THE POTENTIAL AND LIMITATIONS OF FORESIGHT...BIDIRECTIONAL OLED-MICRODISPLAY, Fraunhofer IPMS nincreasingly dense technological surroundings nexpanding technical structure of human

© Fraunhofer ISI

Dr. Kerstin Cuhls, Fraunhofer Institute for Systems and Innovation ResearchConference POWER FROM STATISTICS 19/10/2017

THE POTENTIAL AND LIMITATIONSOF FORESIGHT

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AGENDA

1. Foresight: more than Statistics

2. Methods for thinking unthinkablethings

3. Some Future Developments

4. Benefits in times of uncertainty

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F O RES I G H TForesight is the

structured debate

about complex futures

§ structured: systematic approach by applying methods of futures research, science-based, based on new theories of futures research

§ structured debate: interaction of relevant actors, active preparation for the future ordifferent futures, orientation towards shaping the future

§ complex: consideration of systemic interdependencies, holistic view

§ futures: open view on different paths into the future, thinking in alternatives

Ø long- and medium-term view

Ø no planning, but a step on the way to planning (strategic foresight)

Ø no prediction

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D i f f e r en t F u tu r e s s y s t ema t i ca l l y exp lo r ed

present possible future(s)

desirable future (s)

probable future(s)

sharedvision

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D i f f e r en t Q ues t i ons

F o r e s i g h t a s a b a s i s f o r s t r a t e g i c d e c i s i o n s

shared vision,


probable future (s)

possible future (s)

What does a desirable future look like?

Which probabledevelopments can already be detected?

What are the possiblealternative development paths?

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D i f f e r en t M e thods / combina t ions

Where do we want to go?

What can happen?

Where have we come from?

How to reach our goals?

How to prepare forthe future?

Where are we now?

What is expected?

What are our options?

Visions/concepts

Scenarios

What inspires us?

Roadmaps

Environmental/ Horizon scanning

Trend analyses

What is happening where?

SWOT

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probable future

possible future

Future workshops

(Delphi)

Surveys

shared vision,


Interviews

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D IF F EREN CE TO S TA TI S TI CS , CU RV ES , G R A P H ICS . . .

1 2 3 4 5 6 7 8

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T ime H or i zon

perspectives

from

different

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P e r cep t io n f i l t e r s

1. Surveillance filter limited capacities for 360 degree observation

2. Mentality filter experiences of the past are benchmarks for evaluation of signals and their relevance for own actions (pre-disposition)

3. Power filter Routines and hierarchies have influence on perceptions

4. Desirability bias Positively perceived developments are expected to have a higher degree of probability (Ecken, Gnatzy et al. 2011)

5. Overprediction biasWe overestimate our ability of prediction and underestimate uncertainties (Schoemaker 2003)

6. End of history illusionWe underestimate dynamics of change and expect the current status to be stable (Quoidbach et al 2013)

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FILTERS CANNOT BE ELIMINATED BUT OPENED UP

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FORESIGHT: EXAMPLES FOR DEVELOPMENTS

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On behalf of the Federal Ministry of Education and Research (BMBF)n The BMBF Foresight Process, Cycle I (2007-2010)

THE BMBF'S FORESIGHT PROCESSTH E S EV EN F U TU RE F I ELD S

ProductionConsumption2.0

Human-Technology Cooperation

DecipheringAgeing

Sustainable Living Spaces

Transdisciplinary Models and Multi-Scale Simulation

Time Research

Sustainable EnergySolutions

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Why H uman- Tech n o lo g y Bounda r y S h i f t sn e w p r o x i m i t y t o p e o p l e , t h e i r b o d i e s , b r a i n s a n d d a i l y l i v e s

