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- Vol 6 RE: Chapter 12, App A, App D, App E
collective intelligencedistributed problem solvingcrowdsourcingopen innovationparticipatory motivationcoordination mechanismsprediction marketscollective-intelligence designJournal article Evidence summaryAt a glance
Malone, Laubacher, and Dellarocas offer a design framework for understanding Internet-enabled collective intelligence: groups of people and computers acting together in ways that appear intelligent. From a study of more than 250 examples, they organise systems around four questions—what is being accomplished, who performs the work, why participants contribute, and how contributions are coordinated.
Key ideas
The possible answers become “genes” that can be recombined into a collective-intelligence genome. Goals commonly involve creating something or deciding among alternatives; contributors may come from a hierarchy or a crowd; motivation may include money, enjoyment, or reputation; and coordination may rely on independent work, collaboration, voting, averaging, markets, or contests. Cases such as Wikipedia, Google, prediction markets, and open innovation illustrate different combinations. The framework is primarily a practical taxonomy rather than an experimental test.
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It helps designers compare existing systems and deliberately construct new forms of distributed problem solving.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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