The AI Incident Database in the Literature and Public Record
This bibliography maps the growing body of scholarly, governmental, journalistic, and public-interest work that cites, uses, discusses, or otherwise engages with the AI Incident Database (AIID). It is maintained as a public research resource for examining how AI incident evidence travels across research, policy, standards, and public reporting.
Records are grouped by publication year, with government material and journalism presented separately. Citation-type labels support browsing and do not replace publisher metadata. Names associated with AIID are marked with a subtle highlight.
Experimental bibliography. This page is an evolving, AI-assisted index, not a citation metric, comprehensive literature review, or endorsement of the listed works. Metadata, classifications, links, and version relationships may contain errors. Each record should be verified against the original source before formal use. See About and Methodology for the inclusion standard, version policy, verification procedures, and known limitations.
Bibliography Overview
The figures below are calculated directly from the current HTML. Section counts are exact. Citation-type counts use the first editorial genre label attached to each record.
Entries by Section
| Section | Entries | Share |
|---|---|---|
| 2026 | 40 | 6.4% |
| 2025 | 196 | 31.5% |
| 2024 | 131 | 21.1% |
| 2023 | 76 | 12.2% |
| 2022 | 29 | 4.7% |
| 2021 | 10 | 1.6% |
| 2020 | 2 | 0.3% |
| Government | 25 | 4.0% |
| Journalism | 113 | 18.2% |
Citation Types
| Rank | Citation Type | Count | Share |
|---|---|---|---|
| 1 | Journal Article | 113 | 18.2% |
| 2 | Preprint | 110 | 17.7% |
| 3 | Conference Paper | 98 | 15.8% |
| 4 | AIID Blog | 47 | 7.6% |
| 5 | Book Chapter | 47 | 7.6% |
| 6 | Report | 39 | 6.3% |
| 7 | Unbadged / unspecified | 36 | 5.8% |
| 8 | Thesis / Dissertation | 30 | 4.8% |
| 9 | News | 20 | 3.2% |
| 10 | Trade Press | 15 | 2.4% |
| 11 | Analysis / Explainer | 12 | 1.9% |
| 12 | Blog / Essay | 9 | 1.4% |
| 13 | Magazine | 8 | 1.3% |
| 14 | Book | 6 | 1.0% |
| 15 | Web Resource | 6 | 1.0% |
| 16 | Guidance | 4 | 0.6% |
| 17 | Strategy / Policy | 4 | 0.6% |
| 18 | Standard / Guidance | 3 | 0.5% |
| 19 | Hearing Material | 2 | 0.3% |
| 20 | Newsletter | 2 | 0.3% |
| 21 | Presentation | 2 | 0.3% |
| 22 | Press Release | 2 | 0.3% |
| 23 | Strategy Project Material | 2 | 0.3% |
| 24 | Explainer | 1 | 0.2% |
| 25 | Organizational Publication | 1 | 0.2% |
| 26 | Project Deliverable | 1 | 0.2% |
| 27 | Research Agenda | 1 | 0.2% |
| 28 | Workshop Report | 1 | 0.2% |
Counts reflect the records currently displayed and should not be interpreted as citation-impact measures.
2026
Abraham, Sophia, Taiye Chen, Cyril Chhun, Giovanna Jaramillo-Gutierrez, Simon Mylius, Sayash Raaj, Peter Slattery, and Sean McGregor. “AI Incident Monitoring through a Public Health Lens.” arXiv, April 21, 2026. https://doi.org/10.48550/arXiv.2604.19914.
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.
AI Index Steering Committee. The AI Index 2026 Annual Report. Stanford Institute for Human-Centered Artificial Intelligence, April 2026. https://hai.stanford.edu/assets/files/ai_index_report_2026.pdf.
Anderson, John. “Data-Centric Governance and Trustworthy Artificial Intelligence for Ethical Welfare Management Systems.” EuroLexis Research Index of International Multidisciplinary Journal for Research and 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.
Bogucka, Edyta, Sanja Šćepanović, and Daniele Quercia. “Why AI Harms Can’t Be Fixed One Identity at a Time: What 5300 Incident Reports Reveal About Intersectionality.” In Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’26). ACM, 2026. https://doi.org/10.1145/3805689.3812347.
