Collective Intelligence is defined very broadly as groups of individuals doing things collectively that seem intelligent. Identifying classifications and examples of crowdsourcing.

1. What is Collective Intelligence?

2. Collective Intelligence Is defined very broadly as groups of individuals doing things collectively that seem intelligent.

3. Collective Intelligence Consists of families, companies, countries, and armies… All are groups of individuals doing things collectively that, at least sometimes, seem intelligent.

4. Collective Intelligence on the Internet Crowds have done certain intelligent things, like voting in elections, for a long time, However, low cost electronic communication enabled by the Internet now makes it feasible for crowds to do many more things than ever before.

5. Internet enabled CI Common examples of Internet enabled Collective Intelligence (CI) Google Wikipedia Threadless

6. Google CI Harnesses collective knowledge of the entire Web Takes judgments made by millions of people as they create links to Web pages Produces intelligent answers to questions typed into the Google search bar.

7. Wikipedia CI World’s largest encyclopedia with high quality articles created collectively by thousands worldwide Almostno centralized control. Anyonewho wants to can change almost anything Decisions about what changes to keep are made by a loose consensus of volunteerswho care.

8. Threadless CI Anyone can design a T-shirt submit design to a weekly contest vote for favorite designs. Company selects winning designs from most popular entries puts them into production gives prizes and royalties to winning designers. over 500,000 people design and select T-shirts.

9. How does CI work? Who is performing the task? Why are they doing it? Why do people take part in the activity? What motivates them to participate? What incentives are at work? What is being accomplished? How is it being done?

10. Who contributes to CI tasks? Anyone who chooses to do so can participate without being assigned by someone in a position of authority. Anyone who wants to can submit a module for possible inclusion in Linux. Anyone can create a link to a Web page, and each new link becomes part of the database Google uses to serve up answers to searches. Anyone can propose a new article or edit an existing article in Wikipedia. Anyone can submit a T-shirt design to Threadless or vote on the designs that are submitted.

11. Why participate/contribute to CI? Money Love Glory Avoidance

12. Why participate/contribute to CI? Money Financial gain in direct payments, salary increased likelihood of future earning enhance professional reputation improve skills

13. Why participate/contribute to CI? Love intrinsic enjoyment of an activity opportunities to socialize with others Desire to contribute to a cause larger than themselves Studies of Wikipedia have shown that its participants are motivated by all three of these Love variants

14. Why participate/contribute to CI? Glory recognition from peers Programmers in open source software communities “power seller” on eBay “top reviewer” on Amazon

15. Why participate/contribute to CI? Avoidance Distraction Procrastination Boredom Contributing to online collective intelligence can be stress relieving by distracting one from focusing on accomplishing other things they prefer to avoid

16. What is being done by CI? Create Decide

17. What is being done by CI? Create: Generate something new piece of software code, blog entry, T-shirt design.

18. What is being done by CI? Decide evaluate and select alternatives; whether a new module should be included in the next release of Linux, which T-shirt design to manufacture, whether to delete a Wikipedia article.

19. How is CI being done? Create Collection Contests Collaboration Decide Individual Decisions Group Decisions

20. How is CI being done? Collection items contributed by members of the crowd are created independently of each other YouTube videos are created mostly independently of each other Digg, a collection of news stories Flickr, a collection of photographs

21. How is CI being done? Collection  Contests one or several items in the collection are designated as the best entries and receive a prize or other form of recognition. (Threadless) Large amount of money rewarded to team solving problem, providing better solution after an extended period of time

22. Contests Examples of large money over long time: InnoCentive Netflix IBM’s Innovation Jams TopCoder

23. Contests InnoCentive companies offer cash rewards, typically totaling in the five or even six figures, to researchers anywhere in the world who can solve challenging scientific problems such as how to synthesize a particular chemical compound.

24. Contests Netflix Prize $1 million award given for first algorithm that is at least 10 percent better than the one used by Netflix for suggesting to customers which DVDs they will like.

25. Contests IBM’s Innovation Jams IBM employees, customers and vendors participate in on-line brainstorming sessions to develop ideas for new products and services. Participants and managers then rate ideas that emerge total of $100 million in seed funding is divided up each year among the top ten concepts.

26. Contests TopCoder independent computer programmers compete to provide the best solutions to customers’ problems

27. Collaboration members of a Crowd work together to create something, and important dependencies exist between their contributions.

28. Collaboration Wikipedia as a whole is a Collection of articles each individual Wikipedia article is a collaboration, comprised of contributions submitted by a number of users. additions and editorial changes made by different contributors within a single Wikipedia article are strongly interdependent.

29. Collaboration Open Source Software Projects Linux, and any other open source software project, require strong interdependencies among the modules submitted by different contributors.

30. How is CI being done? Group Decision members of the crowd are assembled to generate a decision that holds for the group as a whole.

