While formal AI incident research is relatively new, a number of people have been collecting what could be considered incidents. These include,

• Awesome Machine Learning Interpretability: AI Incident Tracker
• AI and Algorithimic Incidents and Controversies of Charlie Pownall
• Map of Helpful and Harmful AI

If you have an incident resource that could be added here, please contact us.

The following publications have been indexed by Google scholar as referencing the database itself, rather than solely individual incidents. Please contact us if your reference is missing.

Responsible AI Collaborative Research

Where needed to serve the broader safety and fairness communities, the Collab produces and sponsors research. Works to date include the following.

• The original research publication released at the public announcement of the AI Incident Database. All citations of this work will be added to this page.
  McGregor, Sean. "Preventing repeated real world AI failures by cataloging incidents: The AI incident database." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 35. No. 17. 2021.
• A major update to the incident definitions and criteria as presented at the 2022 NeurIPS Workshop on Human-Centered AI.
  McGregor, Sean, Kevin Paeth, and Khoa Lam. "Indexing AI Risks with Incidents, Issues, and Variants." arXiv preprint arXiv:2211.10384 (2022).
• Our approach to reducing the uncertainty of incident causes when analyzing open source incident reports. Presented at SafeAI.
  Pittaras, Nikiforos, and Sean McGregor. "A taxonomic system for failure cause analysis of open source AI incidents." arXiv preprint arXiv:2211.07280 (2022).
• Important lessons learned from editing AI incidents, focusing on issues related to their temporal ambiguity, multiplicity, large-scale exposure harms, and inherent uncertainty in reporting. Submitted to the 2025 Conference on Innovative Applications of Artificial Intelligence (IAAI-25).
  Paeth, Kevin, Daniel Atherton, Nikiforos Pittaras, Heather Frase, Sean McGregor. "Lessons for Editors of AI Incidents from the AI Incident Database." arXiv preprint arXiv:2409.16425 (2024)

2026 (Through February 15th)

• Abuadbba, Alsharif, Nazatul Sultan, Surya Nepal, and Sanjay Jha. "Human Society-Inspired Approaches to Agentic AI Security: The 4C Framework." arXiv preprint arXiv:2602.01942 (2026). https://doi.org/10.48550/arXiv.2602.01942.
• Anderson, John. "Data-Centric Governance and Trustworthy Artificial Intelligence for Ethical Welfare Management Systems." EuroLexis Research Index of International Multidisciplinary Journal for Research & Development 13, no. 01 (2026): 1075-1081. https://researchcitations.org/index.php/elriijmrd/article/view/94.
• Assalaarachchi, Lakshana Iruni, Zainab Masood, Rashina Hoda, and John Grundy. “Toward Agentic Software Project Management: A Vision and Roadmap.” arXiv (cs.SE), January 23, 2026. (Author’s preprint accepted for AGENT workshop at ICSE 2026.) https://doi.org/10.48550/arXiv.2601.16392.
• Bentley, Kate H., Luca Belli, Adam M. Chekroud, Emily J. Ward, Emily R. Dworkin, Emily Van Ark, Kelly M. Johnston, Will Alexander, Millard Brown, and Matt Hawrilenko. “VERA-MH: Reliability and Validity of an Open-Source AI Safety Evaluation in Mental Health.” arXiv (cs.AI), revised February 17, 2026. https://doi.org/10.48550/arXiv.2602.05088.
• Chaudhry, Mohit. “The Licensing Landscape for Responsible, Open-Source AI.” In Democratising AI: Towards Open, Decentralised AI Ecosystems, edited by Basu Chandola and Anirban Sarma, 98–111. New Delhi: Observer Research Foundation, 2026. https://www.orfonline.org/public/uploads/upload/20260211094122.pdf.
• Çılgın, Turgut. “Dialectical Analysis of Problems Created by Technological Developments in the Labour Market.” Sosyal Siyaset Konferansları Dergisi / Journal of Social Policy Conferences, no. 89 (January 2026). https://doi.org/10.26650/jspc.2025.89.1773834.
• Cuesta, Albert. “La IA en el futur de les llengües europees no hegemòniques: oportunitats, desafiaments i estratègies de preservació.” Barcelona: Fundació Irla; Coppieters Foundation; Accent Obert, February 2026. PDF. ISBN 978-84-09-81831-0. https://irla.cat/wp-content/uploads/2026/01/estudi-ia-llengua-fundacioirla-coppietersfoundation-accentobert.pdf.
• DeLaney, JR. “Deep Dive: The 1973 Lighthill Report: How One Mathematician Accidentally Triggered AI’s Dark Age.” AI Innovations Unleashed, February 4, 2026. https://www.aiinnovationsunleashed.com/deep-dive-the-1973-lighthill-report-how-one-mathematician-accidentally-triggered-ais-dark-age/.
• Dockara, Tirupathi Rao. “Data Governance for Sustainable AI in Organizations: A Benchmarkability-First Capability Model, Evidence Map, and Marketplace Microdata Demonstration.” Research Square (preprint), January 30, 2026. https://doi.org/10.21203/rs.3.rs-8734900/v1.
• Domin, Heather, Pradyumna Chari, Ramesh Raskar, and Grace Davin. “Economic and Systemic Considerations in Agentic Web Systems.” SSRN, January 15, 2026. https://doi.org/10.2139/ssrn.6078327.
• Ford, Heather, Andrew Burrell, Monica Monin, Bhuva Narayan, and Suneel Jethani. “Hacking AI Chatbots for Critical AI Literacy in the Library.” Journal of the Australian Library and Information Association, published online February 4, 2026. https://doi.org/10.1080/24750158.2026.2614000.
• Gordieiev, Oleksandr, Daria Gordieieva, Rainer Austen, Anatoliy Gorbenko, and Olga Tarasyuk. “Quality Assessment of Artificial Intelligence Systems: A Metric-Based Approach.” Electronics 15, no. 3 (2026): 691. https://doi.org/10.3390/electronics15030691.
• Grimm, Robert. “Mapping the Stochastic Penal Colony.” arXiv preprint arXiv:2602.00033 [cs.CY] (January 18, 2026). https://doi.org/10.48550/arXiv.2602.00033.
• Jones, Groucho. “Convergent Personality Representations in Large Language Models Evidence for a Theory of Latent Attractors.” SSRN Scholarly Paper, December 31, 2025. https://doi.org/10.2139/ssrn.5993074.
• Lee, Sung Une, Harsha Perera, Yue Liu, Boming Xia, Qinghua Lu, Liming Zhu, Olivier Salvado, and Jon Whittle. “Responsible AI Question Bank for Risk Assessment.” ACM Computing Surveys (Just Accepted), published online January 29, 2026. https://doi.org/10.1145/3790096.
• Saburov, Sergey. “Security and Risk Implications of Transformer-Based Large Language Models.” Preprint, Preprints.org, February 9, 2026. https://doi.org/10.20944/preprints202602.0680.v1.
• Wall, Emily. “Next Steps in Research on Human Bias in Visual Data Analysis.” In Human Bias in Visual Data Analysis, 221–229. Cham: Springer, 2026. https://doi.org/10.1007/978-3-032-09307-3_8.
• Xu, Wei, Zaifeng Gao, and Marvin J. Dainoff. “An HCAI Methodological Framework: Putting It into Action to Enable Human-Centered AI.” IEEE Transactions on Human-Machine Systems 56, no. 1 (February 2026): 78–94. https://doi.org/10.1109/THMS.2025.3631590.
• Xu, Wei. “Human-Centered Artificial Intelligence (HCAI): Foundations and Approaches.” arXiv preprint arXiv:2601.01247 [cs.HC] (February 18, 2026; rev. from January 3, 2026). https://doi.org/10.48550/arXiv.2601.01247.
• Zhou, Jianlong, and Fang Chen. “AI Ethics Operationalisation: Progress, Tools, and Opportunities.” SSRN (January 12, 2026). https://doi.org/10.2139/ssrn.6067748.