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.
De Miguel Velázquez, Julia, Sanja Šćepanović, Andrés Gvirtz, and Daniele Quercia. “The Quiet Path from Seemingly Minor Design Errors to Workplace AI Incidents.” In Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’26). ACM, 2026. https://doi.org/10.1145/3805689.3812396.
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.
European Telecommunications Standards Institute. ETSI TS 104 158-1 V1.1.1: Securing Artificial Intelligence (SAI); AI Incident Reporting; Part 1: AI Common Incident Expression (AICIE) Global Framework. March 2026. https://www.etsi.org/deliver/etsi_ts/104100_104199/10415801/01.01.01_60/ts_10415801v010101p.pdf.
European Telecommunications Standards Institute. ETSI TS 104 158-2 V1.1.1: Securing Artificial Intelligence (SAI); AI Incident Reporting; Part 2: AI Common Incident Expression (AICIE) Common Container. March 2026. https://www.etsi.org/deliver/etsi_ts/104100_104199/10415802/01.01.01_60/ts_10415802v010101p.pdf.
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.
Giattino, Charlie, Edouard Mathieu, Veronika Samborska, and Max Roser. “Global Annual Number of Reported Artificial Intelligence Incidents and Controversies.” Our World in Data, updated April 20, 2026. https://ourworldindata.org/grapher/annual-reported-ai-incidents-controversies.
Goldberg, Zachary J. “Künstliche Intelligenz und Vorurteil.” In Handbuch Immoralität, edited by Jörg Noller, 1–8. Berlin and Heidelberg: J.B. Metzler, 2026. https://doi.org/10.1007/978-3-476-06014-3_68-1.
Gomez, Francesca, Matthew Ball, Michael Harré, Lydia Preston, Josephine Schwab, and Caio Machado. “Designing Escalation Criteria for International AI Incident Response: Criteria, Triggers, and Thresholds.” arXiv, April 25, 2026; revised May 19, 2026. https://doi.org/10.48550/arXiv.2604.23183.
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.
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.
Machado, Caio Vieira, George Gor, and Omer Bilgin. The Case for Cross-Border Artificial Intelligence Incident Infrastructure. The Future Society, May 2026. https://thefuturesociety.org/wp-content/uploads/2026/05/The_Case_for_Cross-Border_AI_Incident_Infrastructure.pdf.
Mengesha, Isaak, Branwen Owen, Charlie Collins, Tina Wong, Simon Mylius, Peter Slattery, and Sean McGregor. “A Pragmatic Classification Framework for AI Incident Monitoring.” arXiv, April 23, 2026; revised May 6, 2026. https://doi.org/10.48550/arXiv.2604.21412.
Mumtaz, Ummara, and Summaya Mumtaz. “From Reactive to Proactive: A Multi-Regulatory Empirical Analysis of 480 AI Incidents and a Data-Driven Governance Compliance Framework.” arXiv, April 10, 2026. https://doi.org/10.48550/arXiv.2605.16281.
Niu, Chunling, Marta Del Rio-Guerra, Rui Jin, Esmeralda Marrero, Jennifer Carroll, and Christopher Brady. “When Human-AI Collaboration Failed: Analyzing Sociotechnical Incident Patterns in Educational AI.” In Proceedings of the 18th International Conference on Computer Supported Education (CSEDU 2026), vol. 1, 438–445. SCITEPRESS, 2026. https://doi.org/10.5220/0014897100004021.
Pi, Yulu, Lucas Lichner, Jae Woo Lee, Sijia Xiao, Renwen Zhang, and Jatinder Singh. “Push and Pushback in Contesting AI: Demands for and Resistance to Accountability.” In Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’26). ACM, 2026. https://doi.org/10.1145/3805689.3812323.
Popchanovska, Evgenija, Ana Gjorgjevikj, Maryan Rizinski, Lubomir T. Chitkushev, Irena Vodenska, and Dimitar Trajanov. “When AI Fails, What Works? A Data-Driven Taxonomy of Real-World AI Risk Mitigation Strategies.” arXiv, March 4, 2026. https://doi.org/10.48550/arXiv.2603.04259.
Rotlevi, Shaked. “Essential AI Security Best Practices.” Wiz, March 25, 2026. https://www.wiz.io/academy/ai-security/ai-security-best-practices.
