A survey of incentive engineering for crowdsourcing. (17th April 2018)

• Record Type: Journal Article
• Authors: Muldoon, Conor; O'Grady, Michael J.; O'Hare, Gregory M. P.
• Is Part Of: Knowledge engineering review. Volume 33(2018)
• Publication Date: 2018-04-17
• Subjects: Expert systems (Computer science) -- Periodicals; 006.33
• DOI: 10.1017/S0269888918000061
• Languages: English
• ISSNs: 0269-8889

Abstract

Abstract: With the growth of the Internet, crowdsourcing has become a popular way to perform intelligence tasks that hitherto would be either performed internally within an organization or not undertaken due to prohibitive costs and the lack of an appropriate communications infrastructure. In crowdsourcing systems, whereby multiple agents are not under the direct control of a system designer, it cannot be assumed that agents will act in a manner that is consistent with the objectives of the system designer or principal agent. In situations whereby agents' goals are to maximize their return in crowdsourcing systems that offer financial or other rewards, strategies will be adopted by agents to game the system if appropriate mitigating measures are not put in place. The motivational and incentivization research space is quite large; it incorporates diverse techniques from a variety of different disciplines including behavioural economics, incentive theory, and game theory. This paper specifically focusses on game theoretic approaches to the problem in the crowdsourcing domain and places it in the context of the wider research landscape. It provides a survey of incentive engineering techniques that enable the creation of apt incentive structures in a range of different scenarios.