Talent-Spotting in Online Deliberative Crowdsourcing Initiative

Case of Afghanistan’s first ever Internet-based Idea Competition on Solid Waste Management

抄録

This paper focuses on the problem of managing crowdsourced deliberation, with the aim of partitioning deliberation among a set of moderated democratic techniques over multiple sessions of deliberation in idea contest. Specifically, we propose that large-scale deliberation should be separately performed over multiple sessions such that (1) large-scale deliberation should be done by machine agency first, (2) then human expert should manage over the course of medium-scale deliberation, and finally (3) the crowd should be allowed to perform the small-scale deliberation. We first provide an overview of the hybrid deliberative initiative that is being used to facilitate deliberation in a real-world idea contest. Next, we conduct an actual idea contest in collaboration with a governing agency to compare the efficacy of each deliberation technique in managing the contest.The contested generated 14,587 opinions from 3,892 registered participants, were collected in 2020 by internet forum over three sessions, which manage by machine ranking, human expert rating and crowd voting tools, respectively. Our results demonstrate that our initiative manages meaningful deliberation in the civic process. Finally, we discuss the advantages of our initiative over previous approaches and advocate for governing agencies of idea contests to adopt our initiative for future large-scale idea contests.