Library:Harm to Nonhuman Animals from AI: a Systematic Account and Framework (research)
Harm to Nonhuman Animals from AI: a Systematic Account and Framework is a 2021 academic paper by John Hadley, Adam Henschke, and Robert Sparrow, published in the journal AI & Society. The paper provides a systematic account of how artificial intelligence (AI) technologies could harm nonhuman animals and explains why animal harms, often neglected in AI ethics, should be better recognized.
The paper begins by giving reasons for caring about animals and outlining the nature of animal harm, interests, and wellbeing. The authors then develop a comprehensive “harms framework” based on the work of animal scientist David Fraser, which maps human activities that impact on sentient animals. The harms framework is fleshed out with examples inspired by both scholarly literature and media reports.
The authors argue that AI has significant potential to harm animals, both independently and with existing technologies. They provide examples of how AI can create and amplify harms to animals, such as through automation in chicken sheds and dairies, robots, drones, and vehicles that incorporate AI in ways that may benefit or harm animals.
The paper concludes by considering the implications of their framework and suggesting directions for further research. The authors argue that their systematic account and framework should help inform ethical analyses of AI’s impact on animals and serve as a comprehensive and clear basis for the development and regulation of AI technologies to prevent and mitigate harm to nonhumans.
The Harms Framework
The framework is based on the work of animal scientist David Fraser and maps human activities that impact on sentient animals. The harms framework is intended to help inform ethical analyses of AI’s impact on animals and serve as a comprehensive and clear basis for the development and regulation of AI technologies to prevent and mitigate harm to nonhumans. The framework includes intentional harms that are legal or condemned, direct and indirect unintentional harm, foregone benefits, and systemic harms. It provides a way to classify and capture the many ways in which AI might create new harms or amplify existing harms for animals.
The 5 harms
- Intentional harms that are legal or condemned
- Direct unintentional harm
- Indirect unintentional harm
- Foregone benefits
- Systemic harms