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The Oxford Handbook of Ethics of AI
Abstract
This book explores the intertwining domains of artificial intelligence (AI) and ethics—two highly divergent fields which at first seem to have nothing to do with one another. AI is a collection of computational methods for studying human knowledge, learning, and behavior, including by building agents able to know, learn, and behave. Ethics is a body of human knowledge—far from completely understood—that helps agents (humans today, but perhaps eventually robots and other AIs) decide how they and others should behave. Despite these differences, however, the rapid development in AI technology today has led to a growing number of ethical issues in a multitude of fields, ranging from disciplines as far-reaching as international human rights law to issues as intimate as personal identity and sexuality. In fact, the number and variety of topics in this volume illustrate the width, diversity of content, and at times exasperating vagueness of the boundaries of “AI Ethics” as a domain of inquiry. Within this discourse, the book points to the capacity of sociotechnical systems that utilize data-driven algorithms to classify, to make decisions, and to control complex systems. Given the wide-reaching and often intimate impact these AI systems have on daily human lives, this volume attempts to address the increasingly complicated relations between humanity and artificial intelligence. It considers not only how humanity must conduct themselves toward AI but also how AI must behave toward humanity.
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“Biased AI, trained on historical data reflecting societal inequities [26,63], could lead to discriminatory outcomes in resource allocation or pricing, eroding public trust (Section 3.4.3).”
From Addressing Challenges for the Effective Adoption of Artificial Intelligence in the Energy Sector (2025) · cites this paper as [63]
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Kuziemski, M., & Misuraca, G. (2020) · Telecommunications Policy · doi:10.1016/j.telpol.2020.101976 · Cited by 610
Lebovitz, S., Lifshitz-Assaf, H., & Levina, N. (2022) · Organization Science · doi:10.1287/orsc.2021.1549 · Cited by 632
Explainable, trustworthy, and ethical machine learning for healthcare: A survey
Rasheed, K., Qayyum, A., Ghaly, M., Al-Fuqaha, A., Razi, A., & Qadir, J. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.106043 · Cited by 372
Putting AI ethics to work: are the tools fit for purpose?
Ayling, J., & Chapman, A. (2022) · AI and Ethics · doi:10.1007/s43681-021-00084-x · Cited by 253
Three Challenges for AI-Assisted Decision-Making
Steyvers, M., & Kumar, A. (2024) · Perspectives on Psychological Science · doi:10.1177/17456916231181102 · Cited by 217
Shao, C., Nah, S., Makady, H., & McNealy, J. (2024) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2024.2331858 · Cited by 94
AI ethics: from principles to practice
Zhou, J., & Chen, F. (2023) · AI & SOCIETY · doi:10.1007/s00146-022-01602-z · Cited by 72
Sahlgren, O. (2023) · Learning, Media and Technology · doi:10.1080/17439884.2021.1986065 · Cited by 30
Ethics dumping in artificial intelligence
Bélisle-Pipon, J.-C., & Victor, G. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1426761 · Cited by 26
“AI’s undeniable power has sparked discussions in domains such as ELSI (ethical, legal, and social implications), STS (Science and Technology Studies), and applied ethics (Dubber et al., 2020; Hagendorff, 2020; Horgan et al., 2020; Bélisle-Pipon et al., 2021; Slota et al., 2021).”
Regulating the safety of health–related artificial intelligence.
Silva, M., Flood, C., Goldenberg, A., & Singh, D. (2022) · Healthcare Policy | Politiques de Santé · doi:10.12927/hcpol.2022.26824 · Cited by 23
Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability
Metcalf, J., Singh, R., Moss, E., Tafesse, E., & Watkins, E. A. (2023) · 2023 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3593013.3594092 · Cited by 21
Hirvonen, H. (2024) · AI & SOCIETY · doi:10.1007/s00146-023-01731-z · Cited by 19
Enabling ‘AI’? The situated production of commensurabilities
Jaton, F., & Sormani, P. (2023) · Social Studies of Science · doi:10.1177/03063127231194591 · Cited by 17
Addressing Challenges for the Effective Adoption of Artificial Intelligence in the Energy Sector
Park, C. (2025) · Sustainability · doi:10.3390/su17135764 · Cited by 17
AI as a constituted system: accountability lessons from an LLM experiment
Nabben, K. (2024) · Data & Policy · doi:10.1017/dap.2024.58 · Cited by 11
Kasun, G. S., Liao, Y.-C., Margulieux, L. E., & Woodall, M. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1368604 · Cited by 10
Connectionism about human agency: responsible AI and the social lifeworld
Noller, J. (2025) · AI & SOCIETY · doi:10.1007/s00146-024-02133-5 · Cited by 6
Libraries and Artificial Intelligence
Rupar Korosec, M. (2021) · Advances in Library and Information Science · doi:10.4018/978-1-7998-7258-0.ch023 · Cited by 3
Metadata
- Venue
- Oxford University Press eBooks
- Publisher
- Oxford University Press
- Published
- 2020-07-09
- OpenAlex
- W4206566227
- Cited by
- 459
- References
- 0
- Citations by year
- 2026: 25 · 2025: 89 · 2024: 107 · 2023: 100 · 2022: 84 · 2021: 42 · 2020: 10
- FWCI
- 59.15
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Oxford University Press eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Social Sciences › Law › Literary and Philosophical Studies
- Keywords
- AI ethics, AI and society, human-AI relationship, algorithmic decision-making, socio-technical systems, human rights, personal identity, sexuality, moral status of AI
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