penn State University; University of Mary-land; PlantVillage


Smart Farm technologies could bring dramatic changes to agricultural business in 2017.

TREND 149



Smart FarmsFirst year on the list

Key InsightIn order for traditional agriculture to meet the global demand for food, research-ers are trying to make farming look more like modern manufacturing.

ExamplesThe UN’s Food and Agriculture Organization published an alarming report in 2009 stating that by the year 2050, global agricultural production must rise by 70% to meet projected demand. Current farms won’t meet the mark without getting a little smarter.

What’s NextA number of new and emerging technologies can be used to power farms with data and to automate labor. For example, moisture sensors can continuously monitor the moisture level of soil and communicate with an irrigation system to increase the water supply. Editing the genomes of seeds can allow them to flourish, even in unpredictable weather conditions—which are becoming more frequent. It can also match seeds to specific soil types, to generate an optimal crop of vegetables. Advancements in agricultural drones will, in the near-future, assist with planting, harvesting and pest control.

WatchlistUN Food and Agriculture Organization; USDA; Tyson Foods; Alico Incorporated; Agria Corporation; Adler Seeds; American Vanguard; Monsanto; Dow Chemical Company; University of Maryland; Purdue University; Iowa Farm Bureau; OpenAg Initiative at MIT; DNV GL; Cargill; Alltech; Bernard Matthews Farms; BASF; AVEBE; Archer Daniels Midland; Marrone Bio Innovations; Syngenta; Honeywell; DuPont


NASA’s image of Mars.

TREND 150



TerraformingFirst year on the list

Key InsightTerraforming is a concept from science fiction—people reform another planet to make it resemble Earth, so that it can support human life.

ExamplesSci-fi, meet reality. Some people believe that human life is unsustainable in the far-future, and that humans will need to colonize another planet in order to sur-vive. In September 2016, Elon Musk, CEO of SpaceX, delivered his plan to both get us to Mars and to terraform it once we arrive. It will be several years before humans pack up and move to space—but NASA has already moved ahead on several projects to study terraforming the Moon.

What’s NextThe keys to terraforming could be in our current microbes, which are capable of surviving harsh environments like the Atacama Desert. Of course, we might in-vent entirely new forms of life using synthetic biology (see Trend 128).

In order to advance terraforming from theory to reality, we’ll need a host of new robots capable of being trained to mine for resources and build an ecosystem that can sustain human life. And we’ll need powerful rockets that can power spacecraft to transport those robots to space so that they can break ground.

WatchlistNASA; SpaceX


This hamburger was grown in a lab.

TREND 151



Cultivated Food and BeverageFirst year on the list

Key InsightSay goodbye to tofu imitations of traditional meats. Scientists are getting closer to culturing meats and grapes that are made up of the same chemical structures, but were fabricated inside of a lab rather than grown on a farm.

ExamplesIn 2013, the University of Maastricht introduced the world to the first lab-grown hamburger patty, and it cost $330,000 to create. Since then, a number of start-ups have been working on various techniques to culture—rather than harvest—meat that has the same chemical structure as what would have otherwise come from an animal. Meanwhile, Ava Winery has figured out how to create wine that tastes just as good as Dom Perignon Champagne—without any grapes. Propo-nents also like cultured meats because they could help ease the environmental footprint of livestock production.

What’s NextRight now, labs are culturing the two critical elements of meat separately—the fat and the muscle tissue. And they’re currently being produced with some animal products. In the future, researchers are working on eliminating animals entire-ly from the process and instead manufacturing an organic material with both muscle and fat together. It will be 10-15 years before producers are able to scale production to meet our demand, but by that time we might be printing our own hamburgers at home.

WatchlistFuture Meat; Ava Winery; University of Maastricht; EU; FDA


Are we in a new epoch called the Anthropocene?

TREND 152



Anthropocene and ClimateThird year on the list

In 2016 alone, researchers and academics published thousands of peer-reviewed papers, op-ed pieces and books. Traditionalists argue against using “Anthropo-cene,” suggesting that the debate about climate is relevant, but that geology data is still lacking. They want to investigate when, exactly, humans began leaving a visible mark on the planet. There is no doubt that some of our technological advances have led to increased factory output and, as a result, pollution. The In-ternational Union of Geological Sciences convened a special group to study the world on and in which we live—the rock strata, the soil, the atmosphere—and will make a decision about what to call our current geologic time in 2017.

