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Artificial intelligence vs COVID-19: limitations, constraints and pitfalls.
AI Soc. 2020 Apr 28 [Online ahead of print]AS

Abstract

This paper provides an early evaluation of Artificial Intelligence (AI) against COVID-19. The main areas where AI can contribute to the fight against COVID-19 are discussed. It is concluded that AI has not yet been impactful against COVID-19. Its use is hampered by a lack of data, and by too much data. Overcoming these constraints will require a careful balance between data privacy and public health, and rigorous human-AI interaction. It is unlikely that these will be addressed in time to be of much help during the present pandemic. In the meantime, extensive gathering of diagnostic data on who is infectious will be essential to save lives, train AI, and limit economic damages.

Authors+Show Affiliations

Technology, Innovation, Entrepreneurship and Marketing, RWTH Aachen University, Kackertstrasse 7, 52072 Aachen, Germany.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32346223

Citation

Naudé, Wim. "Artificial Intelligence Vs COVID-19: Limitations, Constraints and Pitfalls." AI & Society, 2020, pp. 1-5.
Naudé W. Artificial intelligence vs COVID-19: limitations, constraints and pitfalls. AI Soc. 2020.
Naudé, W. (2020). Artificial intelligence vs COVID-19: limitations, constraints and pitfalls. AI & Society, 1-5. https://doi.org/10.1007/s00146-020-00978-0
Naudé W. Artificial Intelligence Vs COVID-19: Limitations, Constraints and Pitfalls. AI Soc. 2020 Apr 28;1-5. PubMed PMID: 32346223.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Artificial intelligence vs COVID-19: limitations, constraints and pitfalls. A1 - Naudé,Wim, Y1 - 2020/04/28/ PY - 2020/04/01/received PY - 2020/04/03/accepted PY - 2020/4/30/entrez PY - 2020/4/30/pubmed PY - 2020/4/30/medline KW - AI KW - COVID-19 KW - Data science KW - Public health KW - Surveillance SP - 1 EP - 5 JF - AI & society JO - AI Soc N2 - This paper provides an early evaluation of Artificial Intelligence (AI) against COVID-19. The main areas where AI can contribute to the fight against COVID-19 are discussed. It is concluded that AI has not yet been impactful against COVID-19. Its use is hampered by a lack of data, and by too much data. Overcoming these constraints will require a careful balance between data privacy and public health, and rigorous human-AI interaction. It is unlikely that these will be addressed in time to be of much help during the present pandemic. In the meantime, extensive gathering of diagnostic data on who is infectious will be essential to save lives, train AI, and limit economic damages. SN - 0951-5666 UR - https://www.unboundmedicine.com/medline/citation/32346223/Artificial_intelligence_vs_COVID_19:_limitations_constraints_and_pitfalls_ L2 - https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/32346223/ DB - PRIME DP - Unbound Medicine ER -
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