Crowd Research: Open and Scalable University Laboratories

Rajan Vaish , Snehalkumar 'Neil' S. Gaikwad , Geza Kovacs1 , Andreas Veit , Ranjay Krishna, Imanol Arrieta Ibarra , Camelia Simoiu , Michael Wilber , Serge Belongie , Sharad Goel , James Davis , Michael S. Bernstein


Research experiences today are limited to a privileged few at select universities. Providing open access to research experiences would enable global upward mobility and increased diversity in the scientific workforce. How can we coordinate a crowd of diverse volunteers on open-ended research? How could a PI have enough visibility into each person’s contributions to recommend them for further study? We present Crowd Research, a crowdsourcing technique that coordinates open-ended research through an iterative cycle of open contribution, synchronous collaboration, and peer assessment. To aid upward mobility and recognize contributions in publications, we introduce a decentralized credit system: participants allocate credits to each other, which a graph centrality algorithm translates into a collectively-created author order. Over 1,500 people from 62 countries have participated, 74% from institutions with low access to research. Over two years and three projects, this crowd has produced articles at top-tier Computer Science venues, and participants have gone on to leading graduate programs.

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