Regardless of which term we use going forward, it is difficult to argue against the fact that humans are Earth’s first species to wield planet-scale influence. Many of us find a certain comfort in fatalism, so there is a possibility that in accepting this new epoch, we absolve ourselves of blame and accept that our destiny as a species was set in motion nearly 12,000 years ago. There is also an opportunity in acknowledging that humanity has a stake in the ongoing evolution of our planet.

WatchlistThe International Union of Geological Sciences; the Nature Conservancy; the At-mospheric Chemistry and Physics Discussions and other pre-publication forum and open-review journal sites; the Anthropocene Working Group; U.S. Geological Survey

Key InsightScientists and geologists are in the middle of a heated argument about whether we are living in a new geological epoch, one that we’ve created ourselves in many ways because of the technologies we’ve created and use every day. Given that we posted some of the hottest temperatures ever recorded, the debate about whether we’ve permanently impacted the planet will be replaced by conversa-tions about what we need to do next.

ExamplesDepending on whose research and definitions you prefer, we are either in the “Holocene” epoch (from the Greek for “totally new), which began 11,700 years ago just after the last ice age—or we are in a new epoch, called the “Anthropo-cene” (anthro for “man,” and cene for “new”). At the beginning of the Holocene, the global human population was estimated between 1 - 10 million. Today, many smaller American cities boast 1 million citizens. The new geological layers we are creating are riddled with chemicals and industrial waste, everyday garbage, pesti-cide runoff and more. We’ve caused our sea levels to rise and our lakes and rivers to dry up. Ecologist Eugene Stoermer coined the term in the 1980s and Nobel laureate Paul Crutzen popularized it in 2000. Suddenly among earth-science re-searchers, the Anthropocene has found new momentum.

What’s NextSince 2014, each year on Earth has broken records for the hottest year in record-ed history. The North Pole saw temperatures above freezing. Smog in China has gotten so bad that government officials are building a building-sized air purifier in Beijing.


NASA’s SLS tank holds 196,000 gallons of liquid oxygen.

TREND 153



Space ExplorationFifth year on the list

become major players. Within the next 24-36 months, there will be a boom in launch vehicles, landers, probes, rovers, space stations and research craft. We’ll also see partnerships formed for asteroid and moon mining and for space man-ufacturing. There will be ancillary opportunities across industries, from durable clothing retailers to skilled manufacturing operations. In 2017, private equity firms should start looking at the soon-to-launch companies that will ultimately supply the tools, materials and technologies for commercial space operations.

WatchlistNASA; Amazon; European Space Agency; Indian Space Research Organization; China National Space Administration; DARPA; Scaled Composites and Virgin Galactic (The Spaceship Company); XCOR Aerospace; SpaceX; Interorbital Sys-tems; Stratolaunch; Masten Space Systems; Lockheed Martin; Northrop Grum-man; Boeing; Copenhagen Suborbitals; Orbital Sciences Corporation; Planetary Resources; Samsung; Facebook; Alphabet and many more.

Key InsightWith a commercial space exploration boom and civilians now planning to colo-nize Mars, 2017 should be a year of interesting announcements.

ExamplesBigelow Aerospace and Axiom Space have both announced that by 2020, they will have built commercial facilities for the International Space Station (ISS). NASA is hoping that the ISS will help support and grow commercial space activ-ities in the near-future as it focuses more of its attention on exploring Mars.

NASA is also readying the Space Launch System in preparation for deep space exploration. The James Webb Space Telescope, a massive observatory the size of a tennis court, is nearing completion. Some of the most exciting space innova-tion is centered deep inside the Mojave Desert, where 17 space-related companies are closing in on commercial space travel, exploration and development. XCOR and Virgin Galactic are gearing up to take non-astronauts into space...for fun.

What’s NextWe saw successful (and tragically, some unsuccessful) commercial space launch-es in the past two years. In September 2016, Elon Musk’s SpaceX suffered a major setback when its Falcon 9 rocket exploded.

Space agencies in Europe, China and the U.S. are hoping to either land on or get close enough to an asteroid to mine it or change its path. Expect to see humans headed back to the Moon and global discussions about whether or not we should make Mars a protected habitat, free of government fighting. China and India will


Emerging research from the University of Rochester: From a continuous range of viewing angles, the hand remains cloaked, and the grids seen through the device match the background on the wall (about two meters away), in color, spacing, shifts, and magnification.