2025

• Adepu, Pavan Kumar, and Sai Kumar Kalya. "Red Teaming as a Service (RTaaS) for Cloud-Hosted GenAI: A Responsible AI Perspective." (2025). https://www.researchgate.net/publication/399104917_Red_Teaming_as_a_Service_RTaaS_for_Cloud-Hosted_GenAI_A_Responsible_AI_Perspective.
• Agarwal, Avinash, and Manisha J. Nene. “A Five-Layer Framework for AI Governance: Integrating Regulation, Standards, and Certification.” Transforming Government: People, Process and Policy 19, no. 3 (2025): 535–555. https://doi.org/10.1108/TG-03-2025-0065.
• Agarwal, Avinash, and Manisha J. Nene. “Incorporating AI Incident Reporting into Telecommunications Law and Policy: Insights from India.” arXiv (2025). https://doi.org/10.48550/arXiv.2509.09508.
• Aguilar Antonio, Juan Manuel. Uso de la inteligencia artificial por redes criminales de alto riesgo. París: Programa EL PACCTO 2.0 (Expertise France), September 2025. https://doi.org/10.5281/zenodo.16750778.
• Amador-Lankster, Velmar. “Facial Recognition in Policing: How Algorithmic Bias Targets People of Color.” The Undergraduate Law Review at UC San Diego 3, no. 1 (2025). https://doi.org/10.5070/L3.47403.
• Apeiron, Anastasia S., Davide Dell'Anna, Pradeep K. Murukannaiah, and Pınar Yolum. "Model and Mechanisms of Consent for Responsible Autonomy." In 24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025, pp. 133-141. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2025. https://doi.org/10.5555/3709347.3743525.
• Assuncao, Isadora. “The Collaborative Edge: Context-Specific Pathways to Responsible AI Development Through University-Industry Partnerships.” SSRN, January 22, 2025. https://doi.org/10.2139/ssrn.5297671.
• Attard-Frost, Blair, and David Gray Widder. "The ethics of AI value chains." Big Data & Society 12, no. 2 (2025): 20539517251340603. https://doi.org/10.1177/20539517251340603.
• Attard-Frost, Blair. "Transfeminist AI governance." arXiv preprint arXiv:2503.15682 (2025). https://doi.org/10.48550/arXiv.2503.15682.
• Bahiru, Tadesse K., and Ioannis A. Kakadiaris. "Codecard: Leveraging LLMs to Evaluate AI Model Code Development with the System Cards Framework." (2025). https://par.nsf.gov/servlets/purl/10662105.
• Bai, Bing. "Research on Risks and Governance Pathways of False and Harmful Information in the Application of Generative Artificial Intelligence." In 2025 5th International Conference on Artificial Intelligence, Big Data and Algorithms (CAIBDA), pp. 626-629. IEEE, 2025. https://doi.org/10.1109/CAIBDA65784.2025.11183077.
• Ballantyne, Emily, Michael Pin-Chuan Lin, Daniel H Chang, and Eric Poitras. "Bridging educational equity gaps: expanding the CHAT-ACTS framework for personalized GenAI chatbots in higher education." Journal of Computing in Higher Education 37, no. 4 (2025): 1564-1589. https://doi.org/10.1007/s12528-025-09475-z.
• Batool, Amna, Didar Zowghi, and Muneera Bano. "AI governance: a systematic literature review." AI and Ethics 5, no. 3 (2025): 3265-3279. https://doi.org/10.1007/s43681-024-00653-w.
• Batool, Amna, Sunny Lee, Yue Liu, and Liming Dong. “The Anatomy of AI Policies: A Systematic Comparative Analysis of AI Policies across the Globe.” AI and Ethics 6, art. 55 (2026). Published December 10, 2025. https://doi.org/10.1007/s43681-025-00886-3.
• Battineni, Gopi, Sharmin Nisar Chougule, Aman Kataria, and Lalit Mohan Goyal. "Navigating Ethics and Legalities in Artificial Intelligence: Challenges, Frameworks, and Future Directions." In Generative AI in Healthcare: Concepts, Methodologies, Tools, and Applications, pp. 293-315. Singapore: Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-95-2129-6_12.
• Becerra, Sofia, Jiayan Xie, Clare Boulding, and Clara van Muiswinkel. "QueenMUN 2025 Harmful Content on Social Media Background Guide." https://queenmun.qmslife.com/wp-content/uploads/2025/04/QueenMUN-2025-Background-Guide-UNICEF.pdf.
• Beiker, Sven A., Jonas Waidringer, and Chandadevi Giri. "Artificial Intelligence in Product Development and Innovation." In 2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), pp. 1-9. IEEE, 2025. https://doi.org/10.1109/ACDSA65407.2025.11165896.
• Bhardwaj, Akhil, Jackson Nickerson, and Joseph T. Mahoney. “Organizations Beyond the Limit: The Role of Strategic Decisions in Industrial Disasters.” SSRN, October 22, 2025. https://doi.org/10.2139/ssrn.5644048.
• Bhardwaj, Akhil. “Avoiding the Iron Cage of AI Technocracy Based on the Principle of Reversibility of Harm.” Conference paper, accepted September 9, 2025. University of Bath Research Portal. https://researchportal.bath.ac.uk/en/publications/avoiding-the-iron-cage-of-ai-technocracy-based-on-the-principle-o/.
