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Game Structured Hiveminds: Organizing People & Solving Problems with Fun
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Description

Game Structured Hiveminds: Organizing People & Solving Problems with Fun

Speaker/s: Ben Sawyer (Digitalmill), Jerome Waldispuhl (McGill University), Evan Brown (Entertainment Technology Center) and Joe Edelman (Citizen Logistics)
Day / Time / Location: Monday 10:00-11:00 Room 2009, West Hall, 2nd Fl
Track / Duration / Format / Audience Level: Game IT Summit / 60-Minute / Lecture / All
GDC Vault Recording: Video Recorded
Description: The opening set of talks at Game IT focuses on the ability for games to help solve problems through organizing and engaging collaborative groups of people through gameplay and social networks. The opportunities happening here are still emergent but already several projects have exemplified the power of this opportunity. This set of talks seeks to further these discussions and offer exciting new ideas to game-based crowdsourcing, collaboration, and distributed activity and problem solving.

Phylo, a McGill University based project creating a human-based computing framework applying ``crowd sourcing'' techniques and casual style gameplay to help with comparison of the human genome with the DNA of other species essential to deciphering our genetic code and revealing the causes of various genetic disorders.

CEML (Coordinating Event Module Launguage) an innovative new scripting language for coordinating group dynamics, and civic logistics across multiple platforms and applications. Developed by Citizen's Logistics CEML can be used to create exciting new blends of human action and game interaction.

Project Augur, developed by students at Carnegie Melon University's Entertainment Technology Center for Lockheed Martin Corporation. Project Augur's goal was to explore the frontiers of artificial intelligence as a predictive mechanism. Through the use of crowd-sourcing through Amazon Mechanical Turk, and with a trio of gamelike prototypes that collect data, the team built artificial intelligence algorithms that can predict based not only on an individual's past play, but other, less obvious factors as well.
Takeaway: Attendees to this talk will see three excellent and different, examples of how games can be used to create innovative crowdsourcing solutions to complex problems best solved by humans and not machines.

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