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.
Shaffer Shane, Tommy, Simon Mylius, and Hamish Hobbs. Scheming in the Wild: Detecting Real-World AI Scheming Incidents with Open-Source Intelligence. Centre for Long-Term Resilience, March 27, 2026. https://www.longtermresilience.org/reports/v5-scheming-in-the-wild_-detecting-real-world-ai-scheming-incidents-through-open-source-intelligence-pdf/.
Shi, Yike, Qing Xiao, Qing Hu, Hong Shen, and Hua Shen. “The Siren Song of LLMs: How Users Perceive and Respond to Dark Patterns in Large Language Models.” In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI ’26). New York: Association for Computing Machinery, 2026. https://doi.org/10.1145/3772318.3791149.
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.
Wei, Kevin, and Lennart Heim. “Designing Incident Reporting Systems for Harms from General-Purpose AI.” Proceedings of the AAAI Conference on Artificial Intelligence 40, no. 44 (2026): 38016–38029. https://doi.org/10.1609/aaai.v40i44.41139.
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.
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.
Youngstown State University. “Data Visualization: AI Incidents and Their Impact.” n.d. Accessed May 4, 2026. https://ysu.edu/data-visualization-ai-incidents-and-their-impact.
Zhang, Leihan, Wecheng Ye, Xianlong Ma, Haochuan Liu, Yang Li, Qianyu Zhang, Jinliang Chen, and Qiang Yan. “RiskNet: A Large-Scale Dataset of AI Risk Incidents from News with Alignment and Multi-Dimensional Annotations.” arXiv, June 7, 2026. https://doi.org/10.48550/arXiv.2606.08376.
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, 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 and 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), 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, 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), 1-9. IEEE, 2025. https://doi.org/10.1109/ACDSA65407.2025.11165896.
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/.
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.
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.
Bommasani, Rishi, Kevin Klyman, Shayne Longpre, Sayash Kapoor, Nestor Maslej, Betty Xiong, Daniel Zhang, and Percy Liang. “The 2023 Foundation Model Transparency Index.” Transactions on Machine Learning Research, February 2025. https://openreview.net/forum?id=x6fXnsM9Ez.
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, Casey Mahoney, Sören Mindermann, Scott Singer, Vinay Hiremath, Charbel-Raphaël Segerie, Oscar Delaney, Alessandro Abate, Fazl Barez, Michael K. Cohen, Philip Torr, Ferenc Huszár, Anisoara Calinescu, Gabriel Davis Jones, Yoshua Bengio, and Robert F. Trager. "In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate?" In Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 3148-61. New York: Association for Computing Machinery, 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://doi.org/10.2139/ssrn.5392553.
Cascella, Marco. “Basic Knowledge of AI for Clinicians.” In Exploring AI in Pain Research and Management, 5-24. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78833-8_2.
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.
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, 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 (2025): 513–527. 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://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 1, e30 (2025). Cambridge University Press. 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, 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, 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), 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.
Cox, Andrew. “11 Ethics Case Studies of Artificial Intelligence for Library and Information Professionals.” In New Horizons in Artificial Intelligence in Libraries, edited by Edmund Balnaves, Leda Bultrini, Andrew Cox, and Raymond Uzwyshyn, 156–168. IFLA Publications 185. Berlin: De Gruyter Saur, 2025. https://doi.org/10.1515/9783111336435-012.
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2024
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Xu, W., Dainoff, M. J., Ge, L., and 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. https://doi.org/10.1080/10447318.2022.2041900.
Xu, Wei. "User-Centered Design (IX): A 'User Experience 3.0' Paradigm Framework in the Intelligence Era." arXiv, February 13, 2023. https://doi.org/10.48550/arXiv.2302.06681.
Zhan, X., Sun, H., and Miranda, S. M. (2023). “How does AI fail us? A typological theorization of AI failures.” In ICIS 2023 Proceedings: AI in Business and Society. https://aisel.aisnet.org/icis2023/aiinbus/aiinbus/25/.
Zhang, Jin. Evaluating Artificial Neural Network Robustness for Safety-Critical Systems. PhD diss., Technical University of Denmark, 2023. https://orbit.dtu.dk/en/publications/evaluating-artificial-neural-network-robustness-for-safety-critic/.
