Abstract

Harnessing human computation through crowdsourcing offers a new approach to solving complex problems, especially those that are easy for humans but difficult for computers. Micro-tasking platforms such as Amazon Mechanical Turk have attracted a large on-demand workforce of millions of workers as well as hundreds of thousands of requesters. Achieving high quality results and minimizing the total task execution times are the two main goals of these crowdsourcing systems. In this paper we study the effects of cognitive load and complexity of user interface design on work quality and the latency of system. Our results indicate that complex and poorly designed user interfaces contributed to lower worker performance and increased latency.

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