Winter Milestone 4 PierreF

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Exploration of CrowSourcing Dynamics with Soclal Experimentations

CrowdSourcing platforms represent a new dimension in the workspace. While initially deemed as a way to hide the human component in automated workflows, this position has quickly shown its limits. Human relationships have rapidly resurfaced to play an essential role for the global efficiency of existing systems.

Finding a middle-ground between task providers or requesters and workers appear a necessary objective to maintain a lively market where both population can satisfactorily fulfill their respective objectives.

Current playground is heavily unbalanced in the advantages of requesters. Existing platforms put them in control of the dynamics of the major economic factors, namely prices and reputations. This situation is heavily resented by the worker population. A possible evolution leads to ultimate long-term demise of this kind of platforms due to loss of quality in the average task completion resulting from the departure of the more motivated and skilled workforce.

The background of crowdsourcing in game theory terms has already been set up by other authors:

  • Game Theory and Incentives in Human Computation Systems, Arpita Ghosh. Book chapter. Handbook of Human Computation, Springer 2013. [1]
  • Behavioral Mechanism Design: Optimal Crowdsourcing Contracts and Prospect Theory. David Easley, Arpita Ghosh. Proc. 16th ACM Conference on Economics and Computation (EC), 2015. [2]

Large scale social experiments have been conducted to discover best ways to manage financial incentives to optimally engage a crowd of participants.

  • Galen Pickard, Wei Pan, Iyad Rahwan, Manuel Cebrian, Riley Crane, Anmol Madan, and Alex Pentland. Time-critical social mobilization. Science, 334:509–512, 2011. [3]

This paper intends to describe the practical exploration of game theory concepts in crowdsourcing through experiments. These experiments involve the introduction of new mechanisms in the environment of an experimental crowdsourcing platforms. We intend to explore the feasibility of satisfactory emergence of Nash equilibria due to the introduction of such mechanisms leading to a more harmonious field of play.

Experimentations address in particular the introduction of guild organization concept and giving the capacity to workers to adopt different forms of self-governance using in-platform tools. Of particular importance is the repetition of interactions involving the same population to understanding the dynamics and the reactions of requesters and players in the long runs. Three major metrics will be tracked in this evolution:

  • engagement in the platform (participants can decide to quit and not participate anymore)
  • price evolution on a range of task types
  • reputation evolution according to worker attitude and requester attitude.

The workers and requesters are briefed to adopt stylized behaviour. For requesters:

  • Lenient
  • Fair and communicative
  • Judgemental

For workers:

  • Competent and efficient
  • Motivated but unskilled
  • Slow
  • Lazy and negligent

On top of that, guilds of different sizes will be tested as well a control group of people staying alone.



This contribution has benefited a lot from the discussions in the hangout organized by @trygve So thank you to : @trygve @dilrukshi @m.kambal