Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion
This document aims to support CGIAR researchers and their partners by providing guidance, recommendations and resources on ethical considerations in using artificial intelligence (AI) in food, land and water systems (FLWS) research and practice with attention to equity and inclusion dimensions. This...
| Main Authors: | , , , , |
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| Format: | Training Material |
| Language: | Inglés |
| Published: |
International Livestock Research Institute
2025
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| Online Access: | https://hdl.handle.net/10568/176705 |
| _version_ | 1855534088245477376 |
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| author | Jones-Garcia, Eliot Malapit, Hazel J. Magalhaes, Marilia Go, Ara Bryan, Elizabeth |
| author_browse | Bryan, Elizabeth Go, Ara Jones-Garcia, Eliot Magalhaes, Marilia Malapit, Hazel J. |
| author_facet | Jones-Garcia, Eliot Malapit, Hazel J. Magalhaes, Marilia Go, Ara Bryan, Elizabeth |
| author_sort | Jones-Garcia, Eliot |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This document aims to support CGIAR researchers and their partners by providing guidance, recommendations and resources on ethical considerations in using artificial intelligence (AI) in food, land and water systems (FLWS) research and practice with attention to equity and inclusion dimensions. This toolkit complements the GENDER Impact Platform Ethics and Standards Toolkit and aligns with CGIAR’s core ethical values outlined in the CGIAR Ethics Framework and the CGIAR Research Ethics Code.
In response to the rapid development and adoption of emerging AI technologies, the toolkit presents key issues and practical recommendations for researchers to consider across the research cycle, drawing on a comprehensive literature review and interviews with experts in AI ethics and social inclusion.
AI systems, as used in this context, refer to technologies that mimic aspects of human cognition and behavior—interpreting real-world data, generating predictions, and adapting through continuous learning (Benefo et al. 2022; Fu 2022; Manning et al. 2022). These systems are increasingly central to a suite of AI and agricultural technologies poised to transform FLWS research: not only in how we conduct research and generate insights, but also in how we define best practice for gender-related research and understand the downstream impacts of our research outputs. |
| format | Training Material |
| id | CGSpace176705 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | International Livestock Research Institute |
| publisherStr | International Livestock Research Institute |
| record_format | dspace |
| spelling | CGSpace1767052025-11-06T07:08:04Z Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion Jones-Garcia, Eliot Malapit, Hazel J. Magalhaes, Marilia Go, Ara Bryan, Elizabeth artificial intelligence agrifood systems research This document aims to support CGIAR researchers and their partners by providing guidance, recommendations and resources on ethical considerations in using artificial intelligence (AI) in food, land and water systems (FLWS) research and practice with attention to equity and inclusion dimensions. This toolkit complements the GENDER Impact Platform Ethics and Standards Toolkit and aligns with CGIAR’s core ethical values outlined in the CGIAR Ethics Framework and the CGIAR Research Ethics Code. In response to the rapid development and adoption of emerging AI technologies, the toolkit presents key issues and practical recommendations for researchers to consider across the research cycle, drawing on a comprehensive literature review and interviews with experts in AI ethics and social inclusion. AI systems, as used in this context, refer to technologies that mimic aspects of human cognition and behavior—interpreting real-world data, generating predictions, and adapting through continuous learning (Benefo et al. 2022; Fu 2022; Manning et al. 2022). These systems are increasingly central to a suite of AI and agricultural technologies poised to transform FLWS research: not only in how we conduct research and generate insights, but also in how we define best practice for gender-related research and understand the downstream impacts of our research outputs. 2025-09 2025-09-29T19:36:20Z 2025-09-29T19:36:20Z Training Material https://hdl.handle.net/10568/176705 en Open Access application/pdf International Livestock Research Institute Jones-Garcia, E., Malapit, H., Magalhaes, M., Go, A. and Bryan, E. 2025. Ethical use of artificial intelligence in food, land and water systems research: a guide for equity and inclusion. Nairobi, Kenya: CGIAR Gender Equality and Inclusion. |
| spellingShingle | artificial intelligence agrifood systems research Jones-Garcia, Eliot Malapit, Hazel J. Magalhaes, Marilia Go, Ara Bryan, Elizabeth Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion |
| title | Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion |
| title_full | Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion |
| title_fullStr | Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion |
| title_full_unstemmed | Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion |
| title_short | Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion |
| title_sort | ethical use of artificial intelligence in food land and water systems research a guide for equity and inclusion |
| topic | artificial intelligence agrifood systems research |
| url | https://hdl.handle.net/10568/176705 |
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