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

被引：0

作者：

Bontempi, Gianluca ^{[1
]}

Chavarriaga, Ricardo ^{[2
]}

Ed Canck, Hans ^{[3
]}

Girardi, Emanuela ^{[4
]}

Hoos, Holger ^{[5
,6
]}

Kilbane-Dawe, Iarla ^{[7
]}

Ball, Tonio ^{[8
]}

Nowe, Ann ^{[9
]}

Sousa, Jose ^{[10
]}

Bacciu, Davide ^{[11
]}

Aldinucci, Marco ^{[12
]}

Ed Domenico, Manlio ^{[13
]}

Saffiotti, Alessandro ^{[14
]}

Maratea, Marco ^{[15
]}

机构：

[1] Univ Libre Bruxelles, Machine Learning Grp, Comp Sci Dept, Brussels, Belgium

[2] Zurich Univ Appl Sci ZHAW, IEEE Brain Initiat, Geneva Ctr Secur Policy GCSP, CLAIRE Off Switzerland, Winterthur, Switzerland

[3] Vrije Univ Brussel, AI Experience Ctr, AI Common Good Initiat, CLAIRE Off Belgium, Ixelles, Belgium

[4] Pop AI, Turin, Italy

[5] Leiden Univ, Leiden Inst Adv Comp Sci LIACS, Leiden, Netherlands

[6] Univ British Columbia, Vancouver, BC, Canada

[7] Parliament Hill Res Ltd, London, England

[8] Neuromed AI Lab Freiburg, Freiburg, Germany

[9] Vrije Univ Brussel, AI Lab, Brussels, Belgium

[10] Queens Univ Belfast, Fac Med Hlth & Life Sci, Belfast, Antrim, North Ireland

[11] Univ Pisa, Computat Intelligence & Machine Learning Grp, Pisa, Italy

[12] Univ Torino, Comp Sci Dept, Turin, Italy

[13] FBK Fdn Bruno Kessler, Complex Multilayer Networks Lab, Kessler, Italy

[14] Orebro Univ, Sch Sci & Technol, AASS Cognit Robot Syst Lab, Orebro, Sweden

[15] Univ Genoa, Dipartimento Informat, Bioingn, Robot Ingn Sistemi, Genoa, Italy

来源：

ETHICS AND INFORMATION TECHNOLOGY | 2021年 / 23卷 / SUPPL 1期

关键词：

Artificial intelligence; COVID-19; Emergency response;

D O I：

10.1007/s10676-020-09567-7

中图分类号：

B82 [伦理学（道德学）];

学科分类号：

摘要：

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.

引用

页码：127 / 133

页数：7

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Ricardo Chavarriaga
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Holger Hoos
Iarla Kilbane-Dawe
Tonio Ball
Ann Nowé
Jose Sousa
Davide Bacciu
Marco Aldinucci
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Alessandro Saffiotti
Marco Maratea
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