TREND 154



Invisibility CloaksFirst year on the list

WatchlistDARPA; University of Rochester; U.S. Department of Energy’s Lawrence Berkeley National Laboratory; Kavli Energy NanoSciences Institute at Berkeley; the Univer-sity of California-Berkeley; University of Texas-Austin; University of Copenhagen

Key InsightResearchers are experimenting with electromagnetic and audio waves, tiny lens-es that bend light and reflective materials to hide objects in plain sight.

ExamplesThe cloak doesn’t exactly look like what you’ve seen in Harry Potter. In 2006, physicist John Pendry theorized that it was possible to hide objects using special optical lenses capable of bending light. In 2013, researchers at the University of Texas-Austin successfully experimented with a three-dimensional mantle cloak, which makes a 3D object invisible to radio waves. More recently, the Queen Mary University of London has been studying how to make curved surfaces look flat using a substance made out of thin layers that each have different electromag-netic properties. An object is hidden when the layers prevent waves from inter-acting.

What’s NextInvisibility cloaks have an obvious application for defense. However the same basic idea might be applied to other kinds of waves, including heat—meaning that in the future, we might be able to cloak everything from annoying sounds to the sun. And of course, whoever’s inside the cloak would be able to see outside, without being seen.


MatchMaker Exchange is an “Internet of DNA,” matching the DNA from sick people around the world.

TREND 155



Quantum ComputersSecond year on the list

What’s NextOne challenge that will need to be addressed in the next few years—how to com-mercialize this technology. IBM, Microsoft, Hewlett-Packard and Google, as well as D-Wave, are trying to figure out how to advance and commercialize the quan-tum computers. Quantum computers require special programs like Shor’s algo-rithm—invented by MIT’s Peter Shor—that can factorize any prime number. The National Security Agency is already predicting that the cryptography in use will be rendered completely obsolete once quantum computing comes online.

WatchlistD-Wave Systems; IBM; Alphabet (Google); Lockheed Martin; NSA; Microsoft; Hewlett-Packard; MIT; Stanford University; University of Southern California

Key InsightIn short, quantum computers can solve problems that are computationally too difficult for a classical computer, which can only process information in 1s or 0s. In the quantum universe, those 1 and 0 bytes can exist in two states (qubits) at once, allowing computations to be performed in parallel. Therefore, if you build two qubits, they are able to hold four values at the same time: 00, 01, 10, 11. Quan-tum computers are not only more powerful than anything built to date—they require special algorithms capable of doing new things. Scientists have been re-searching quantum computing for decades. The challenge has been proving that a quantum machine is actually doing quantum computations. That’s because in a quantum system, the very act of observing information in transit changes the nature of that data.

ExamplesD-Wave Systems recently announced that it will ship a 2000-qubit quantum computer in 2017, which would make it the fastest and most powerful computer on the planet. Researchers at IBM’s experimental quantum computing group have begun to unlock difficult problems in quantum computing, such as detect-ing errors. For example, classical computers can detect and correct errors using a system of copying and extracting the value from the correct bits. When a quan-tum computer tries to do the same thing, it alters the qubits just attempting to copy them.


Custom-printed shoes from Zaha Hadid at Milan Fashion Week.

TREND 156



3D PrintingSixth year on the list

WatchlistAutodesk; Organovo; MIT Media Lab; GE; Formlabs; Aurora Labs; Arc Group; Ex-One; Voxeljet; Stratasys; HP; Shapeways; MakerBot; University of Illinois Urbana; University College London

Key InsightIn the next year, we will see lots of new methods of 3D printing as well as innova-tive uses for the technology.

Examples3D printing isn’t just for keychains anymore. One of the biggest breakthroughs making 3D printing more practical is MIT’s new MultiFab printer, an intentionally hackable system that can print up to 10 materials at the same time, including hy-drogels, co-polymers and solvent-based materials...along with glass, wood, nylon, chocolate, metal and plastic. New machines can print really small—to a resolution of 40 microns, which is less than half the width of a human hair. Artist Jonty Hurwitz created a nanosculpture of a woman that stands a mere 100 microns. (A strand of hair looks like an enormous road with her on top.)