• Bikkasani, Dileesh Chandra. "Navigating artificial general intelligence (AGI): Societal implications, ethical considerations, and governance strategies." AI and Ethics 5, no. 3 (2025): 2021-2036. https://doi.org/10.1007/s43681-024-00642-z.
• Bonnet, Severin, and Frank Teuteberg. "Unfolding the potential of generative artificial intelligence: Design principles for chatbots in academic teaching and research." International Journal of Knowledge Management (IJKM) 21, no. 1 (2025): 1-25. https://doi.org/10.4018/IJKM.368223.
• Brennan, Andrea, Gwyneth Sutherlin, Lisa Pagano-Wallace, and Hermie Mendoza. "Finding Deepfakes: A Tabletop Exercise About AI, Decisionmaking, and Algorithmic Performance." Joint Force Quarterly 118, no. 3 (2025): 49-55. https://digitalcommons.ndu.edu/joint-force-quarterly/vol118/iss3/8/.
• Bucknall, Ben, Saad Siddiqui, Lara Thurnherr, Conor McGurk, Ben Harack, Anka Reuel, Patricia Paskov et al. "In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate?." In Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, pp. 3148-3161. 2025. https://doi.org/10.1145/3715275.3732201.
• Burton, Sharon L., and David P. Harvie. "Deepfakes: Unmasking the Technological, Societal, and Ethical Dimensions." RAIS Journal for Social Sciences 9, no. 2 (2025): 1-14. https://journal.rais.education/index.php/raiss/article/view/277.
• Buselli, Irene. No Metric Is an Island: How Algorithmic Fairness Interacts with Other AI Properties. PhD diss., Università degli Studi di Genova, 2025. https://hdl.handle.net/20.500.14242/352707.
• Campos-Castillo, Celeste, Xuan Kang, and Linnea I. Laestadius. "Perspectives on How Sociology Can Advance Theorizing about Human-Chatbot Interaction and Developing Chatbots for Social Good." arXiv preprint arXiv:2507.05030 (2025). https://doi.org/10.48550/arXiv.2507.05030.
• Cao, Hongpeng, Yanbing Mao, Yihao Cai, Lui Sha, and Marco Caccamo. “Runtime Learning Machine.” OpenReview (submitted to ICLR 2025; first posted September 17, 2024; last modified February 5, 2025). https://openreview.net/forum?id=KCTHM2Ffh3.
• Carvalho, Waydell. "Governing Self-Modifying AI: A Federal Framework for Runtime Safety." Available at SSRN 5392553 (2025). https://dx.doi.org/10.2139/ssrn.5392553.
• Cascella, Marco, Mohammed Naveed Shariff, Omar Viswanath, Matteo Luigi Giuseppe Leoni, and Giustino Varrassi. "Ethical Considerations in the Use of Artificial Intelligence in Pain Medicine." Current Pain and Headache Reports 29, no. 1 (2025): 10. https://doi.org/10.1007/s11916-024-01330-7.
• Cascella, Marco. "Basic Knowledge of AI for Clinicians." In Exploring AI in Pain Research and Management, pp. 5-24. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78833-8_2.
• Castañeira, Josu Eguiluz, Axel Brando, Migle Laukyte, and Marc Serra-Vidal. "Position Paper: If Innovation in AI Systematically Violates Fundamental Rights, Is It Innovation at All?" arXiv preprint arXiv:2511.00027 (2025). https://doi.org/10.48550/arXiv.2511.00027.
• Çetin, Orçun, Baturay Birinci, Çağlar Uysal, and Budi Arief. "Exploring the Cybercrime Potential of LLMs: A Focus on Phishing and Malware Generation." In European Interdisciplinary Cybersecurity Conference, pp. 98-115. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-94855-8_7.
• Chakraborti, Mahasweta, Bert Joseph Prestoza, Nicholas Vincent, Vladimir Filkov, and Seth Frey. "Responsible AI in the OSS: Reconciling Innovation with Risk Assessment and Disclosure." In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, vol. 8, no. 1, pp. 513-527. 2025. https://doi.org/10.1609/aies.v8i1.36567.
• Chatzipanagiotis, Michael. "Incident Reporting and Investigation under the AI Act: Some Insights from Aviation." International Journal of Law and Information Technology, forthcoming (2025). https://dx.doi.org/10.2139/ssrn.5811603.
• Chau, Bao Kham, and George He. "Audio deepfakes and the regulation of the landlords of creativity." In Cambridge Forum on AI: Law and Governance, vol. 1, p. e30. Cambridge University Press, 2025. https://doi.org/10.1017/cfl.2025.10011.
• Chedalla, Anish Sai, Samina Ali, Jiuming Chen, and Eric Xia. "Turn-by-Turn Behavior Monitoring in LM-Guided Psychotherapy." In The 14th International Joint Conference on Natural Language Processing and The 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, pp. 105-122. 2025. https://aclanthology.org/2025.ijcnlp-srw.10/.
