1. Chapter 9: Tapping the Crowd for Fast Innovation ISTO SIPILÄ

2. Collective Intelligence  Other term crowdsourcing  Deriving data, knowledge and insight from large groups connected online  Many varieties of collective intelligence  Three approaches that use Open Data in different ways are examined in the book  Open innovation through collaboration (discussed in the next chapter)  The Match.com model  The Data Hive

3. The Match.com Model  Search for a small number of experts who have the right experience, skills and interests to solve a problem  Someone with a problem to solve or data to analyze try to reach as large crowd as possible to find the few right people  If you understand a problem well enough to publish it and you put the right inducements around the system then innovators from all over the world can work with it  Often new perspective and outside thinking is the key to identifying new patterns and correlations

4. Examples  InnoCentive: works with companies and organizations, runs contests, largely focused on science and technical problems, offers prizes ranging from 500 dollars to over a million  Kaggle: presents challenges for data scientists, predicted what level of IT access different employees would need based on their jobs  TopCoder: another community for data problems, worked with Harvard Medical School, solution to the tough gene-sequencing problem  Washington University: tried to understand the structure of a virus, released their data on the foldit.com site, solution in three weeks  Peer-to-Patent: commenting and studying patent applications  Stack Exchange (started as Stack Overflow), Wikipedia etc.

5. The Data Hive  Volunteers are doing routine work to analyze or improve Open Data  Each individual does small pieces of work that contribute to the solution  Model has been applied to government data and scientific data with some striking results  Sometimes untrained amateurs see important things that experts miss (Galaxy Zoo example)

6. Examples  NASA: invited people to help identify planetary systems in space telescope images  Zooniverse: an international hub where anyone can help solve large-scale scientific puzzles, over 800 000 people registered  Galaxy Zoo: participant looked at an image and said what type of galaxy it is or is it a star, an artifact or more than one galaxy  CrowdCrafting.org: Zooniverse kind of approach, presents a range of challenges in areas like basic science, linguistics and the analysis of social media  SkyTruth: uses the crowd to analyze Open Data in satellite images to keep a collective eye on the environmental impact of corporate activities

7. How to Make People to Participate  Mass data-hive projects that pay people to participate in dull routine tasks have had limited success  The nature of the task and the community engaged in it seems to determine dedication and performance  Research done to InnoCentive says there are three factors motivating problem solvers:  They want to take on projects that will have an impact  They want to be part of a group of elite problem solvers  They want whatever inducement is being offered, intrinsic reward or extrinsic rewards like money and recognition

8. Question What is the best way to motivate people to take part on collective mind projects?