What’s NextThe Mediated Matter Group at the MIT Media Lab has developed a technique to print molten glass in 3D, and soon, the technology could be used at architectural scale. New organic materials—such as tissue suitable for human bodies—will be printed for use in medical procedures. In the next year, we’ll see companies cus-tom-printing orthotics and footwear, eyeglasses and athletic equipment. Soon, “one size fits all” won’t need to fit any one person ever again.


MatchMaker Exchange is an “Internet of DNA,” matching the DNA from sick people around the world.

TREND 157



Internet of XSecond year on the list

Key InsightWith so many objects, networks and people coming online, you will start to hear companies calling themselves the “Internet of X.”

ExamplesIsraeli startup Consumer Physics—a sort of Internet of Ingestibles— wants to put molecular spectroscopy into smartphones so that you can extract information out of your food and pills. This would enable you to scan a piece of chicken in order to search the fat and calories on your plate. Their research is also able to image prescription and over-the-counter drugs in order to spot counterfeits. Meantime, a new project called MatchMaker Exchange is an “Internet of DNA,” matching the DNA from sick people around the world.

What’s NextIt’s not unrealistic to say that in the near future, everything you see (and even the things you can’t) will become searchable via a distributed network. This will unlock layers of information previously unavailable to us—but it will also create a significant demand for verification.

WatchlistGlobal Alliance for Genomics and Health; Alphabet (Google); Personal Genomics Project; University of Southern California


5G is the fifth generation of wireless technology.

TREND 158



5GFirst year on the list

Key Insight5G trials, supported by the Federal Communications Commission and the Euro-pean Union, are underway around the world.

Examples5G is the fifth generation of wireless technology. We had 1G in the early 1990s and 2G in the late 90s, which enabled us to send text messages between two mobile devices. 3G supported our ability to browse the internet. Now, with 4G, we’re able to download and upload large videos. There are competing standards—WiMax and LTE. 5G will dramatically increase the speeds at which we connect—we’ll be able to pull Ultra HD and 3D video and use VR in the cloud, since download speeds will hover around 10 gigabits per second. But it isn’t just our phones that will use the connection: driverless cars, smart cities, and smart grids will all rely on 5G.

What’s NextHardware manufacturers like Qualcomm are readying 5G modems and advanced chipsets. For 5G to work, internet service providers will need to upgrade their networks. Verizon and AT&T have already begun piloting 5G, but it will be a few years before everyone has access.

WatchlistFederal Communications Commission; European Union; internet service provid-ers worldwide; car manufacturers; modem and chip manufacturers

Our focus is the future of technology. Every single business, industry and government agency is affected by the fu-ture of technology. Because FTI does not cover one single industry or vertical, we are uniquely positioned to help you and your leadership team understand the broader horizon.

We use a data-driven process.Forecasting is a science, one that we have been refining for more than a dec-ade. In fact, FTI’s six-part methodology has been featured in the Harvard Business Review. We don’t gaze into a crystal ball—and we don’t rely on fo-cus groups to tell us what’s trendy. Our research and forecasting models are data-driven.

We help R&D teams understand what’s next. When dedicated researchers are focused on their everyday work, it can be hard to see around corners. FTI helps R&D teams understand their research within the broader context of emerging technologies.

We help Leaders map their futures.Smart leaders need to know not just the emerging sources of disruption and opportunity, but what strategies to create in the present. FTI equips leaders with the tools necessary to future-proof their strategies against new technol-ogies and tech trends. We empower leaders to know where they are today, and how that informs where they should be tomorrow.

ABOUT THE FUTURE TODAY INSTITUTEWe are futurists. We investigate emerging technology in order to answer “What’s the future of X?” for our global client base. We help leaders, teams and individuals forecast the future so they can make better, more informed decisions, even as their organizations face great disruption caused by technology.


The Future Today Institute ensures that you and your organization will know all of the important near-future trends and any critical updates far earlier than anyone else.

Membership is open to organizations of all sizes and includes:

• Quarterly custom tech trends presentations and workshops in your office for you, your staff and (if you want) your clients

• Monthly personalized trends research and strategy packs (about 3 hours of reading)

• A monthly tech trends debriefing (voice or video) for you and your team

• A custom Slack channel just for you and your team

• Complimentary invitations to our Institute events, where you’ll meet with and learn from other Institute members.

To learn more about becoming a member of the Future Today Institute, call 267-342-4300 or email [email protected].

BECOME A MEMBER OF THE FUTURE TODAY INSTITUTE


The Future Today Institute researches emerging technologies at the fringes and tracks them as they move towards the mainstream.

