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A time-critical crowdsourced computational search for the origins of COVID-19

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To the Editor — On 26 May, President Joe Biden called on the US Intelligence Community to redouble efforts to collect and analyse information on the origins of coronavirus disease… Click to show full abstract

To the Editor — On 26 May, President Joe Biden called on the US Intelligence Community to redouble efforts to collect and analyse information on the origins of coronavirus disease 2019 (COVID-19), and report back to him in 90 days. After more than 18 months of intensive global investigations, the deadline will put pressure on a task that is proving to be substantially more challenging to solve than the origins of other threats1. I want to offer some technical considerations on the vast — but not insurmountable — complexity of the task ahead. My advice builds on a decade of experience leading teams that participated in2, designed3 and analysed4 challenges involving the time-critical search for hard-to-find information entities. I also borrow insights from my field of study, network science, which has tackled the theoretical5 and empirical6,7 aspects of searching for rare information spreading on a network. A successful investigation will, I believe, benefit from implementing five principles: incentive structures, transparency, unbiased search, crowdsourcing and human–machine computational sense-making.

Keywords: search; time critical; critical crowdsourced; computational search; crowdsourced computational

Journal Title: Nature Electronics
Year Published: 2021

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