§ ambient assistive living, smart environments, ambient intelligence

§ mixed-, augmented reality§ robotic exoskeletons§ “physical Avatars”, VR-immersion,

telepresence and teleaction§ various Assistance Systems § anthropomimetic robots§ software agents (virtual broker)§ neuroprostetics, implants§ … BIDIRECTIONAL OLED-MICRODISPLAY, Fraunhofer IPMS

n increasingly dense technological surroundings

n expanding technical structure of human life

Human-Technology-

Teams

Neuroprosthetics, -implants

Philosophy of technology

NeuroenhancementIntelligent prosthetics

Autonomous robotics

AI research

Software Agents

Ambient Intelligence

Intelligent automation

Assessment of the consequences of technology

Affective Computing

Anthropology

Aesthetics

Brain-Machine-Interface

Sensors

VR-Immersion

Semantic technologies

Adaptive environments

Social robotics

Pervasive ComputingNanoethics/Neuroethics

Technical genesis/ Innovation research

Physical Avatars

Behavioural sciences (Neuro/Psycho)Telepresence /Teleaction

Micro-systems technology

Intelligent materials

Semantics

Anthropomatics

Media technology/image sciences

Social structure analysis/social policy

Empirical social research

Human-Machine-Culture

Redefininghumanity

1

2

3

4

Machineagents

Human-Machine-Systems

HumanTechnologyCooperation

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Anthropomimesise m b o d i e d c o g n i t i o n , h u m a n l e a r n i n g a n d d e v e l o p m e n t

Left: iCub an open source cognitive humanoid robotic platform http://www.icub.org/Above: CB2 robotic child created at Osaka University, Japan Right: ECCEROBOT Embodied Cognition in a Compliantly Engineered Robot http://eccerobot.org/


Hybr id human- technology cons te l la t ionss e a m l e s s i n t e r a c t i o n

Left: HAL (Hybrid Assistive Limb®) y CyberdyneMiddle above: BBCI berlin brain computer interfaceMiddle below left: OLED microdisplay based Eyetracking HMD, Fraunhofer IPMS, 2011 Middle below right: VI-Bot (DFKI) Virtual Immersion for holistic feedback control of semi-autonomous robots Right: Amanda Boxtel, before this 18 years reliant on a wheelchair. Now having a walk in the park with E-Legs by Berkeley Bionics


BMBF Fores ight Process Cycle 2 2012-2014

Search for open, hiddenand normative societal

trends

60 Trend profiles

Deriving societalchallenges

8 Thematic Fields

Update of the resultsfrom the first BMBF

Foresight Cycle + socialsciences and humanities

11 Science and Technology Fields

Search for societalchallenges

Search forScience and Technology

perspectivesInterlinking societal challenges withresearch and technology perspectives

20+ „Innovationskeime“/ Innovation seeds and 7 „Stories from the Future 2030“


Example : Quant i fy ing Sel f /Se l f -op t imisa t ion – Me and my body

New cognition about own well-being,

together with technically supported

self-monitoring (quantified self),

e.g. with optic micro or nanosensors, mobile devices

(+ software)


Dig i ta l Revo lu t ion / B ig Da ta : M e in the (g loba l ) w or ld

• Change in the understanding of private sphere – when everydaylife is more and moredigitalized

• increase in central datastorage and analytics, e.g. in the fields of security, market research, administration


Post-Privacy vs. Privacy ProtectionWorldwide detailed knowledge on people’s habits and preferences becomes accessible to external actors. The border between of public and private spheres is shifting.

A- PostPrivacywithverylimitedcontrolcontrolControlofonesowndataisimpossible.Beingatthewrongplaceinthewrongtimemayhaveseverepersonalconsequences.

DRIVERS

Moreandmoreareasofworkanddailylifearebeingdigitalisedandconnected

Inordertobenefitfromwebbasedservicesuservoluntarilyletgooftheirprivateinformation

Providersgetholdonenormousamountsofdatafromwhichdetaileduserprofilescanbededucted

Theconnectionofdatasetsgeneratesnewinformationaboutindividualswithouttheirknowledge

B– Hyper-TransparencySocietywithoutsecretswherenobodyneedstoorwantstohideanything.Everybodyisfreelyprovidingpersonalinformation.Thenewopennessisseenasahugelearningopportunityforsociety.

