Social Intelligence Systems for Wicked Problems

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Simon Buckingham Shum

Knowledge Media Institute Open University UK http://people.kmi.open.ac.uk/sbs

Towards a Science of Socially Intelligent ICT ASSYST Workshop, Imperial College London, 3 Aug. 2010. http://assystcomplexity.eu

http://creativecommons.org/licenses/by-nc/2.0/uk

What is ICT-enabled ‘Social Intelligence’?

Working hypothesis:

In the context of wicked problems (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 Social Intelligence Systems

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

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Relevant theories should explain (ideally predict…) when and why social intelligence fails or excels

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Breakdown in personal and/or social intelligence

Relevant theory?

Risk of entrained thinking from experts who fail to recognise a novel phenomenon

•  Weick and Snowdon’s work on organisational sensemaking in complexity

•  Cognitive science theories of expertise •  Group deliberation research

Breakdown in critical reasoning •  Informal logic and argumentation theory

Breakdown in ability to listen deeply to other stakeholders

•  Theory-U (Scharmer) •  Dialogue/Reconciliation (Isaacs; Kahane) •  Sensemaking for leadership in complex

challenges (Palus & Horth) Learners cannot adapt fast enough or work effectively together to cope with the complexity

•  Learning Power in schools and workplace (Deakin Crick, Claxton)

Inability to reliably predict based on past history •  Complexity science

Motivating requirements for a Social Intelligence System (people + technology + practices)

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Social Intelligence Phenomena Social Intelligence System? 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 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)

SI-System engineering principles? One approach is to design for resilience

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Resilience engineering principle Social Intelligence Infrastructure? build in the potential for diversity •  e.g. of worldviews, and the debates this sets

up

make tight feedback loops •  e.g. rapid awareness of dis/agreement amongst peers

promote building of trust/social capital •  e.g. through social networking and mutual support

enable experimentation •  e.g. in order to learn through practical action on the world, or simulations

use a decentralised, modular architecture •  e.g. enabling innovation, interoperability and mashups with diverse end-user tools/data

•  “Resilience platforms”: 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.

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Blog: www.open.ac.uk/sociallearn Demo: http://sociallearn.org

Site 2

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SocialLearn 1. Profile 2. User Interface 3. Social Graph 4. Services

Site 1

Interoperability via Google Gadgets

SocialLearn provides the ‘glue’ to connect learning activities, ‘friends’, coaches, and recommendations

Site 4 Site 3

…other sites…

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SocialLearn “dashboard” of gadgets

Embedding SocialLearn gadgets in a partner site (the OU’s Cloudworks)

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People Recommender

gadget

Cloud Recommender

gadget

Cloudstream Recommender

gadget

SocialLearn: accessing my Gadgets from the browser toolbar while browsing any website

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http://cohere.open.ac.uk

web annotation/discourse for sensemaking (A winner in the Mozilla/MacArthur Foundation

Jetpack for Learning Design Challenge)

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

- Toward a Research Agenda, February 6-10, 2010, Savannah, Georgia, USA. http://oro.open.ac.uk/19554

a prototype infrastructure for collective intelligence/social learning

— web annotation for sensemaking

12 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

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

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

Visualizing all the connections that a set of analysts have made between web resources

— but this may also be confusing

Visualizing multiple learners’ interpretations of

global warming sources

Connections have been filtered by a set of

semantic relationships grouped as Consistency

— semantic filter of argument map

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

“Semantic Google Scholar”: Query: What is the lineage of this idea?

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Buckingham Shum, S.J., Uren, V., Li, G., Sereno, B. and Mancini, C. (2007).Modelling Naturalistic Argumentation in Research Literatures: Representation and Interaction Design Issues. International Journal of Intelligent Systems, (Special Issue on Computational Models of Natural Argument, Eds: C. Reed and F. Grasso, 22, (1), pp.17-47. http://oro.open.ac.uk/6463

— geospatial mashup of ideas

Nodes in the semantic network containing

geolocation data can be visualized in Google Maps

— timeline viz. mashup of ideas

Nodes in the semantic network containing temporal data can be visualized in MIT

Simile’s timeline

In more detail… articles, books, news, movies, software, community…

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http://cohere.open.ac.uk

www.open.ac.uk/sociallearn

http://projects.kmi.open.ac.uk/hyperdiscourse