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Towards a Science of Socially Intelligent ICTASSYST Project WorkshopImperial College London, 3 Aug. 2010. http://assystcomplexity.eu
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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