C– StrictPrivacyProtectionCloseinteractionbetweencarefulusersandprivacy-protectingtechnicalsystemsallowsformaximumcontroloverpersonaldata.

POSSIBLEFUTUREPATHWAYS2030


Da ta - in tens ive Governance

• detailed data collection and (nearly) realtime, networkedanalysis change the Governanceprocesses on nearly all levels

• (Smart) Cities as „Global laboratories“ of data-intensive governance

Ø decision-making (support) bymachines? (source: BOHEMIA)

Statistics automatized


Co l l abo r a t i ve ly expe r imen t ing f o r f u tu r e s o lu t i ons

• Experimentation in Realtime

• Labs

• Reality

• together with citizens

• Citizen Sciences deliveringthe data for statistics


Science on the moveChanging ways of doing, organising, publishing and teaching science.

A– ScienceasoneofmanyScienceisbeingcomplementedandblendedwitharangeofothertypesofknowledgesuchasindigenous,intuition,arts,craftsmanshipwhichallcompeteforresourcesandlegitimacy.

DRIVERS

Globallyrisingdemandforscientificknowledge

Newcountriesbecomekeyplayers

ICTenablescooperationingeneratingandusingknowledgeacrosstheglobeaswellasuniversalaccess

Newformsofknowledgegenerationrequested:trans-disciplinary,systemic,experimental,solutionoriented

riseofpartlyconflictingdemandsonscience

B– Anewscience/societycontractScienceinallitsdisciplinesiswidelyrecognisedinsocietyandgenerouslysupportedfrompublicandprivatesources.

C – Slow Science

Triggeredbyamovementofscientists,qualityandpurposeofscienceisbeingredefinedfromwithinthesystem.

Societyquestionsusefulnessofscience,increasingcompetitionforresources

Otherformsofknowledgegainlegitimacy

Increasingrelevanceofdatabasedmethods

Risingnumberofonlinecourses

“Scientometrics”indicatorbasedassessment

POSSIBLEFUTUREPATHWAYS2030

New way for sciences/ official statistics?

official statistics

as one of many?


AND A LOT OF TECHNOLOGY...


Biomass based sustainable production§ Refineries producing fuels, power, heat

and materials from biomassØ Improved energy and material efficiency

across the product lifecycle

Molecular Bio-Production§ Biotechnology operating on the scale of a

moleculeØ Molecular switches

Technology platforms§ Analysis of biological functions

and principlesØ “brain mapping”Ø Personalised medicine

Biotechnology investigates living organisms and their building blocks and uses their functions for technical purposes. https://news.usc.edu/files/2015/03/brai

n2-824x549.jpeg

http://www.pfizer.ie/images/template2/personalized%20medicine_big.jpg

towards a

BIOECONOMY?


Hybrid business models§ Integrating goods and

services into consistent offers

Service Engineering§ Systematic development of

services and experiences using engineering methods

Integrating services and new technologies§ Automation of transaction based

services to create space for interaction based activities

Ø „self-services“, remote maintenance, diagnosisØ measuring effectiveness and efficiency of services

Modelling and simulation of services

§ Modelling value creation networks and human experience

Services within a context of decentralised production

Ø Do-It-Yourself-offersØ Repair and spare parts

Services create value for and with the customer through unique intangible offers

http://www.innovation-digital.de/virtuelles_unternehmen/serviceengenering.gif


Molecular analytics and diagnosticsBetter understanding due to more detailed insights into mechanisms (e.g. Imaging technologies)

Personalised medicine and nutrition § Personalised therapies and nutrition concepts

based on individual diagnostics (biomarkers )§ „Quantified self“, measuring food intake§ Modelling lifestyle and therapy effects

Sustainable Healthcare System§ New concepts of healthcare

provision and diagnostics

Medical technology and e-health Ø Linking diagnostics and

therapyØ High-Tech-ProsthesesØ Bio implantsØ IT-networked health system

Food allergies Designer Food, Functional Food, Medical Food

Ø „Antisense-Strategy“ (Reduction of allergenic components)

Ø Metagenom analysis, probiotics, prebiotics

Ø Molecularbiological routine-diagnostics of food

Health and Nutrition

Health research (natural science & medicine) to foster health, combat diseases and secure provision of healthcare. Interplay of health and nutrition.