• Chen, Kevin, Saleh Afroogh, Abhejay Murali, David Atkinson, Amit Dhurandhar, and Junfeng Jiao. "LLM Harms: A Taxonomy and Discussion." arXiv preprint arXiv:2512.05929 (2025). https://doi.org/10.48550/arXiv.2512.05929.
• Chen, Yian, and Lana Do. "Leveraging LLMs with Strategic Prompting." In Human-Computer Interaction: 10th Iberoamerican Conference, HCI-COLLAB 2024, Pereira, Colombia, June 4–7, 2024, Revised Selected Papers, p. 39. Springer Nature, 2025. https://doi.org/10.1007/978-3-031-91328-0_4.
• Ciriello, Raffaele Fabio, Angelina Ying Chen, and Zara Annette Rubinsztein. "Compassionate AI Design, Governance, and Use." IEEE Transactions on Technology and Society (2025). https://doi.org/10.1109/TTS.2025.3538125.
• Coester, Ursula, Dominik Adler, Christian Böttger, and Norbert Pohlmann. "Unintended Consequences of Large Language Models and Their Impact on Society." Electronic Communications of the EASST 84 (2025). https://doi.org/10.14279/eceasst.v84.2676.
• Conklin, Sherri. "A Model for Using Ethical Theory to Specify Epistemic Goals for Explainable AI." In 2025 IEEE International Symposium on Ethics in Engineering, Science, and Technology (ETHICS), pp. 1-9. IEEE, 2025. https://doi.org/10.1109/ETHICS65148.2025.11098188.
• Corbucci, Luca. Beyond Model Accuracy: Building Trustworthy Federated Learning Systems. PhD diss., Università degli Studi di Pisa, 2025. https://hdl.handle.net/20.500.14242/307962.
• Dai, Jessica, Inioluwa Deborah Raji, Benjamin Recht, and Irene Y. Chen. "Aggregated Individual Reporting for Post-Deployment Evaluation." arXiv preprint arXiv:2506.18133 (2025). https://doi.org/10.48550/arXiv.2506.18133.
• Del Castillo, Aída Ponce. "Governing AI at Work: Anticipating Technological Trends and the Role of Social Dialogue." Rethink, Regulate, Reimagine: 55-61. https://accoshop-assets-prod.s3.eu-west-1.amazonaws.com/content_download/9789464679694/9789464679694_AI%20Rethink%2C%20Regulate%2C%20Reimagine_downloadable.pdf#page=56.
• Denecke, Kerstin, Guillermo Lopez-Campos, and Richard May. "The unintended harm of Artificial Intelligence (AI): exploring critical incidents of AI in healthcare." In MEDINFO 2025—Healthcare Smart× Medicine Deep, pp. 1013-1018. IOS Press, 2025. https://doi.org/10.3233/shti250992.
• Doherty, Camille. “The Danger of Deepfakes: Information Pollution and Epistemic Insecurity.” Senior thesis (B.A.), Claremont McKenna College, December 2024. https://scholarship.claremont.edu/cmc_theses/3750.
• Durand, Serge. "Over-Approximating Neural Networks for Verification, Robustness, and Explainability." PhD diss., Université Paris-Saclay, 2025. https://theses.hal.science/tel-05468098/.
• Elamrani, Aïda. "Introduction to Artificial Consciousness: History, Current Trends and Ethical Challenges." arXiv preprint arXiv:2503.05823 (2025). https://doi.org/10.48550/arXiv.2503.05823.
• Emory, Tara, and Maura R. Grossman. “A Primer on the Different Meanings of ‘Bias’ for Legal Practice.” SSRN, last revised July 17, 2025. https://doi.org/10.2139/ssrn.5356035.
• Erukude, Sai Teja, Viswa Chaitanya Marella, and Suhasnadh Reddy Veluru. "AI-Driven Cybersecurity Threats: A Survey of Emerging Risks and Defensive Strategies." In International Conference on Data Science and Applications, pp. 185-197. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-032-10783-1_14.
• Ezell, Carson, Xavier Roberts-Gaal, and Alan Chan. " Incident Analysis for AI Agents." In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, vol. 8, no. 1, pp. 865-878. 2025. https://doi.org/10.1609/aies.v8i1.36596.
• Faba, José María Martín. "La inteligencia artificial en la nueva directiva de responsabilidad por los daños causados por productos defectuosos¿ realidad o expectativa?." Revista CESCO de Derecho de Consumo 53 (2025): 14-19. https://doi.org/10.18239/RCDC_2025.53.3648.
• Faleiro, Felipe Reis. Jornalismo na era da IA: limites e possibilidades da inteligência artificial generativa em veículos jornalísticos. Master’s thesis, Programa de Pós-Graduação em Comunicação Social, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, 2025. https://repositorio.pucrs.br/dspace/bitstream/10923/27165/1/000510063-Texto%2Bcompleto-0.pdf.
• Fan, Liang, and Menglei Wu. "Social Impacts, Risks, and Governance Framework of Generative Artificial Intelligence Applications." In 2025 International Conference on Algorithms, Software and Network Security (ASNS), pp. 41-48. IEEE, 2025. https://doi.org/10.1109/ASNS67347.2025.11346050.
