KCB201 Week 12 Lecture: Knowledge Structures and Collective Intelligence
Download as PPT, PDF2 likes224 views
This document discusses knowledge representation on Wikipedia and the balance needed between community participation and diversity. It also examines the roles of experts versus general participants ("folks") and how expertise can be acknowledged. Different methods are presented for evaluating contributions and highlighting expertise in collaborative knowledge systems, with challenges around reliability and gaming the system. The document concludes by discussing Pierre Lévy's vision of collective intelligence through iterative finding, evaluating and sharing of information, and how the intelligence of such collective systems depends on protections against disruption and the skills/capacities of participants.
![Knowledge Structures and Collective Intelligence Dr Axel Bruns KCB201 Virtual Cultures [email_address]](https://image.slidesharecdn.com/week-12-lecture-1211416481907232-8/85/KCB201-Week-12-Lecture-Knowledge-Structures-and-Collective-Intelligence-1-320.jpg)
KCB201 Week 12 Lecture: Knowledge Structures and Collective Intelligence
- 1. Knowledge Structures and Collective Intelligence Dr Axel Bruns KCB201 Virtual Cultures [email_address]
- 2. Wikipedia Representations of knowledge: Wikipedia is a system (or process) for negotiating how knowledge is represented negotiation through discussion pages, repeated edits, conflict resolution, etc. guided by key principles: NPOV, verifiability, no original research Wikipedia ’s content quality is only as good as that system of negotiation see Stephen Colbert on ‘ Wikiality ’ , ‘ Wikilobbying ’ Potential problems: user community not diverse enough groupthink – only ‘commonsense’ content represented user community too diverse not enough common ground – in-fighting and lack of mutual respect too much power in the hands of admins able to influence content – hierarchical control of produsage processes too little power in the hands of admins unable to resolve conflicts between users – disruption of produsage processes Fine balance between community and diversity, organisation and participation also applies to many other produsage projects (social bookmarking, citizen journalism, etc.)
- 3. Folks and Experts Conflicting needs: encourage participation but manage diversity encourage debate but manage disputes What about experts: special role for experts – but how special? when is ‘common sense’ problematic? what defines ‘expertise’, where are its limits? what if experts don’t agree? do experts always trump ‘folks’? Need for collaboration between both: reality check for experts, produsage of new ideas knowledge in areas not covered by expertise we’re all experts on something Heterarchy of participation: experts above, folks below waterline – and crossover possible image by greenpeace.italia
- 4. Highlighting Expertise Communal evaluation: key principle of produsage processes through explicit ratings or implicit approval also affects contributors – who gain or lose status in the community acknowledging existing experts, or rewarding emerging experts combination of social and technological solutions Possibilities: manual evaluation and rating – e.g. German Wikipedia automated evaluation – e.g. Wikipedia trust colouring demo ratings for authors – e.g. Slashdot karma scores portable ratings across sites and platforms – but also problems with this global quality / importance / ‘interestingness’ ratings – e.g. Google PageRank but how reliable are any of these? can they be ‘gamed’?
- 5. Towards Collective Intelligence Pierre L é vy: “ This new human dimension of communication should obviously enable us to share our knowledge and acknowledge it to others, which is the fundamental condition for collective intelligence. Beyond this are two major possibilities, which could radically transform the fundamental data of social life. First, we will have at our disposal simple and practical means for knowing what we are doing as a group. Second, we will be able to manipulate, much more easily than we are able to write, the instruments for collective utterance.” ( Collective Intelligence , p. xxviii) Key processes: finding evaluating sharing ( finding evaluating sharing …) information communication collective intelligence How intelligent will this collective intelligence be? depends on protections against disruption – technological barriers and social protocols depends on participants’ enthusiasm, and their skills, literacies, and capacities if we think collective intelligence is worth supporting, we need to contribute and be vigilant