Thursday, June 17, 2010

Online labor markets, as an experimental lab

There are a growing number of online labor markets (for a description of a wide range, see Work the New Digital Sweatshops By Jonathan Zittrain).

A recent paper explores their use for conducting experiments: The Online Laboratory: Conducting Experiments in a Real Labor Market by John Horton, David Rand and Richard Zeckhauser . They suggest that Amazon's Mechanical Turk is a convenient venue to do experiments, with some natural advantages (e.g. it's possible to recruit large numbers of participants, who don't need to know they are in an experiment), in which adequate control is possible.

"Abstract: "Online labor markets have great potential as platforms for conducting experiments, as they provide immediate access to a large and diverse subject pool and allow researchers to conduct randomized controlled trials. We argue that online experiments can be just as valid – both internally and externally – as laboratory and field experiments, while requiring far less money and time to design and to conduct. In this paper, we first describe the benefits of conducting experiments in online labor markets; we then use one such market to replicate three classic experiments and confirm their results. We confirm that subjects (1) reverse decisions in response to how a decision-problem is framed, (2) have pro-social preferences (value payoffs to others positively), and (3) respond to priming by altering their choices. We also conduct a labor supply field experiment in which we confirm that workers have upward sloping labor supply curves. In addition to reporting these results, we discuss the unique threats to validity in an online setting and propose methods for coping with these threats. We also discuss the external validity of results from online domains and explain why online results can have external validity equal to or even better than that of traditional methods, depending on the research question. We conclude with our views on the potential role that online experiments can play within the social sciences, and then recommend software development priorities and best practices. "

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