The Institute’s Membership Program is our core offering. Our client members val-ue the research, custom trends presentations and events, where they can meet with and learn from other Institute members.

One Hour, Half-Day, Full-Day and Multiple-Day Trends and Forecasting WorkshopsPresenting a customized overview of trends that will impact an organization, as-sociation, company or group. Workshops range from half-day sessions to two or three-day intensives.

Project-Based AdvisingMapping the future of a discreet project or trend, or working with a leadership team to create a long-range strategic plan. Projects range from a few weeks to several months. Examples: An auto company asked us to forecast the future of driving, given what we know to be true today. We worked with a financial services company to forecast the future of credit cards. We advised a government agency on forecasting scenarios for the future of America’s relationship with Russia.

Pop-Up Think Tanks and SalonsWe draw upon FTI’s extensive professional network to convene pop-up think tanks and salons on behalf of our clients. Using our unique convening framework, we bring together your staff with experts from outside your industry for fresh per-spective and insights. We host them on behalf of clients all over the world.

OUR WORK


Amy Webb is Founder and CEO of the Future Today Institute, a lead-ing future forecasting and strategy firm that researches technology and answers “What’s the future of X?” for a global client base. She is the author of The Signals Are Talking, Why Today’s Fringe Is Tomorrow’s Mainstream (PublicAffairs, Dec. 2016), a book about how everyone can and should use the tools of a futurist.

Amy teaches courses on the future of technology at NYU’s Stern School of Business and the future of media at Columbia University. She was a 2014-15 Visiting Nieman Fellow at Harvard University, and her research on the future of postsecondary education reform received a national Sig-ma Delta Chi award.

Amy’s research focuses on how technology will transform the way we work, lead, govern and live. Her future forecasting work has been fea-tured in the New York Times, Harvard Business Review, Wall Street Jour-nal, Fortune, Fast Company, CNN, NPR, and more. Her research has also been cited in several academic papers. She and FTI have advised For-tune 50 companies, government agencies and foundations, as well as some of the most influential global leaders.

Amy holds many professional affiliations and collaborates with a number of institutions. She was a Delegate on the former U.S.-Russia Bilateral Presidential Commission and served on the Aspen Institute’s Dialogue on Libraries, where she worked with FCC Chairman Reed Hundt and oth-ers on the future of libraries. Every year, Amy lectures about the future of media and technology at a number of universities, which have included Institut d’études politiques de Paris, Temple University, Tokyo University and National University of Kyiv.

She works out of FTI offices in New York City and Washington D.C.

ABOUT THE AUTHOR


We invite you to learn and use the tools of a futurist. Amy Webb’s new book: THE SIGNALS ARE TALKING: Why Today’s Fringe is Tomorrow’s Mainstream arrives at a fortuitous moment, as it gives critical guidance on how to think like a futurist in order to most accurately answer pressing questions about the future of emerging technol-ogies, science, our economy, political systems, and civil liberties.

“A rare treasure: a substantive guide written in a narrative that’s a delight to read.” —Christopher Graves, Global Chair, Ogilvy Public Relations

“[The Signals Are Talking] provides several brain-bending future possibilities...Webb’s stellar reputation in this red-hot field should generate demand.” —Booklist

“A logical way to sift through today’s onslaught of events and information to spot coming changes in your corner of the world.” —KIRKUS


THE SIGNALS ARE TALKINGWhy Today’s Fringe is Tomorrow’s Mainstream

Amy WebbPublication date: December 6, 2016

$27.99/34.99 CAN • 336 pages • ISBN 978-1-61039-666-0

21st Century Fox

3M

ABB Robotics

Abide

ABRA

ACLU

Ad Ready

AdExtent

Adler Seeds

Adria Corporation

AdRoll

Advance Publications

Aeon

Aethon Inc.

