Learning and Incentives in Crowd-Powered Systems

  • Adish Singla | ETH Zurich

There is large potential in designing intelligent and self-sustainable crowd-powered systems that incentivize and empower their users to actively engage them in the system processes. This talk explores various research questions at the interplay of learning and incentives, with the goal of improving the overall effectiveness of such systems. In this talk, we focus on a unique crowd-powered system based on bike sharing. We discuss the challenges faced by the operators of the bike sharing systems from fluctuating and unpredictable demands, leading to imbalance problems such as unavailability of bikes or parking docks at stations. We present a crowdsourcing mechanism that incentivizes the users in the bike repositioning process by providing them with alternate choices for pick up or return of bikes in exchange for monetary incentives. We deployed the proposed mechanism through a smartphone app among users of a large-scale bike sharing system operated by a public transport company in a city of Europe, and we present results from this experimental deployment.

Series: Microsoft Research Talks