Zhou, L., Moreno-Casares, P. A., Martínez-Plumed, F., Burden, J., Burnell, R., Cheke, L., Ferri, C., Marcoci, A., Mehrbakhsh, B., Moros-Daval, Y., Ó hÉigeartaigh, S., Rutar, D., Schellaert, W., Voudouris, K., and Hernández-Orallo, J. (2023). Predictable artificial intelligence. arXiv. https://doi.org/10.48550/arXiv.2310.06167.
Zhu, Y. (Zhu Yu 朱禹), Chen, G. (Chen Guanze 陈关泽), Lu, Y. (Lu Yongrong 陆泳溶), and Fan, W. (Fan Wei 樊伟). (2023). “Generative Artificial Intelligence Governance Action Framework: Content Analysis Based on AIGC Incident Report Texts.” 图书情报知识 (Library and Information Knowledge) 40(4): 41–51. https://doi.org/10.13366/j.dik.2023.04.041.
Žunić, L., G. Đukanović, and G. Popović. “Rizici vještačke inteligencije: Analiza i implikacije.” In 15th International Scientific Congress – ITeO (Informational Technology for e-Education), 29–40. Banja Luka, 2023. https://www.researchgate.net/publication/384454549_RIZICI_VJESTACKE_INTELIGENCIJE_ANALIZA_I_IMPLIKACIJE.
2022
Braga, Juliao, Francisco Regateiro, Itana Stiubiener, and Juliana Cristina Braga. "Project for the Development of a Paper on Algorithm and Data Governance." OSF Preprints, September 2022. https://doi.org/10.31219/osf.io/sr7kt.
Braga, Juliao, Francisco Regateiro, Itana Stiubiener, and Juliana Cristina Braga. "Projeto para o desenvolvimento de um artigo sobre governança de algoritmos e dados." OSF Preprints, September 2022. https://doi.org/10.31219/osf.io/xcpsd.
Carmichael, Zachariah, and Walter J. Scheirer. “Unfooling Perturbation-Based Post Hoc Explainers.” arXiv preprint arXiv:2205.14772, 2022. https://doi.org/10.48550/arXiv.2205.14772.
Cinà, Antonio Emanuele, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard A. Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, and Fabio Roli. "Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning." arXiv, May 4, 2022. https://doi.org/10.48550/arXiv.2205.01992.
Durso, Francis, M. S. Raunak, D. Richard Kuhn, and Raghu Kacker. “Analyzing Failures in Artificial Intelligent Learning Systems (FAILS).” In 2022 IEEE 29th Annual Software Technology Conference (STC), 7–8. 2022. https://doi.org/10.1109/STC55697.2022.00010.
Felländer, Anna, Jonathan Rebane, Stefan Larsson, Mattias Wiggberg, and Fredrik Heintz. "Achieving a Data-Driven Risk Assessment Methodology for Ethical AI." Digital Society 1, no. 2 (2022): article 13, 1-27. https://doi.org/10.1007/s44206-022-00016-0.
Ferguson, Ryan. “Transform Your Risk Processes Using Neural Networks.” Presentation PDF, 2022. https://www.firm.fm/wp-content/uploads/2022/05/Papers-Round-Table-AI-April-2022.pdf.
Fujitsu Corporation. AI Ethics Impact Assessment Casebook. 2022. https://global.fujitsu/-/media/Project/Fujitsu/Fujitsu-HQ/technology/key-technologies/ai/PDF/fujitsu-aIethics-case_en.pdf.
Garner, Carrie. “Creating Transformative and Trustworthy AI Systems Requires a Community Effort.” Software Engineering Institute, 2022. https://www.sei.cmu.edu/blog/creating-transformative-and-trustworthy-ai-systems-requires-a-community-effort/.
Hundt, Andrew, William Agnew, Vicky Zeng, Severin Kacianka, and Matthew Gombolay. “Robots Enact Malignant Stereotypes.” In 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’22), 743–756. 2022. https://doi.org/10.1145/3531146.3533138.