• Faustorilla Jr, John Francis, and Joseph Thomas Capistrano. "Establishing Responsible Artificial Intelligence-Use Among Healthcare Institutions Through ISO IEC 42001 Artificial Intelligence Management System." In Proceedings of Eighth International Conference on Information System Design and Intelligent Applications, pp. 355-366. Singapore: Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-9248-4_27.
• Feng, Jing, Xiaolu Bai, Yunan Liu, and Christopher Michael Cunningham. "Proactive Remote Operation of Automated Vehicles: Supporting human controllability." In Handbook of Human-Centered Artificial Intelligence, pp. 1-47. Singapore: Springer Nature Singapore, 2025. https://link.springer.com/content/pdf/10.1007/978-981-97-8440-0_107-1.pdf.
• Gao, Haoyu, Mansooreh Zahedi, Wenxin Jiang, Hong Yi Lin, James Davis, and Christoph Treude. "AI Safety in the Eyes of the Downstream Developer: A First Look at Concerns, Practices, and Challenges." arXiv preprint arXiv:2503.19444 (2025). https://doi.org/10.48550/arXiv.2503.19444.
• Gengler, Eva, and Marco Wedel. “Ethical AI Through a Feminist Lens: Challenging Power and Redefining Technology.” In Handbook of Global Philosophies on AI Ethics: Toward Sustainable Futures, edited by Naresh Singh and Ram B. Ramachandran, 189–200. CRC Press, 2025. https://www.routledge.com/Handbook-of-Global-Philosophies-on-AI-Ethics-Toward-Sustainable-Futures/Singh-Ramachandran/p/book/9781032955643.
• Ghaffar Nia, Nafiseh, Amin Amiri, and Adrienne Kline. "Bioethical Perspectives on Deployment of Large Language Model Agents: A Scoping Review." Authorea Preprints (2025). https://doi.org/10.36227/techrxiv.175979365.58528281/v1.
• Ghaffar Nia, Nafiseh, Amin Amiri, Yuan Luo, and Adrienne Kline. “Ethical Perspectives on Deployment of Large Language Model Agents in Biomedicine: A Survey.” AI and Ethics 6, art. 32 (2026). Published December 4, 2025. https://doi.org/10.1007/s43681-025-00847-w.
• Giannopoulos, Giorgos, and Dimitris Sacharidis. "Responsible AI." In Human-Centered AI: An Illustrated Scientific Quest, pp. 619-644. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-61375-3_12.
• Gibson, Stephen, and Winston Tang. “Challenges in Assessing the Impacts of Regulation of Artificial Intelligence.” M-RCBG Associate Working Paper Series 2025.262. Cambridge, MA: Harvard Kennedy School, Mossavar-Rahmani Center for Business & Government, July 2025. https://dash.harvard.edu/handle/1/42718677.
• Gibson, Stephen, and Winston Tang. Challenges in Assessing the Impacts of Regulation of Artificial Intelligence. London: Social Market Foundation, October 2025. https://www.smf.co.uk/wp-content/uploads/2025/10/Challenges-in-assessing-the-impacts-of-regulation-of-Artificial-Intelligence-Oct-25.pdf.
• Gigante, Domenico. "A framework for mitigating Trustworthy AI issues in practice." (2025). https://ricerca.uniba.it/handle/11586/539808.
• Girard-Chanudet, Camille. "Ground-truth is law: The invisible conceptual work behind AI." Big Data & Society 12, no. 2 (2025): 20539517251352823. https://doi.org/10.1177/20539517251352823.
• Goldkind, Lauri, Joy Ming, and Alex Fink. "AI in the nonprofit human services: Distinguishing between hype, harm, and hope." Human Service Organizations: Management, Leadership & Governance 49, no. 3 (2025): 225-236. https://doi.org/10.1080/23303131.2024.2427459.
• Golpayegani, Seyedeh Delaram S. Semantic Frameworks to Support the EU AI Act’s Risk Management and Documentation. PhD diss., Trinity College Dublin, the University of Dublin, 2025. https://www.tara.tcd.ie/bitstreams/6056f177-b210-4aa3-9abd-1dd67f669588/download.
• Gölz, Paul, Nika Haghtalab, and Kunhe Yang. "Distortion of AI Alignment: Does Preference Optimization Optimize for Preferences?" arXiv preprint arXiv:2505.23749 (2025). https://doi.org/10.48550/arXiv.2505.23749.
• Goutier, Marc, Christopher Diebel, Martin Adam, and Alexander Benlian. "Humans Over-rely On Help From Artificial Intelligence In Problem-Solving." (2025). https://aisel.aisnet.org/ecis2025/hci/hci/5/.
• Gross, Nicole. "A powerful potion for a potent problem: transformative justice for generative AI in healthcare." AI and Ethics 5, no. 3 (2025): 2089-2101. https://doi.org/10.1007/s43681-024-00519-1.
• Gunasekara, Lakshitha, Nicole El-Haber, Swati Nagpal, Harsha Moraliyage, Zafar Issadeen, Milos Manic, and Daswin De Silva. "A Systematic Review of Responsible Artificial Intelligence Principles and Practice." Applied System Innovation 8, no. 4 (2025): 97. https://doi.org/10.3390/asi8040097.
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2024

