Contested Collective Intelligence Resilience, Complexity & Sensemaking

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Simon Buckingham Shum & Anna De Liddo Knowledge Media Institute, Open Learning Network Project Open University UK http://people.kmi.open.ac.uk/sbs http://people.kmi.open.ac.uk/anna

PARC, Apr 1st 2011

Acknowledgements

Open Learning Network project (2009-12): olnet.org funded by the William & Flora Hewlett Foundation

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OLnet Collective Intelligence workstream: http://olnet.org/collective-intelligence

Developing conceptual foundations and infrastructure (people+proceses+tools) for Contested Collective Intelligence on the open social web.

Example: Open Education Evidence Hub http://ci.olnet.org (alpha)

Your team, organization, school, professional network, community...

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Your team, organization, school, professional network, community...

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Your team, organization, school, professional network, community...

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How do we augment this system’s capacity to sense, respond to, and shape its environment?

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§  Through the lens of complex adaptive systems, resilience and network science...

§  Through the lens of sensemaking and HCI...

§  Hypermedia Discourse: social-semantic web + models of discourse

How do we augment this system’s capacity to sense, respond to, and shape its environment?

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§  Through the lens of complex adaptive systems, resilience and network science... §  many interacting agents (human

and software) §  many weak signals that can

build up unexpectedly §  diversity and redundancy §  feedback loops §  visual analytics to reveal

emergent patterns and network properties

§  ability to withstand change and shock to the system

Resilience

§  Walker, et al. (2004) define resilience as

“the capacity of a system to absorb disturbance and reorganize while undergoing change, so as to still

retain essentially the same function, structure, identity, and feedbacks”

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Resilience Platforms

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http://www.futureofed.org/driver/Platforms-for-Resilience.aspx

Resilience Platforms

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http://www.futureofed.org/driver/Platforms-for-Resilience.aspx

Creating flexibility and innovation amid system failures “Platforms for resilience - enabling responsive flexibility, distributed collaboration, and transparency - will allow institutions to meet such challenges through innovation, adaptation, and openness.”

Resilience in knowledge-intensive ecosystems

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When knowledge and understanding are key variables in the system, resilience depends on the capacity for learning

e.g. awareness of discrepant evidence, critical practice, reflection and dialogue when confronted by challenges or shocks to the system.

How does this help?

Working hypothesis:

Confronted by overwhelming complexity... (e.g. incomplete, ambiguous data, complex adaptive systems, diverse perspectives, technical/social/political dimensions, time pressure…)

…Personal and Collective Cognition

break down in particular ways…

We need Theories, Tools and Practices in order to create CI for tackling such dilemmas

(and we need ways to teach these, both to our children, and the current workforce)

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Augmenting human intellect (ack. Engelbart)

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Phenomenon Role for CI infrastructure? Dangers of entrained thinking from experts who fail to recognise a novel phenomenon

•  Pay particular attention to exceptions •  Computer-supported argumentation •  Make the system open to diverse

perspectives ontologically, and in usability

Complex systems only seem to make sense retrospectively: narrative is an appropriately complex form of knowledge sharing and reflection for such domains

•  Stories and coherent pathways are important

•  Reflection and overlaying of interpretation(s) is critical

Patterns are emergent •  Generate gestalt views from the data evidenced in the platform, not from preconceptions

Much of the relevant knowledge is tacit, shared through discourse, not formal codifications

•  Scaffold the formation of significant inter-personal, learning relationships

Many small signals can build over time into a significant force/change

•  Enable individuals to highlight important events and connections à aggregate

•  Recommend connections based on different kinds of significant relationship

Sources include: Weick (1995); Kurtz & Snowden (2003); Browning, L. and Boudès, T. (2005); Hagel et al (2010)

Designing CI to embody resilience principles

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Resilience principle Role for CI infrastructure? build in the potential for diversity •  manage diversity of worldviews, and the

tensions this sets up make tight feedback loops •  shared awareness of dis/agreement

amongst peers promote building of trust/social capital

particularly for learning and sensemaking

•  using social media to build learning relationships: trust, affirmation, challenge

enable experimentation •  effective dissemination of findings in relation to key issues and what is already known

use a decentralised, modular architecture

•  both technically (enabling innovation, interoperability and mashups) but also in how we represent interpretations (ideas as networks, not big chunks of text)

a stable state – however temporary – in epistemic terms is a plausible narrative

•  model key coherence relations; explore narrative indexing

How do we augment this system’s capacity to sense, respond to, and shape its environment?

