Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities

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Date Issued

2022-02

Date Online

2022-02-23

Language

en
Type
Journal Article

Review Status

Peer Review

Access Rights

Limited Access Limited Access

Usage Rights

Copyrighted; all rights reserved
Metadata
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Citation

Tzachor, A.; Devare, M.; King, B.; Avin, S.; Ó hÉigeartaigh, S. (2022) Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities. Nature Machine Intelligence 4, p. 104–109. ISSN: 2522-5839

Permanent link to cite or share this item

https://hdl.handle.net/10568/118363

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DOI

https://doi.org/10.1038/s42256-022-00440-4

Abstract/Description

Author ORCID identifiers

Medha Devare  https://orcid.org/0000-0003-0041-4812
 Brian King  https://orcid.org/0000-0002-7056-9214

Contributes to SDGs

SDG 1 - No poverty
SDG 2 - Zero hunger
AGROVOC Keywords
agriculture; artificial intelligence; risk factors; machine learning; data; risk reduction; participatory research; agricultura; inteligencia artificial; factores de riesgo; aprendizaje electrónico
Subjects
DOCUMENTATION; INFORMATICS; INFORMATION SYSTEMS; MODELING
Organizations Affiliated to the Authors
University of Cambridge; Reichman University; CGIAR Platform for Big Data in Agriculture; International Institute of Tropical Agriculture
CGIAR Impact Areas
Nutrition, health and food security; Poverty reduction, livelihoods and jobs

Collections

Alliance Bioversity CIAT Journal Articles
Alliance Research Lever 5: Digital Inclusion
CGIAR BigData Articles in Refereed Journals
IITA Journal Articles