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Massively Collaborative Problem Solving

Posted on November 11th, 2015

UX + Data

11/11/2015 @Pivotal Labs, 625 6th Ave, NY

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Matt Weber @zoomdata started by describing how simple rules can create complex, interesting systems

  1. #Conway’s game of life – simple rule
  2. The #Delphi Method (Rand Corporation) – collaboration

He next described his use of #Amazon Turk in 2009 to obtain interesting answers to complex problems. His example was a question asking for ways to make the U.S. energy self-sufficient. He used

Simple rules + iterative collaboration = massively #collaborative #ProblemSolving

Answers were selected using three simple tasks

  1. Create –each worker creates a list of 7 proposals – repeated by 50 workers
  2. Rate – Each proposal was rated on a 1-10 scale – done by 20 workers
  3. Atomize – take the 7 proposals with the highest aggregate score. Of the 7 proposals ask which need more details – ask 50 workers

This person proposed 7 as the maximum number of items that can be kept in working memory. Answer: Who is George A. Miller in his paper the Magical number seven plus or minus two?

End of round one.

  1. Take the top proposals and ask another set of workers to make a plan of action for this proposal
  2. 20 workers rate the subproposals on a 1-10 scale
  3. Select the top sub-proposals

Repeat for each of the top tasks

Matt then displayed the answers and commented on how many proposals were reasonable and well-thought-out

He next talked about design considerations when determining what problems could be successfully addressed by this method. The main consideration is to pick a general topic and let the crowd guide the process. The problem should be of general interest and be framed so it is

  1. Human readable – also can be handled by computers
  2. Short text – can be written and consumed fast
  3. Hierarchical
  4. Keep it relevant and passionate – people need to be involved

The problem needs to be encapsulated so it is bite-size and does not need a context.

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