AI for One Welfare: the role of animal welfare scientists in developing valid and ethical AI-based welfare assessment tools
The increasing use of artificial intelligence (AI) in livestock farming is accelerating the development of automated welfare assessment tools, particularly with advancement in generative AI such as large multimodal models (LMMs). Yet, animal welfare scientists have rarely been involved in the develo...
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Veterinary Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fvets.2025.1645901/full |
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| author | Borbala Foris Kehan Sheng Christian Dürnberger Maciej Oczak Jean-Loup Rault |
| author_facet | Borbala Foris Kehan Sheng Christian Dürnberger Maciej Oczak Jean-Loup Rault |
| author_sort | Borbala Foris |
| collection | DOAJ |
| description | The increasing use of artificial intelligence (AI) in livestock farming is accelerating the development of automated welfare assessment tools, particularly with advancement in generative AI such as large multimodal models (LMMs). Yet, animal welfare scientists have rarely been involved in the development process of these tools or their subsequent adaptation within the field. Here, we discuss possible roles for animal welfare scientists in the development and validation of AI-based welfare assessment tools. We first examine key uncertainties that emerge during development, including the selection of relevant, valid and reliable welfare indicators and gold standards, hardware and software solutions for data collection, methods for integrating multiple welfare indicators, and the real-world impact of automated welfare assessment tools. Second, we demonstrate the use of LMMs to assess welfare based on a case study using dairy cow cleanliness. Finally, we consider the practical implementation of AI-based welfare assessment and discuss potential tensions around (1) embedded values in LMMs, (2) AI’s influence on decision-making on farms, (3) the integration of AI in current knowledge systems by human-AI collaboration, and (4) the economics of AI-based welfare assessment and improvement. We conclude that LMMs could help automate welfare assessment and communicate results to humans in accessible formats, but outcomes depend on which stakeholders are involved in the development process. We advocate for developing AI-based welfare assessment tools through the One Welfare framework, recognizing that AI deployment affects humans, animals, and the environment simultaneously, and suggest potential pathways for animal welfare scientists to engage in the process. |
| format | Article |
| id | doaj-art-dd1d41fdef0e45ea8aa372c5e948cbc6 |
| institution | Kabale University |
| issn | 2297-1769 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Veterinary Science |
| spelling | doaj-art-dd1d41fdef0e45ea8aa372c5e948cbc62025-08-20T04:00:34ZengFrontiers Media S.A.Frontiers in Veterinary Science2297-17692025-08-011210.3389/fvets.2025.16459011645901AI for One Welfare: the role of animal welfare scientists in developing valid and ethical AI-based welfare assessment toolsBorbala Foris0Kehan Sheng1Christian Dürnberger2Maciej Oczak3Jean-Loup Rault4Centre for Animal Nutrition and Welfare, Clinical Department of Farm Animals and Food System Science, University of Veterinary Medicine Vienna, Vienna, AustriaAnimal Welfare Program, Faculty of Land and Food Systems, The University of British Columbia, Vancouver, BC, CanadaMesserli Research Institute, University of Veterinary Medicine Vienna, Vienna, AustriaPrecision Livestock Farming Hub, Clinical Department of Farm Animals and Food System Science, University of Veterinary Medicine Vienna, Vienna, AustriaCentre for Animal Nutrition and Welfare, Clinical Department of Farm Animals and Food System Science, University of Veterinary Medicine Vienna, Vienna, AustriaThe increasing use of artificial intelligence (AI) in livestock farming is accelerating the development of automated welfare assessment tools, particularly with advancement in generative AI such as large multimodal models (LMMs). Yet, animal welfare scientists have rarely been involved in the development process of these tools or their subsequent adaptation within the field. Here, we discuss possible roles for animal welfare scientists in the development and validation of AI-based welfare assessment tools. We first examine key uncertainties that emerge during development, including the selection of relevant, valid and reliable welfare indicators and gold standards, hardware and software solutions for data collection, methods for integrating multiple welfare indicators, and the real-world impact of automated welfare assessment tools. Second, we demonstrate the use of LMMs to assess welfare based on a case study using dairy cow cleanliness. Finally, we consider the practical implementation of AI-based welfare assessment and discuss potential tensions around (1) embedded values in LMMs, (2) AI’s influence on decision-making on farms, (3) the integration of AI in current knowledge systems by human-AI collaboration, and (4) the economics of AI-based welfare assessment and improvement. We conclude that LMMs could help automate welfare assessment and communicate results to humans in accessible formats, but outcomes depend on which stakeholders are involved in the development process. We advocate for developing AI-based welfare assessment tools through the One Welfare framework, recognizing that AI deployment affects humans, animals, and the environment simultaneously, and suggest potential pathways for animal welfare scientists to engage in the process.https://www.frontiersin.org/articles/10.3389/fvets.2025.1645901/fullgenerative AIlarge multimodal modelAI alignmentWelfare Qualityanimal interestsprecision livestock farming |
| spellingShingle | Borbala Foris Kehan Sheng Christian Dürnberger Maciej Oczak Jean-Loup Rault AI for One Welfare: the role of animal welfare scientists in developing valid and ethical AI-based welfare assessment tools Frontiers in Veterinary Science generative AI large multimodal model AI alignment Welfare Quality animal interests precision livestock farming |
| title | AI for One Welfare: the role of animal welfare scientists in developing valid and ethical AI-based welfare assessment tools |
| title_full | AI for One Welfare: the role of animal welfare scientists in developing valid and ethical AI-based welfare assessment tools |
| title_fullStr | AI for One Welfare: the role of animal welfare scientists in developing valid and ethical AI-based welfare assessment tools |
| title_full_unstemmed | AI for One Welfare: the role of animal welfare scientists in developing valid and ethical AI-based welfare assessment tools |
| title_short | AI for One Welfare: the role of animal welfare scientists in developing valid and ethical AI-based welfare assessment tools |
| title_sort | ai for one welfare the role of animal welfare scientists in developing valid and ethical ai based welfare assessment tools |
| topic | generative AI large multimodal model AI alignment Welfare Quality animal interests precision livestock farming |
| url | https://www.frontiersin.org/articles/10.3389/fvets.2025.1645901/full |
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