Efficiency in energy use§ Demand reduction is vital to achieve goals at acceptable

costs § Need to overcome fragmentation of technologies and

approachesØ Efficient systems for heating, lighting, air conditionØ Understanding of interactions in complex systemsØ Radical process innovation in energy intense industries

Energy ProvisionGerman goals until 2050: reduce carbon emissions 80-95% vis a vis1990, increase share of energy from renewable sources to 80% and reduce energy demand by increasing efficiency until 2050,.Challenge: secure stable and affordable supply in spite of fluctuating sourcesØ Adaptable conventional plantsØ Technologies for exploiting solar and wind energyØ Energy from wasteØ Fuel cells

Energy System§ Transport huge and volatile amounts of

power across long distanceØ Increase transport capacityØ Technologies for smart control of

flows and for storage

Enabler§ Efficient, robust and affordable electronics§ Storage technologies for electricity § System analysis and modelling (including user

behaviour)§ New materials§ Participatory methods to involve users /citizens into

system design

Energy: Technological and organisational innovations for transforming, transporting and storing energy and maximising the efficiency of energy use.

GRIDS and interplay as the

major problem + infrastructure


Logistics§ Cyber-physical logistics systems where all goods and plants are

connected

Ø Flexible variants and lot sizes Ø Transparent material flows

§ Dematerialised logistics: only data is “transported” the product materialises at the final destination of useØ Reduction of transport cost and carbon emissions

„Autonomous“ Driving§ Communication between

vehicles and between vehicles and infrastructure

§ Driverless control

Ø Better security and comfort especially for elderly drivers

IT-Services in/for the vehicle§ New interfaces with driver

Ø Personalisation via Smartphone Ø Sharing and renting of vehiclesØ Location-based services e.g. parking space

§ After Sales services such as maintenance and remote diagnostics

§ Provision of information e.g. Energy saving options

Multimodal Mobility§ Connected vehicles and fleets

Ø Integrated mobility services Ø Seamless availability of car on demand

lift-sharing servicesØ Mobility services for elderly personsØ Seamless ticketing across transport modes

§ Real time data exchangeØ Seamless connection and coordination of

transport modes and providers on the one hand and users on the other

Ø Advice for optimal mobility tailored to situation

§ ICT-Services for multimodal mobilityØ One-Stop-ShopØ Integrated payment concepts

Vehicle and drive concepts § Combustion engines § Electric drives (battery based or hybrid)§ Lightweight construction principles

Ø Reduction of emissions and noise

Mobility enables us to move across spatial distances. Mobility research is investigating suitable vehicles and infrastructures enabling mobility.


Sensor and detection technologies§ Real time early warning systems for

traces of dangerous substances§ Mobile detectors for dangerous

substances (artificial noses)Ø E.g. Monitoring quality of

drinking water

Protection technology and equipment§ Self healing materials§ Carriers for safe transport

and targeted release of substances

§ Autonomous energy autonomous sensor systems that monitor the state of buildingsØ Protection of critical

infrastructures

Biometrics und Pattern Recognition§ Visual Analytics: Automated analysis and

interactive visualisation of very large amounts of data (Big Data Mining).