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§  Through the lens of sensemaking and HCI... §  many plausible narratives: what

was, is, or might be going on?... §  many representational artifacts

being shared and annotated §  attention to the quality of

conversation: how well are agents listening to each other and what kinds of contributions do they make?

§  informal interaction mixed with stronger public claims

§  many connections being made, both formal and fuzzy

• critical thinking • argumentation • rhetorical moves • assumptions • analogical thinking

• causality • juxtapositions • “kinda related...”

Sensemaking: the search for plausible, narrative connections

§  In their review of sensemaking, Klein, et al. conclude:

§  “By sensemaking, modern researchers seem to mean something different from creativity, comprehension, curiosity, mental modeling, explanation, or situational awareness, although all these factors or phenomena can be involved in or related to sensemaking. Sensemaking is a motivated, continuous effort to understand connections (which can be among people, places, and events) in order to anticipate their trajectories and act effectively. […] A frame functions as a hypothesis about the connections among data.”

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Sensemaking

Weick proposes that: §  “Sensemaking is about such things as

placement of items into frameworks, comprehending, redressing surprise, constructing meaning, interacting in pursuit of mutual understanding, and patterning.” (Weick, [23], p.6)

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Sensemaking

Weick: §  “The point we want to make here is that

sensemaking is about plausibility, coherence, and reasonableness. Sensemaking is about accounts that are socially acceptable and credible” ([23] p.61)

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contested collective intelligence...

conversations are critical to sensemaking

there is no master worldview

we need CI infrastructures to pool awareness of how people are reading small signals, and amplify important

connections

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Where our tools fit… Given a wealth of documents…

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Where our tools fit… Given a wealth of documents, and tools to detect and render potentially significant patterns…

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Where our tools fit… Given a wealth of documents, and tools to detect and render potentially significant patterns…

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Where our tools fit: making meaningful connections between information elements…

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Where our tools fit: making meaningful connections between interpretations

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interpretation

interpretation

interpretation

interpretation

Where our tools fit: making meaningful connections between interpretations

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interpretation

interpretation interpretation

interpretation

interpretation

(a hunch – no grounding

evidence yet)

interpretation

Where our tools fit: making meaningful connections between information elements

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predicts causes

interpretation

interpretation interpretation

interpretation

interpretation

(a hunch – no grounding

evidence yet)

interpretation

Is pre-requisite for

Where our tools fit: making meaningful connections between information elements

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prevents

predicts causes

interpretation

interpretation interpretation

interpretation

interpretation

(a hunch – no grounding

evidence yet) Is inconsistent with

interpretation

challenges

Is pre-requisite for

Where our tools fit: building the story that makes sense of the evidence… i.e. plausible arguments

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Question

Answer

Supporting Argument… Challenging

Argument…

challenges supports

responds to

Assumption

motivates

Where our tools fit: building the story that makes sense of the evidence… i.e. plausible arguments

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Question

Answer

Supporting Argument… Challenging

Argument…

challenges supports

responds to

Hunch

motivates

Where our tools fit: building the story that makes sense of the evidence… i.e. plausible arguments

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Question

Answer

Supporting Argument… Challenging

Argument…

challenges supports

responds to

Data

motivates

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http://cohere.open.ac.uk

Convergence of… web annotation social bookmarking concept mapping structured debate

a prototype infrastructure for collective intelligence/social learning

Structured deliberation and debate in which Questions, Evidence and Connections are first class entities (linkable, addressable, embeddable, contestable…)

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Structured deliberation and debate in which Questions, Evidence and Connections are first class entities (linkable, addressable, embeddable, contestable…)

— web annotation of OER (Firefox extension)

User/community-defined visual language

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Structured deliberation and debate in which Questions, Evidence and Connections are first class entities (linkable, addressable, embeddable, contestable…)

Social Network

Social Discourse Network

Concept Network

By looking at the post type table it is possible to evaluate learner’s performance connecting the discourse outcomes with the specific learning goal.

