The CLAIRE COVID-19 initiative: approach, experiences and recommendations

Gianluca Bontempi; Ricardo Chavarriaga; Hans eD Canck; Emanuela Girardi; Holger Hoos; Iarla Kilbane-Dawe; Tonio Ball; Ann Nowé; Jose Sousa; Davide Bacciu; Marco Aldinucci; Manlio eD Domenico; Alessandro Saffiotti; Marco Maratea

doi:10.1007/s10676-020-09567-7

The CLAIRE COVID-19 initiative: approach, experiences and recommendations

Ethics Inf Technol. 2021;23(Suppl 1):127-133. doi: 10.1007/s10676-020-09567-7. Epub 2021 Feb 9.

Authors

Affiliations

¹ Computer Science Department, Machine Learning Group, Université Libre de Bruxelles, Bruxelles, Belgium.
² CLAIRE Office Switzerland, Geneva Center for Security Policy (GCSP), IEEE Brain Initiative, Zurich University of Applied Sciences (ZHAW), Winterthur, Switzerland.
³ CLAIRE Office Belgium, Vrije Universiteit Brussel, AI Experience Center / AI for the Common Good Initiative, Ixelles, Belgium.
⁴ Pop AI, Torino, Italy.
⁵ Leiden Institute of Advanced Computer Science (LIACS), Universiteit Leiden, The Netherlands and University of British Columbia, Vancouver, Canada.
⁶ Parliament Hill Research Ltd, London, UK.
⁷ Neuromedical AI Lab Freiburg, Freiburg, Germany.
⁸ AI Lab, Vrije Universiteit Brussel, Brussel, Belgium.
⁹ Faculty of Medicine, Health and Life Sciences, Queen's University Belfast, Belfast, UK.
¹⁰ Computational Intelligence and Machine Learning Group, Universita'di Pisa, Pisa, Italy.
¹¹ Computer Science Department, University of Torino, Torino, Italy.
¹² Complex Multilayer Networks Lab, FBK - Fondazione Bruno Kessler, Kessler, Italy.
¹³ AASS Cognitive Robotic Systems Lab, School of Science and Technology, Orebro University, Orebro, Sweden.
¹⁴ Dipartimento Di Informatica, Bioingegneria, Roboticae Ingegneria Dei Sistemi. University Genova, Genova, Italy.

Abstract

A volunteer effort by Artificial Intelligence (AI) researchers has shown it can deliver significant research outcomes rapidly to help tackle COVID-19. Within two months, CLAIRE's self-organising volunteers delivered the World's first comprehensive curated repository of COVID-19-related datasets useful for drug-repurposing, drafted review papers on the role CT/X-ray scan analysis and robotics could play, and progressed research in other areas. Given the pace required and nature of voluntary efforts, the teams faced a number of challenges. These offer insights in how better to prepare for future volunteer scientific efforts and large scale, data-dependent AI collaborations in general. We offer seven recommendations on how to best leverage such efforts and collaborations in the context of managing future crises.

Keywords: Artificial intelligence; COVID-19; Emergency response.