Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: The CLAIRE COVID-19 initiative : approach, experiences and recommendations
Authors: Bontempi, Gianluca
Chavarriaga, Ricardo
De Canck, Hans
Girardi, Emanuela
Hoos, Holger
Kilbane-Dawe, Iarla
Ball, Tonio
Nowé, Ann
Sousa, Jose
Bacciu, Davide
Aldinucci, Marco
De Domenico, Manlio
Saffiotti, Alessandro
Maratea, Marco
et. al: No
DOI: 10.1007/s10676-020-09567-7
Published in: Ethics and Information Technology
Issue Date: 9-Feb-2021
Publisher / Ed. Institution: Springer
ISSN: 1388-1957
1572-8439
Language: English
Subjects: Artificial intelligence; Covid-19; Data sharing
Subject (DDC): 000: Generalities and science
006: Special computer methods
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.
URI: https://rdcu.be/cfcKw
https://digitalcollection.zhaw.ch/handle/11475/21990
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Centre for Artificial Intelligence (CAI)
Institute of Applied Information Technology (InIT)
Appears in collections:Publikationen School of Engineering

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