31. Group Decisions Voting Implicit Weighted Consensus Averaging Prediction Markets

32. Group Decisions: Voting Diggusers vote on which news stories are most interesting winning stories displayed prominently on the website. EbbsfleetUnited, a U.K. soccer team, owned by 30,000 members vote over the Internet on issues such as which players should be traded and which should play. Kasparov v. the World, a chess match held in 1999 world champion Gary Kasparov played against “the World,” the World’s moves were determined by majority vote over the Internet of anyone who wanted to participate. Kasparov eventually won, but he said it was the hardest game he ever played.

33. Implicit Voting actions like buying or viewing items are counted as implicit “votes.” iStockPhoto displays photos in order of the number of times each photo has been downloaded YouTube ranks videos by the number of times they have been viewed.

34. Weighted Voting Google ranks search results, in part, on the basis of how many other sites link to the sites in the list. But Google’s algorithm gives more weight to links from sites that are, themselves, more popular.

35. Group Decisions: Consensus all, or essentially all, group members agree on the final decision. Examples Wikipedia reCAPTCHA

36. Consensus: Wikipedia Wikipedia uses consensus to make editing decisions: articles remain unchanged when everyone who cares is satisfied with the current version.

37. Consensus: reCAPTCHA reCAPTCHA, a Web security utility, deems words correctly transcribed by consensus Two words are displayed on the screen, with users required to type both to gain access to a Web page. One word is a security key /other word previously scanned as part of a project to digitize old books. Words that optical character recognition software finds difficult to read are served up to multiple users. Only after transcriptions provided by multiple users reach a level of consensus, as determined by a statistical algorithm, is that word deemed to have been correctly transcribed.

38. Group Decisions: Averaging Numbers contributed by the members of the Crowd are averaged. Averaging is commonly used in systems that rely on a point scale for quality rating.

39. Group Decisions: Averaging Example: users of Amazon rate books or CDs on a five star scale, ratings are averaged to provide an overall score for each item. users of Expedia rate hotels users of Internet Movie Database rate movies Marketocracy runs an investment portfolio selected by averaging stocks and bonds chosen by the 100 most successful investors from over 55,000 who participate on the website.

40. Group Decisions: Prediction Markets crowds estimate the probability of future events people buy and sell “shares” of predictions about future events. If their predictions are correct, they are rewarded, either with real money or with points that can be redeemed for cash or prizes.

41. Group Decisions: Prediction Markets Decision consists of estimating a number Crowd has some information about estimating the number (biases and non-independent information are okay) Some people may have (or obtain) much better information than others Continuously updated estimates are useful

42. Group Decisions: Prediction Markets Google, Microsoft, and Best Buy have all used prediction markets to tap the collective intelligence of people within their organizations.

43. Individual Decisions Members of a Crowd make decisions that, though informed by crowd input, do not need to be identical for all. Example: individual YouTube users decide for themselves which videos to watch. may be influenced by recommendations or rankings from others, not required to watch the same videos as others.

44. Individual Decisions: Market Some kind of formal exchange (like money) is involved in the decisions. Each member of the crowd makes an individual decision about what products to buy or sell. Purchasing decisions determine collective demand, which, for its part affects the availability of products and their prices. Quantities and prices of the goods put up for sale by sellers in the crowd influence, but do not bind, purchasing decisions.

45. Individual Decisions: Market Markets for many kinds of goods and services have existed for millennia, but new technologies will enable new electronic forms of markets.

46. Individual Decisions: Market Examples: iStockPhoto photographers post their photos for sale on a website editors and others buy the rights to use photos they want. eBay sellers post items they want to sell buyers bid for them.

47. Individual Decisions: Social Networks Members of a crowd form network of relationships that, depending on the context, might translate into levels of trust, similarity of taste and viewpoints, other common characteristics that might cause individuals to feel an affinity for one another

48. Individual Decisions: Social Networks Crowd members Assign different weights to individual inputs Based on their relationship with the people who provided them Make individual decisions.

49. Individual Decisions: Social Networks Examples: YouTube Epinions.com

50. Individual Decisions: Social Networks Examples: YouTube: Every user associated with a “channel.” Users upload their own videos and/or link to selections of other users’ videos, via a favorites option on channels Users can subscribe to other users’ channels and receive notifications when their favorite channels have been updated. Users thus form social networks that affect their choices of what videos to watch.

51. Individual Decisions: Social Networks Epinions.com, product review site, users form trust networks with other reviewers. Empirical evidence suggests that users weigh reviews written by members of their trust network more heavily than other reviews, leads to personalized assessments of individual product quality.

52. Thank you to MIT Center for Collective Intelligence Massachusetts Institute of Technology Cambridge, MA Harnessing Crowds: Mapping the Genome of Collective Intelligence by Thomas W. Malone, Robert Laubacher, and ChrysanthosDellarocas