Karunagaran, Surya, Ana Lucic, and Christine Custis. “XAI Toolsheet: Towards a Documentation Framework for XAI Tools.” IJCAI 2022 Workshop on Explainable Artificial Intelligence (XAI), 2022. https://www.researchgate.net/publication/390464429_XAI_Toolsheet_Towards_A_Documentation_Framework_for_XAI_Tools.
Kassab, Mohamad, Joanna F. DeFranco, and Phillip A. Laplante. “Investigating Bugs in AI-Infused Systems: Analysis and Proposed Taxonomy.” In 2022 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), 365–370. 2022. https://doi.org/10.1109/ISSREW55968.2022.00094.
Macrae, Carl. “Learning from the failure of autonomous and intelligent systems: Accidents, safety, and sociotechnical sources of risk.” Risk Analysis 42, no. 9 (2022): 1999–2025. https://doi.org/10.1111/risa.13850.
McGrath, Quintin P. “An Enterprise Risk Management Framework to Design Pro-Ethical AI Solutions.” PhD diss., University of South Florida, 2022. https://digitalcommons.usf.edu/etd/9793/.
McGregor, Sean, Kevin Paeth, and Khoa Lam. “Indexing AI Risks with Incidents, Issues, and Variants.” arXiv preprint arXiv:2211.10384, 2022. https://doi.org/10.48550/arXiv.2211.10384.
Naja, Iman, Milan Markovic, Pete Edwards, Wei Pang, Caitlin Cottrill, and Rebecca Williams. "Using Knowledge Graphs to Unlock Practical Collection, Integration, and Audit of AI Accountability Information." IEEE Access 10 (2022): 74383-74411. https://doi.org/10.1109/ACCESS.2022.3188967.
Neretin, Oleksii, and Vyacheslav Kharchenko. “Model for Describing Processes of AI Systems Vulnerabilities Collection and Analysis using Big Data Tools.” In 2022 12th International Conference on Dependable Systems, Services and Technologies (DESSERT), 2022. https://doi.org/10.1109/DESSERT58054.2022.10018811.
Nor, Ahmad Kamal Mohd, Srinivasa Rao Pedapati, Masdi Muhammad, and Víctor Leiva. "Abnormality Detection and Failure Prediction Using Explainable Bayesian Deep Learning: Methodology and Case Study of Real-World Gas Turbine Anomalies." Preprints, January 2022. https://doi.org/10.20944/preprints202109.0034.v3.
Petersen, Eike, Yannik Potdevin, Esfandiar Mohammadi, Stephan Zidowitz, Sabrina Breyer, Dirk Nowotka, Sandra Henn, Ludwig Pechmann, Martin Leucker, Philipp Rostalski, and Christian Herzog. "Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions." IEEE Access 10 (2022): 58375-58418. https://doi.org/10.1109/ACCESS.2022.3178382.
Pletcher, Scott Nicholas. "Visual Privacy: Current and Emerging Regulations around Unconsented Video Analytics in Retail." OSF Preprints, December 2022. https://doi.org/10.31219/osf.io/tfw96.
Salih, Salih. “Understanding Machine Learning Interpretability.” Medium, 2022. https://medium.com/data-science/understanding-machine-learning-interpretability-168fd7562a1a.
Schröder, Tim, and Michael Schulz. “Monitoring machine learning models: A categorization of challenges and methods.” Data Science and Management 5, no. 3 (2022): 105–116. https://doi.org/10.1016/j.dsm.2022.07.004.
Schuett, Jonas. “Three lines of defense against risks from AI.” arXiv preprint arXiv:2212.08364, 2022. https://arxiv.org/abs/2212.08364.
Secchi, Carlo, and Alessandro Gili, eds. Digitalisation for Sustainable Infrastructure: The Road Ahead. Ledizioni, 2022. https://www.ledipublishing.com/book/9788855267908/digitalisation-for-sustainable-infrastructure-the-road-ahead/.
Shneiderman, Ben. Human-Centered AI. Oxford University Press, 2022. https://global.oup.com/academic/product/human-centered-ai-9780192845290.
Tidjon, Lionel Nganyewou, and Foutse Khomh. “Threat Assessment in Machine Learning based Systems.” arXiv preprint arXiv:2207.00091, 2022. https://arxiv.org/abs/2207.00091.