§ Behaviour analysis§ Combating cybercrime

Technologies for navigation, observation and localisation§ Navigation and localisation of persons in

buildings (wireless, real-time, radar based)§ Very small satellites (Nano-/ Pico-/Femto)

Ø Judging the situation in natural disastersØ Localising and saving people in danger

Artificial Intelligence, Robotics§ Swarm robotics: autonomously operating, communicating

and cooperating systems of robots § Miniature autonomous flying robots § Chemical Robots (ChemBots): soft, flexible, shape

changing floor robots § Bio mimetic AUV: Miniature autonomous underwater

robots with bio mimetic drives and sensorsØ Intelligence gathering for disaster situations

Simulation and Modelling§ Augmented Reality (AR): Computer based

provision of context specific information about the real world in real time

§ Contact lens displays providing information right in front of the user’s eye

§ Software based modelling of cities and regionsØ Planning for the protection of critical

infrastructures, information and decision support in disasters

Research for civil security is an interdisciplinary research domain contributing to the protection of humans, infrastructures and organisations against both purposefully damaging actions and impacts of natural or technical disasters.

http://www.ifam.fraunhofer.de/content/dam/ifam/de/images/dd/ETM/Simulation/gro%C3%9F_Berechnungsgitter%20f%C3%BCr%20w%C3%A4rme-%20und%20str%C3%B6mungstechnische%20Simulation.png Is technology

the solution?

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binfind.com

Limits of Foresight:

Who participates? Who is asked?

same problem forstatistics

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• often: a lot of objectives

• sometimes: even contradictory

• Hidden Agendas

impactlearning.com

Limits of Foresight:

Too many objectives in FORESIGHT and

policy-making?

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Lim i t : Res ou r ces f o r F O RES I G H T?

Lim i t : To iden t i f y „The U nus ua l “ i s o f t enexpec t ed , bu t

i t i s impos s ib l e to iden t i f y w hen you do no t knoww ha t and w he re to a s k . . .

white spots…

schnittpunkt2012.blogspot.com

© Fraunhofer ISI

a nd i f you have iden t i f i ed unus ua l th ings f o rpo l i cy - mak ing . . .

n they are not politically correct

n not implementable in the existing organisation

n unbelieved

n so far away that they do not touch me

Ø Policy makers have many reasons to ignore the future (s)

Ø STATISTICS and FIGURES help to evoke attention and underpin the newfindings

Ø ...help to underline what and where to search


Fores igh t was concept iona l i sed to s tep back/ ou t o f the da i ly bus iness to deve lop a pos i t ive v iew

And thinkimaginedream

consider barriersconsider chances…

emsaal.itcilo.org

http://www.google.de/imgres?imgurl=http://thelucidplanet.com/wp-content/uploads/2015/02/creativity.jpg&imgrefurl=http://thelucidplanet.com/riding-your-flow-8-steps-for-enhancing-your-creativity-and-productivity/&h=1536&w=1536&tbnid=s3TJLJqKfUaclM:&zoom=1&tbnh=122&tbnw=122&usg=__Cz1xwzbqAkg3PH9WhhDHPhG2Xek=&docid=I7ESwuWtvhhrxM


Bene f i t s : M or e F o r e s igh t combined w i th S ta t i s t i c s

• from Statistics and former trends: early warnings

• more creativity and other pointsof view/ perspectives combined

• integrate the long-term thinking

• you will detect more options forindicators and for policy-making

• you will detect more alternatives for your action – even short-term, even in daily work


You can change something,make it happen

within your limits!

With the long- te rm v iew


Sor ry

Foresight is nothing for couchpotatoes or

Business As Usual

Activity needed


Never t rus t s ta t i s t i cs tha t you d id no t fake yourse l f . . .

Be aware of all yourfilters…


Fores igh t p rovides working mater ia l

Don‘t believe in yourstatistics – don‘t believe in

your Foresight!…update it…


Anthropomimetischer Robotertorso - ECCEROBOT

Have a brightfuture!

For further information:Dr. Kerstin [email protected]

Documents

THE POTENTIAL AND LIMITATIONS OF FORESIGHT...BIDIRECTIONAL OLED-MICRODISPLAY, Fraunhofer IPMS nincreasingly dense technological surroundings nexpanding technical structure of human