Agria Corporation

Airbnb

Alico Incorporated

Alliance for American Manufacturing

Alltech

Alphabet

Alphabet (Google)

Amazon

Amazon Web Services

American Enterprise Institute

American Vanguard

Anonymous

Anthropocene Working Group

AOL

Apple

Appsfire

Arc Group

Archer Daniels Midland

Aria NLG

Asahi Shimbun Company

Astra Zeneca

AT&T

Atmel

Auphonic

Aurora Labs

Austrian Institute of Technology

Autodesk

Automated Insights

Autonomous Solutions

Ava Winery

AVEBE

Axel Springer

Backchannel

Baidu

Bank of America

BASF

BBC News

BBDO

BBH

Bell Labs

Bernard Matthews Farms

Bertelsmann

Bitter Southerner

BitTorrent

BlipTrack

Bloomberg

Boeing

BOKU

Boost VC

Boston Dynamics

Boxbee

Branch

BTC

BTCC

BTCS

Buddy

Business Leaders

Button

BuzzFeed

C-Suite executives

Cadreon

Camera Culture Research Group at the MIT Media Lab

Cargill

Carnegie Mellon University

Case Western Reserve University

CBS Corporation

Center for BioInterface Research at Georgia Tech

Chartbeat

Chatfuel

China

China National Space Administration

Circos VR

CITI

Cloudera

CloudPeeps

CNN

Cognitive Horizons Network

Coin base

Coin desk

Coinsetter

Columbia Journalism Review

Comcast

Content-producing organizations

Copenhagen Suborbitals

Coursera

Criteo

Critical Mass

Crowd Companies Council

Crowdtangle

Crystal

CVS

D-Wave Systems

DARPA

DataONE

Deeplink.me

Department of Defense

Department of Energy

Department of Health and Human Services

Department of Homeland Security

Department of Housing and Urban Development

Department of Justice

Department of Transportation

Design Lab

Digital Asset Holdings

Discovery

Discovery Communications

Disney

DNV GL

doubleclick

Dow Chemical Company

DreamBox

Droga5

Dropbox

Duke University

DuPont

EatWith

eBay Enterprise

EdX

EFF

Electronic Frontier Foundation

EMC

Energid Technologies

Environmental Protection Agency

Epic Games

EPSON Robotics

ESA Data Registry

ESPN

Estimote

Estonia

Etsy

European Space Agency

European Union

ExOne

Expect Labs

ExxonMobil

Facebook

Facebook Exchange

FANUC Robotics

FarmLink

Fastacash

FDA

Federal Bureau of Investigation

Federal Chief Information Officer

Federal Communications Commission

Financial Times

Finland

fon

For Labs

Fuji Media Holdings

Fujitsu

Funding Circle

Future Meat

Gannett

Garage Band

Geekie

General Electric

Gimbal

Global Alliance for Genomics and Health

COMPANIES, ORGANIZATIONS, UNIVERSITIES AND GOVERNMENT AGENCIES MENTIONED IN OUR 2017 TRENDS REPORT.


Goodbye Silverstein & Partners

Google

Government Accountability Office

Greylock Partners

Grupo Globo

GSD&M

GSK

Guardian

HackerRank

Harvard University’s WYSS Institute

Harvard-MIT Division of Health Sciences & Technology

HBO

Hearst Corporation

Heroku

Hershey’s

Hewlett-Packard

HipChat

Hitachi

Home Depot

Honeywell

HSBC

Hubert Burda Media

HumanAPI

HunchLab

IBM

IBM Research

IBM Watson

IFTTT

IHeartMedia

ImageNet database

Indian Space Research Organization

ING

Ingenious

InMobi

Inner Space VR

Instagram

Institute of

Anthropomatics and Robotics at the Karlsruhe Institute of Technology

Insurance companies

Intel

Interactive Advertising Bureau (IAB)

International Union of Geological Sciences

Internet Archive

Interorbital Systems

Interviewed

Investigative Reporters and Editors (professional association)

Iowa Farm Bureau

ISIS

ITV

Johns Hopkins University

Journalism organizations and professional associations

Kaggle

Kakapo Talk

Karlsruhe Institute of Technology

Keonn Kavli Energy Nanosciences Institute at Berkeley

Kitestring

Knewton

Knowledge Network for Biocomplexity

Kraken

Leap Motion

LeftoverSwap

LendingClub

Leo Burnett

Lexus

Libsyn

Life360

Line

LinkedIn

Lockheed Martin

Lowes

Lyft

MailChimp

MakerBot

Margot Kaminski, Assistant Professor, Moritz College of Law, The Ohio State University

Marrone Bio Innovations

Master Space Systems

Mastercard

Mattersight

McClatchy Corporation

McGraw-Hill

Media organizations

Mediaset

Medicaid

Medicare

Memory Mirror

Mic

Microsoft

MIT

MIT Media Lab

MIT’s CSAIL

MIT’s Interactive Robotics Group

MobileDeepLinking.org

MongoDB

Monsanto

MoPub

Mosaic

Mother Jones

MuelSoft

Mumble

MuniRent

Mya A.I.