Wei, Mengyi, and Zhixuan Zhou. “AI Ethics Issues in Real World: Evidence from AI Incident Database.” arXiv preprint arXiv:2206.07635, 2022. https://arxiv.org/abs/2206.07635.
Weissinger, Laurin. “AI, Complexity, and Regulation.” In The Oxford Handbook of AI Governance, 2022. https://doi.org/10.1093/oxfordhb/9780197579329.013.66.
Xie, Xuan, Kristian Kersting, and Daniel Neider. “Neuro-Symbolic Verification of Deep Neural Networks.” arXiv preprint arXiv:2203.00938, 2022. https://arxiv.org/abs/2203.00938.
2021
Aliman, Nadisha Marie, and Leon Kester. “Epistemic defenses against scientific and empirical adversarial AI attacks.” In CEUR Workshop Proceedings, vol. 2916, 2021. https://ceur-ws.org/Vol-2916/paper_1.pdf.
Aliman, Nadisha-Marie, Leon Kester, and Roman Yampolskiy. “Transdisciplinary AI Observatory—Retrospective Analyses and Future-Oriented Contradistinctions.” Philosophies 6, no. 1 (2021): 6. https://doi.org/10.3390/philosophies6010006.
Arnold, Zachary, and Helen Toner. AI Accidents: An Emerging Threat: What Could Happen and What to Do. Center for Security and Emerging Technology, July 2021. https://doi.org/10.51593/20200072.
Falco, Gregory, and Leilani H. Gilpin. “A Stress Testing Framework for Autonomous System Verification and Validation (V&V).” In 2021 IEEE International Conference on Autonomous Systems (ICAS), 2021. https://doi.org/10.1109/ICAS49788.2021.9551154.
Hong, Matthew K., Adam Fourney, Derek DeBellis, and Saleema Amershi. “Planning for Natural Language Failures with the AI Playbook.” In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, article 386, 1–11. 2021. https://doi.org/10.1145/3411764.3445735.
John-Mathews, Jean-Marie. L’Éthique de l’Intelligence Artificielle en Pratique: Enjeux et Limites [AI Ethics in Practice: Challenges and Limitations]. PhD diss., Université Paris-Saclay, 2021. https://theses.fr/2021UPASI015.
Kalin, Josh, David Noever, Matthew Ciolino, and Gerry Dozier. “A Modified Drake Equation for Assessing Adversarial Risk to Machine Learning Models.” Computer Science & Information Technology 11 (2021): 1–9. https://doi.org/10.5121/csit.2021.111001.
Paudel, Shreyasha, and Aatiz Ghimire. AI Ethics Survey in Nepal. Lalitpur, Nepal: Nepal Applied Mathematics and Informatics Institute, 2021. https://web.archive.org/web/20260124104706/https://naamii.org/wp-content/uploads/2021/11/AI-Ethics-Survey-Report.pdf.
Ruohonen, Jukka. “A Review of Product Safety Regulations in the European Union.” arXiv preprint arXiv:2102.03679, 2021. https://arxiv.org/abs/2102.03679.
Smith, Catherine. “Automating intellectual freedom: Artificial intelligence, bias, and the information landscape.” IFLA Journal 48, no. 3 (2022): 422–431. Published online December 7, 2021. https://doi.org/10.1177/03400352211057145.
2020
McGregor, Sean. “Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database.” arXiv preprint arXiv:2011.08512, November 17, 2020. https://doi.org/10.48550/arXiv.2011.08512.
McGregor, Sean. “When AI Systems Fail: Introducing the AI Incident Database.” Partnership on AI, November 18, 2020. https://partnershiponai.org/aiincidentdatabase/.
Government
Canada
Canadian Centre for Cyber Security. National Cyber Threat Assessment 2025–2026. 2024. https://www.cyber.gc.ca/en/guidance/national-cyber-threat-assessment-2025-2026.
Policy Horizons Canada. Foresight on AI: Policy considerations. February 10, 2025. https://horizons.service.canada.ca/en/2025/02/10/ai-policy-consideration/index.shtml.
Europe — Public-Sector and EU-Hosted Project Materials
Venturi, Giulia, Maria Ustenko, Claudio Testani, and Giulia Treossi. D5.3 Monitoring of EU Research and Horizon Scanning – v2. NOTIONES deliverable, October 28, 2022. European Commission–hosted project document. https://ec.europa.eu/research/participants/documents/downloadPublic?appId=PPGMS&documentIds=080166e5f31e7a5b.