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2023

Citations in peer-reviewed journal articles, book chapters, and preprints

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• Velichkovska, B., Denkovski, D., Gjoreski, H., Kalendar, M., & Osmani, V. (2023). A Survey of Bias in Healthcare: Pitfalls of Using Biased Datasets and Applications. In Artificial Intelligence Application in Networks and Systems (CSOC 2023) (pp. 570-584). Lecture Notes in Networks and Systems, volume 724. Springer.
• Watson, E., Viana, T., & Zhang, S. (2023). Augmented behavioral annotation tools, with application to multimodal datasets and models: A systematic review. AI, 4(1), 128-171.
• Winter, C., Hollman, N., & Manheim, D. (2023). Value Alignment for Advanced Artificial Judicial Intelligence. American Philosophical Quarterly, 60(2), 187-203.
• Wright, L. S. (2023). Artificial intelligence: Why we need it and why we need to be cautious. In M. Lovell, O. S. Moghraby, & R. Waller (Eds.), Digital Mental Health: From Theory to Practice (pp. 60-71). Cambridge University Press.
• Wu, W., & Liu, S. (2023). A comprehensive review and systematic analysis of artificial intelligence regulation policies. arXiv.
• Xia, B., Lu, Q., Perera, H., Zhu, L., Xing, Z., Liu, Y., & Whittle, J. (2023). Towards concrete and connected AI risk assessment (C2AIRA): A systematic mapping study. In 2023 IEEE/ACM 2nd International Conference on AI Engineering -- Software Engineering for AI (CAIN) (pp. 27-34). IEEE.
• Xia, B., Lu, Q., Perera, H., Zhu, L., Xing, Z., Liu, Y., & Whittle, J. (2023). Towards concrete and connected AI risk assessment (C2AIRA): A systematic mapping study. arXiv.
• Xu, W. (2023). User-centered design (IX): A "user experience 3.0" paradigm framework in the intelligence era. arXiv.
• Xu, W., & Dainoff, M. (2023). Enabling human-centered AI: A new junction and shared journey between AI and HCI communities. Interactions, 30(1), 42-47.
• Xu, W., & Dainoff, M. (2023). Enabling human-centered AI: A new junction and shared journey between AI and HCI communities. arXiv.
• Xu, W., Dainoff, M. J., Ge, L., & Gao, Z. (2023). Transitioning to human interaction with AI systems: New challenges and opportunities for HCI professionals to enable human-centered AI. International Journal of Human--Computer Interaction, 39(3), 494-518.
• Zhan, X., Sun, H., & Miranda, S. M. (2023). How does AI fail us? A typological theorization of AI failures. In ICIS 2023 Proceedings: AI in Business and Society.
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• Žunić, L., Đukanović, G., & Popović, G. (2023). Rizici vještačke inteligencije: Analiza i implikacije. In 15th International Conference "Information Technology and Application" (ITeO 2023) (Vol. 15, pp. 29-40). Banja Luka, Bosnia and Herzegovina.