Cohere analytics

Legend:

Positive link type

Negative link type

Neutral link type

Cohere analytics

Comparing usage of connections

Comparison of one’s own ideas to others

De Liddo, A., Buckingham Shum, S., Quinto, I., Bachler, M. and Cannavacciuolo, L.(2011). Discourse-Centric Learning Analytics. Proc. 1st Int. Conf. Learning Analytics & Knowledge. Feb. 27-Mar 1, 2011, Banff

Does the learner compare his/her own ideas to that of peers, and if so, in what ways?

De Liddo, A., Buckingham Shum, S., Quinto, I., Bachler, M. and Cannavacciuolo, L.(2011). Discourse-Centric Learning Analytics. Proc. 1st Int. Conf. Learning Analytics & Knowledge. Feb. 27-Mar 1, 2011, Banff

Does the learner act as a broker, connecting the ideas of his/her peers, and if so, in what ways?

Link broker: connecting other people’s ideas

seeing the connections people make as they annotate the web using Cohere

Visualizing all the connections that a set of analysts have made

— but unfiltered, this may not be very helpful

Visualizing multiple learners’ interpretations of global

warming sources

Connections have been filtered by a set of semantic

relationships grouped as Consistency

— semantic filtering of connections

De Liddo, A. and Buckingham Shum, S. (2010). Cohere: A prototype for contested collective intelligence. In: ACM Computer Supported Cooperative Work (CSCW 2010) - Workshop: Collective Intelligence In Organizations, February 6-10, 2010, Savannah, Georgia, USA. http://oro.open.ac.uk/19554

— web annotation for sensemaking

http

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OLnet  is    searching  out  the  

evidence  for    effec4ve  OER,  and  building  an    Evidence  Hub    —  a  living    map    by,  of  and  for  

the  OER  movement  —  and  those  we  need  

to  impact  

!

Moving from document annotation to connection-making for sensemaking

Discourse analysis with Xerox Incremental Parser

BACKGROUND KNOWLEDGE:

Recent studies indicate …

… the previously proposed …

… is universally accepted ...

NOVELTY:

... new insights provide direct evidence ...

... we suggest a new ... approach ...

... results define a novel role ...

OPEN QUESTION: … little is known … … role … has been elusive Current data is insufficient …

GENERALIZING: ... emerging as a promising approach Our understanding ... has grown exponentially ... ... growing recognition of the importance ...

CONRASTING IDEAS: … unorthodox view resolves … paradoxes … In contrast with previous hypotheses ... ... inconsistent with past findings ...

SIGNIFICANCE: studies ... have provided important advances Knowledge ... is crucial for ... understanding valuable information ... from studies

SURPRISE: We have recently observed ... surprisingly We have identified ... unusual The recent discovery ... suggests intriguing roles

SUMMARIZING: The goal of this study ... Here, we show ... Altogether, our results ... indicate

Detection of salient sentences based on rhetorical markers:

Ágnes Sándor & OLnet Project: http://olnet.org/node/512

XIP annotation to Cohere

XIP annotations in Cohere’s Firefox Ideas sidebar

XIP annotations in Cohere’s Firefox Connections sidebar

XIP annotations visualized in Cohere (ack: prefuse)

XIP/Cohere integration: conclusions from analysis of the corpus (ack: Ágnes Sándor, XRCE)

§  Machine annotation can effectively draw attention to

key issues and contrasting ideas, in a cost effective and timely manner

§  Human annotation adds higher-level cognitive activities such as abstracting, contextualizing and summarizing.

An appropriate combination of both machine and human annotation can augment and enhance both human and machine analysis.

OpenEd Evidence Hub: ci.olnet.org an alpha release

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OpenEd Evidence Hub: ci.olnet.org an alpha release

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OpenEd Evidence Hub: ci.olnet.org an alpha release

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olnet.org

ci.olnet.org