Nanyang Technological University

Narrative Science

NASA

National Academy of Science

National Association of Manufacturers

National Institute for Computer-Assisted Reporting

National Institute of Justice

National Instruments

National Public Radio

Nature Conservancy

Nautilus

Netflix

Netherlands

New Inquiry

New York Times

New York University

NewsCorp

Nielsen

Northrop Grumman

Northwestern University

Norway

Novartis

NSA

Nutonian

OakLabs

Office of Management and Budget

Office of Science and Technology Policy

Ogilvy & Mather

OpenAG Initiative at MIT

OpenX

Orbital Sciences Corporation

Organization for Economic Co-operation and Development

Organovo

Oxford University

Pacific Standard

Palantir Technologies

Pandorabots

PayPal

PBS

Pearson

Peercoin

Pennsylvania State University

Personal Genomics Project

Planetary Resources

PlantVillage

Polytechnical University (China)

Postmates

PredPol

PRI

Prospera

PRX

Purdue University

Qualcomm

Quixey

Razorfish

RBS

Reclaim

Recruit Strategic Partners

REDEF group

Refinery 29

Rent The Runway

Research Center on Information Technologies (CiTIUS)



Reverge VR

Ripple

Robin Labs

Robocoin

RoundPegg

Russia

Russia Today

Salesforce

Samsung

SANParks Data Repository

Scaled Composites and Virgin Galactic (The Spaceship Company)

Schneir on Security

School of Informatics University of Edinburgh

School of Science and Engineering

Scuola Superiore Sant’Anna

SecondMarket

Seegrid

Sewbo

Shapeways

Sharp

shyp

Skype

Slack

Smart Sparrow

Snapchat

Snapgoods

SoftBank Robotics Corporation

Sony

SoundCloud

SpaceAway

SpaceX

Spain

Sparkbox

SpeakPipe

Spotify

Square

Stanford Center for

Philanthropy and Civil Society

Stanford University

Stanford’s AI Lab and Vision Lab

Starlab

StartVR

State Department

Stitcher

Stratasys

Stratolaunch

Strava

Survios

Sweden

Syngenta

Tactio

tapCommerce

Tesla

The Atmospheric Chemistry and Physics Discussions

The Information

Three One Zero

Time Inc.

Time Warner

TimeBanks

TinyLetter

Tow Center For Digital Journalism

Toyota

Toys Trunk

Trello

tronc

Tufts University

Tumblr

Twilio

Twitter

Tyson Foods

U.S. Census

U.S. Department of Energy’s Lawrence Berkeley National Laboratory

U.S. Geological Survey

U.S. National Science Foundation

Uber

UBS

Udacity

ULC Robotics

UN Food and Agriculture Organization

University College London

University of Aberdeen

University of Birmingham

University of California -

Berkeley

University of California - Los Angeles

University of Chicago

University of Copenhagen

University of Dundee

University of Illinois at Urbana

University of Maastricht

University of Maryland

University of Massachusetts

University of Michigan

University of New Mexico

University of Oxford’s Martin Programme on the Impacts of Future Technology

University of Pennsylvania’s Nano/Bio Interface Center

University of Rochester

University of Santiago de Compostela

University of South Wales (Australia)

University of Southern California

University of Stuttgart

University of Texas Austin

University of Tokyo

University of Toronto

University of Washington

University of Washington’s Center for Sensorimotor Neural Engineering

Upstart

Upworthy

USC Robotics Research Lab

USDA

Validic

Valve

vandebron

Venmo

Verily Life Sciences

Verizon

VEX Robotics

Viacom

Vice

VirtualSKY

Vivify

VML

Vocativ

Vox

Voxeljet

Vserv

Vungle

Walgreens

Walmart

Washington Post

Wayfair

WeChat

Wevr

WeWork

White House Council of Economic Advisors

White House OSTP

Widen + Kennedy

WikiLeaks

Worchester Polytechnic Institute

World Bank

XAPO

Xaxis

XCOR Aerospace

Xerox

Y Combinator

Yahoo

Yale University Law School

Yamaha

Yammer

Yomirui Shimbun Holdings

YouTube

Zendesk



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