Citations in briefs, theses, white papers, and mixed genres

• Acion, L., Rajngewerc, M., Randall, G., & Etcheverry, L. (2023). Generative AI poses ethical challenges for open science. Nature Human Behaviour, 7(1800--1801).
• Antunović, J. (2023). Sigurnost komunikacije u kritičnoj infrastrukturi [Undergraduate thesis, Sveučilište u Zagrebu, Fakultet prometnih znanosti]. Repozitorij Fakulteta prometnih znanosti.
• Agnew, W. (2023). AI ethics and critique for robotics (Publication No. 30636400) [Doctoral dissertation, University of Washington]. ProQuest Dissertations & Theses Global.
• Attard-Frost, B., & Widder, D. G. (2023). The Ethics of AI Value Chains. arXiv.
• Bogusz, I. C., & Johnson, D. (2023). AI for the benefit of society: Progress with trust and transparency. Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media. Stockholm: Fores.
• D'Albergo, E., Fasciani, T., & Giovanelli, G. (2023, January 19-21). Social Powers and Governance of Artificial Intelligence in Urban Security Policies: Video Surveillance in Turin. Paper presented at Re-assembling the social. Re(i)stituting the social. 40 years of AIS, Naples, Italy.
• Desouza, K. C., & Dawson, G. S. (2023). Pathways to trusted progress with artificial intelligence. IBM Center for The Business of Government.
• Duarte, A. B. F. (2023). Enhancing portuguese public services: Prototype of a mobile application with a digital assistant [Trabalho de projeto de mestrado, Escola Superior de Comunicação Social]. Instituto Politécnico de Lisboa, Escola Superior de Comunicação Social.
• Giannini, A. (2023). Criminal behavior and accountability of artificial intelligence systems (Doctoral dissertation, University of Florence and Maastricht University).
• Hoffmann, M., & Frase, H. (2023). Adding structure to AI harm: An introduction to CSET's AI harm framework. Center for Security and Emerging Technology.
• Isbell, C., Littman, M. L., & Norvig, P. (2023). Viewpoint: Software Engineering of Machine Learning Systems. Communications of the ACM, 66(2), 35-37.
• Knight, S., Heggart, K., Dickson-Deane, C., Ford, H., Hunter, J., Johns, A., Kitto, K., Cetindamar Kozanoglu, D., Maher, D., & Narayan, B. (2023). Submission in response to the House Standing Committee on Employment, Education and Training's inquiry into the use of generative artificial intelligence in the Australian education system. House Standing Committee on Employment, Education and Training's inquiry into the use of generative artificial intelligence in the Australian education system.
• Kutz, J., Göbels, V. P., Brajovic, D., Fresz, B., Renner, N., Omri, S., Neuhüttler, J., Huber, M., & Bienzeisler, B. (2023). KI-Zertifizierung und Absicherung im Kontext des EU AI Act: Herausforderungen und Bedürfnisse aus Sicht von Unternehmen. Fraunhofer IAO.
• Longstaff, T. (2023). SEI Thoughts on AI T and E and Related Topics. (Technical Report). Carnegie-Mellon University, Pittsburgh, PA. Air Force Life Cycle Management Center, Hanscom AFB, MA. Retrieved from Accession Number: AD1199686.
• Massei, G. (2023). Algorithmic Trading: An Overview and Evaluation of Its Impact on Financial Markets [Master's thesis, Università Ca' Foscari Venezia].
• Musser, M., Lohn, A., Dempsey, J. X., Spring, J., Kumar, R. S. S., Leong, B., Liaghati, C., Martinez, C., Grant, C. D., Rohrer, D., Frase, H., Bansemer, J., Rodriguez, M., Regan, M., Chowdhury, R., & Hermanek, S. (2023). Adversarial machine learning and cybersecurity: Risks, challenges, and legal implications. Center for Security and Emerging Technology.
• Narayanan, M., Seymour, A., Frase, H., & Elmgren, K. (2023). Repurposing the wheel: Lessons for AI standards (Workshop Report). Center for Security and Emerging Technology.
• NIST. Risk Management Playbook. 2023
• Sharma, A. (2023). Testing of machine learning algorithms and models (PhD dissertation). Universität Oldenburg.
• Shneiderman, B. (2023). ACM TechBrief: Safer algorithmic systems (Issue 6). Association for Computing Machinery.
• Sivakumaran, A. (2023). Investigating consumer perception and speculative AI labels for creative AI usage in media (Master's thesis, KTH, School of Electrical Engineering and Computer Science).
• Toner, H., Ji, J., Bansemer, J., Lim, L., Painter, C., Corley, C., Whittlestone, J., Botvinick, M., Rodriguez, M., & Kumar, R. S. S. (2023). Skating to where the puck is going: Anticipating and managing risks from frontier AI systems. Center for Security and Emerging Technology.
• Wang, L. (2023). An urgency for inclusivity: Redesigning datasets for improved representation of LGBTQ+ identity terms in artificial intelligence (A.I.). HSS4 - The Modern Context: Queer Theory and Politics, Professor Barnick.
• Zhang, J. (2023). Evaluating Artificial Neural Network Robustness for Safety-Critical Systems [Ph.D. dissertation, Technical University of Denmark]. Kgs. Lyngby: Technical University of Denmark.

