Social Choice for Human Computation

Mao, Andrew (Harvard University) | Procaccia, Ariel D. (Carnegie Mellon University) | Chen, Yiling (Harvard University)

AAAI Conferences 

A natural, common way of doing this is by crowdsourcing this stage as well, and specifically Human computation is a fast-growing field that seeks to harness letting people vote over different proposals that were the relative strengths of humans to solve problems that submitted by their peers. For example, in EteRNA thousands are difficult for computers to solve alone. The field has recently of designs are submitted each month, but only a small number been gaining traction within the AI community, as k of them can be synthesized in the lab (as of late 2011, increasingly more deep connections between AI and human k 8). To single out k designs to be synthesized, players computation are uncovered (Dai, Mausam, and Weld 2010; vote by reporting their k favorite designs, each of which is Shahaf and Horvitz 2010).

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