Romania — Strategy Project Materials
Groza, Adrian, George Bara, Cristina Belba, Aurelian Ionescu, Marian Iurian, Camelia Lemnaru, Luciana Morogan, and Eugen Popescu. Elaborarea cadrului strategic național în domeniul inteligenței artificiale: Analiza reglementărilor pentru domeniul inteligenței artificiale. December 21, 2021. https://strategie-ia.utcluj.ro/docs/POCA_CSN-IA_Analiza_reglement%C4%83rilor_pentru_domeniul%20inteligentei_artificiale.pdf.
Belba, Cristina, Cristina Catai, Aurelia Ciupe, Claudia Cordoș, Adina Dragoman, Adina Florea, Adrian Groza, Sorin Hintea, Aurelian Ionescu, Alexandru Lazarec, Camelia Lemnaru, Raul Măluțan, Liviu Miclea, Laura Mihăilă, Luciana Morogan, Eugen Popescu, Gabriel Prefac, Gabriel Oltean, Alina Pârăială, Adriana Stan, Cozet Șerban, and Honoriu Vălean. Cadrul strategic național în domeniul inteligenței artificiale 2023–2027. Version 28 iulie 2023. Autoritatea pentru Digitalizarea României and Universitatea Tehnică din Cluj-Napoca, 2023. https://www.mcid.gov.ro/wp-content/uploads/2023/10/Propunere-Cadru-Strategic-National-IA-.pdf.
International / Intergovernmental
International AI Safety Report. International AI Safety Report 2026. Department for Science, Innovation and Technology, February 3, 2026. DSIT 2026/001. https://internationalaisafetyreport.org/publication/international-ai-safety-report-2026.
OECD. Stocktaking for the Development of an AI Incident Definition. OECD Artificial Intelligence Papers, 2023. https://www.oecd.org/content/dam/oecd/en/publications/reports/2023/10/stocktaking-for-the-development-of-an-ai-incident-definition_64c69a10/c323ac71-en.pdf.
OECD. Towards a Common Reporting Framework for AI Incidents. OECD Artificial Intelligence Papers, 2025. https://www.oecd.org/content/dam/oecd/en/publications/reports/2025/02/towards-a-common-reporting-framework-for-ai-incidents_8c488fdb/f326d4ac-en.pdf.
Multinational
Canadian Nuclear Safety Commission, Office for Nuclear Regulation, and U.S. Nuclear Regulatory Commission. Considerations for Developing Artificial Intelligence Systems in Nuclear Applications. September 2024. https://www.nrc.gov/docs/ML2424/ML24241A252.pdf.
United Kingdom
AI Security Institute. “Examples of systemic AI safety projects.” AI Security Institute, n.d. https://www.aisi.gov.uk/grants/example-projects.
Competition and Markets Authority. AI Foundation Models: Technical Update Report. April 16, 2024. https://assets.publishing.service.gov.uk/media/661e5a4c7469198185bd3d62/AI_Foundation_Models_technical_update_report.pdf.
Department for Science, Innovation and Technology. Emerging Processes for Frontier AI Safety. Policy paper. October 27, 2023. https://www.gov.uk/government/publications/emerging-processes-for-frontier-ai-safety.
Law Commission. AI and the Law: Discussion Paper. July 21, 2025. https://cdn.websitebuilder.service.justice.gov.uk/uploads/sites/54/2025/07/AI-paper-PDF.pdf.
United States — Agencies and Public Bodies
Maryland Health Care Commission. “A Survey of AI Incidents and Malpractice.” Health Care Artificial Intelligence Symposium presentation, Spring 2025. https://mhcc.maryland.gov/mhcc/pages/hit/hit/documents/ai_incidents_malpractice.pdf.
National Institute of Standards and Technology (NIST). Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile. NIST AI 600-1. July 2024. https://doi.org/10.6028/NIST.AI.600-1.