2022

• Macrae, Carl. "Learning from the failure of autonomous and intelligent systems: Accidents, safety, and sociotechnical sources of risk." Risk analysis 42.9 (2022): 1999-2025.
• Felländer, Anna, et al. "Achieving a Data-driven Risk Assessment Methodology for Ethical AI." Digital Society 1.2 (2022): 13.
• Apruzzese, Giovanni, et al. "" Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice." arXiv preprint arXiv:2212.14315 (2022).
• Petersen, Eike, et al. "Responsible and regulatory conform machine learning for medicine: A survey of challenges and solutions." IEEE Access 10 (2022): 58375-58418.
• Schuett, Jonas. "Three lines of defense against risks from AI." arXiv preprint arXiv:2212.08364 (2022).
• Schiff, Daniel S. "Looking through a policy window with tinted glasses: Setting the agenda for US AI policy." Review of Policy Research.
• Neretin, Oleksii, and Vyacheslav Kharchenko. "Model for Describing Processes of AI Systems Vulnerabilities Collection and Analysis using Big Data Tools." 2022 12th International Conference on Dependable Systems, Services and Technologies (DESSERT). IEEE, 2022.
• Durso, Francis, et al. "Analyzing Failures in Artificial Intelligent Learning Systems (FAILS)." 2022 IEEE 29th Annual Software Technology Conference (STC). IEEE, 2022.
• Kassab, Mohamad, Joanna DeFranco, and Phillip Laplante. "Investigating Bugs in AI-Infused Systems: Analysis and Proposed Taxonomy." 2022 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW). IEEE, 2022.
• Braga, Juliao, et al. "Projeto para o desenvolvimento de um artigo sobre governança de algoritmos e dados." (2022).
• Secchi, Carlo, and Alessandro Gili. "Digitalisation for sustainable infrastructure: the road ahead." Digitalisation for sustainable infrastructure (2022): 1-326.
• Groza, Adrian, et al. "Elaborarea cadrului strategic nat, ional în domeniul inteligent, ei artificiale."
• Braga, Juliao, et al. "Project for the Development of a Paper on Algorithm and Data Governance." (2022). (Original Portuguese).
• NIST. Risk Management Playbook. 2022
• Shneiderman, Ben. Human-Centered AI. Oxford University Press, 2022.
• Schwartz, Reva, et al. "Towards a Standard for Identifying and Managing Bias in Artificial Intelligence." (2022).
• McGrath, Quintin et al. An Enterprise Risk Management Framework to Design Pro-Ethical AI Solutions." University of South Florida. (2022).
• Nor, Ahmad Kamal Mohd, et al. "Abnormality Detection and Failure Prediction Using Explainable Bayesian Deep Learning: Methodology and Case Study of Real-World Gas Turbine Anomalies." (2022).
• Xie, Xuan, Kristian Kersting, and Daniel Neider. "Neuro-Symbolic Verification of Deep Neural Networks." arXiv preprint arXiv:2203.00938 (2022).
• Hundt, Andrew, et al. "Robots Enact Malignant Stereotypes." 2022 ACM Conference on Fairness, Accountability, and Transparency. 2022.
• Tidjon, Lionel Nganyewou, and Foutse Khomh. "Threat Assessment in Machine Learning based Systems." arXiv preprint arXiv:2207.00091 (2022).
• Naja, Iman, et al. "Using Knowledge Graphs to Unlock Practical Collection, Integration, and Audit of AI Accountability Information." IEEE Access 10 (2022): 74383-74411.
• Cinà, Antonio Emanuele, et al. "Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning." arXiv preprint arXiv:2205.01992 (2022).
• Schröder, Tim, and Michael Schulz. "Monitoring machine learning models: A categorization of challenges and methods." Data Science and Management (2022).
• Corea, Francesco, et al. "A principle-based approach to AI: the case for European Union and Italy." AI & SOCIETY (2022): 1-15.
• Carmichael, Zachariah, and Walter J. Scheirer. "Unfooling Perturbation-Based Post Hoc Explainers." arXiv preprint arXiv:2205.14772 (2022).
• Wei, Mengyi, and Zhixuan Zhou. "AI Ethics Issues in Real World: Evidence from AI Incident Database." arXiv preprint arXiv:2206.07635 (2022).
• Petersen, Eike, et al. "Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions." IEEE Access (2022).
• Karunagaran, Surya, Ana Lucic, and Christine Custis. "XAI Toolsheet: Towards A Documentation Framework for XAI Tools."
• Paudel, Shreyasha, and Aatiz Ghimire. "AI Ethics Survey in Nepal."
• Ferguson, Ryan. "Transform Your Risk Processes Using Neural Networks."
• Fujitsu Corporation. "AI Ethics Impact Assessment Casebook," 2022
• Shneiderman, Ben and Du, Mengnan. "Human-Centered AI: Tools" 2022
• Salih, Salih. "Understanding Machine Learning Interpretability." Medium. 2022
• Garner, Carrie. "Creating Transformative and Trustworthy AI Systems Requires a Community Effort." Software Engineering Institute. 2022
• Weissinger, Laurin, AI, Complexity, and Regulation (February 14, 2022). The Oxford Handbook of AI Governance

2021

• Arnold, Z., Toner, H., CSET Policy. "AI Accidents: An Emerging Threat." (2021).
• Aliman, Nadisha-Marie, Leon Kester, and Roman Yampolskiy. "Transdisciplinary AI Observatory—Retrospective Analyses and Future-Oriented Contradistinctions." Philosophies 6.1 (2021): 6.
• Falco, Gregory, and Leilani H. Gilpin. "A stress testing framework for autonomous system verification and validation (v&v)." 2021 IEEE International Conference on Autonomous Systems (ICAS). IEEE, 2021.
• Petersen, Eike, et al. "Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Technical Challenges and Solutions." arXiv preprint arXiv:2107.09546 (2021).
• John-Mathews, Jean-Marie. AI ethics in practice, challenges and limitations. Diss. Université Paris-Saclay, 2021.
• Macrae, Carl. "Learning from the Failure of Autonomous and Intelligent Systems: Accidents, Safety and Sociotechnical Sources of Risk." Safety and Sociotechnical Sources of Risk (June 4, 2021) (2021).
• Hong, Matthew K., et al. "Planning for Natural Language Failures with the AI Playbook." Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 2021.
• Ruohonen, Jukka. "A Review of Product Safety Regulations in the European Union." arXiv preprint arXiv:2102.03679 (2021).
• Kalin, Josh, David Noever, and Matthew Ciolino. "A Modified Drake Equation for Assessing Adversarial Risk to Machine Learning Models." arXiv preprint arXiv:2103.02718 (2021).
• Aliman, Nadisha Marie, and Leon Kester. "Epistemic defenses against scientific and empirical adversarial AI attacks." CEUR Workshop Proceedings. Vol. 2916. CEUR WS, 2021.
• John-Mathews, Jean-Marie. L’Éthique de l’Intelligence Artificielle en Pratique. Enjeux et Limites. Diss. université Paris-Saclay, 2021.
• Smith, Catherine. "Automating intellectual freedom: Artificial intelligence, bias, and the information landscape." IFLA Journal (2021): 03400352211057145

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