Rao, Anita, Drew Keller, Neha Kalra, Ryan Steed, Kweku Kwegyir-Aggrey, Kevin Klyman, Diane Staheli, and Stevie Bergman. Challenges to the Monitoring of Deployed AI Systems. NIST AI 800-4. Gaithersburg, MD: National Institute of Standards and Technology, March 2026. https://doi.org/10.6028/NIST.AI.800-4.
National Institute of Standards and Technology (NIST). “Govern.” NIST AI RMF Playbook, n.d. https://airc.nist.gov/airmf-resources/playbook/govern/.
National Institute of Standards and Technology (NIST). “Manage.” NIST AI RMF Playbook, n.d. https://airc.nist.gov/airmf-resources/playbook/manage/.
National Institute of Standards and Technology (NIST). “Measure.” NIST AI RMF Playbook, n.d. https://airc.nist.gov/airmf-resources/playbook/measure/.
Schwartz, Reva, Apostol Vassilev, Kristen Greene, Lori Perine, Andrew Burt, and Patrick Hall. Towards a Standard for Identifying and Managing Bias in Artificial Intelligence. NIST Special Publication 1270. 2022. https://doi.org/10.6028/NIST.SP.1270.
U.S. Consumer Product Safety Commission. Meeting Log: UL Research Institute’s Digital Safety Research Institute Meeting. Filed July 31, 2023. https://www.cpsc.gov/s3fs-public/UL-DSRI-Meeting-Log.pdf?VersionId=Q6CNGM1QxObwUsRxTZotnF0KjJ0f98g1.
U.S. Department of Homeland Security. Impact of Artificial Intelligence on Criminal and Illicit Activities. 2024. https://www.dhs.gov/sites/default/files/2024-10/24_0927_ia_aep-impact-ai-on-criminal-and-illicit-activities.pdf.
U.S. Nuclear Regulatory Commission. 09/19/2023 NRC Public AI Workshop Presentation. September 19, 2023. https://www.nrc.gov/docs/ML2324/ML23249A070.pdf.
United States — Congressional Hearing Materials
Krishnan, Ramayya. “Testimony Before the Subcommittee on Consumer Protection, Product Safety, and Data Security, Senate Committee on Commerce, Science, and Transportation, Hearing Entitled ‘The Need for Transparency in Artificial Intelligence.’” September 12, 2023. https://www.commerce.senate.gov/services/files/96B6B41C-9335-43AF-9DB1-1231AF66C493.
Vallor, Shannon. “Testimony of Prof. Shannon Vallor.” For the U.S. Senate Committee on Homeland Security and Governmental Affairs. November 8, 2023. https://www.hsgac.senate.gov/wp-content/uploads/Testimony-Vallor-2023-11-08.pdf.
Journalism
2026
Berman, Michael. “‘The AI Incident Database.’” E-Discovery LLC, June 19, 2026. https://www.ediscoveryllc.com/the-ai-incident-database/.
Austin, Doug. “The AI Incident Database: Artificial Intelligence Trends.” eDiscovery Today, June 9, 2026. https://ediscoverytoday.com/2026/06/09/the-ai-incident-database-artificial-intelligence-trends/.
Atherton, Daniel. “AI Incident Roundup – February, March, and April 2026.” AI Incident Database Blog, May 5, 2026. https://incidentdatabase.ai/blog/incident-report-2026-february-march-april/.
Clearwater, Andrew. “The AI Governance Stack Has Holes in It.” Andrew Clearwater, May 4, 2026. https://andrewclearwater.substack.com/p/the-ai-governance-stack-has-holes.
Guaglione, Sara. “The Rise of Deepfakes Poses a New Trust Challenge for Publishers.” Digiday, April 29, 2026. https://digiday.com/media/the-rise-of-deepfakes-poses-a-new-trust-challenge-for-publishers/.
José, Pedro, and Caetano Yamamoto. “Perdas com deepfake custam US$ 2 bilhões.” Correio Braziliense, April 26, 2026. https://www.correiobraziliense.com.br/economia/2026/04/7406124-perdas-com-deepfake-custam-uss-2-bilhoes.html.
Santoro, Michael A. “The Denominator Problem in AI Governance.” Tech Policy Press, April 24, 2026. https://www.techpolicy.press/the-denominator-problem-in-ai-governance/.
Rijo, Luis. “Most AI Harm Comes from Software, Not Robots, 1,400 Incidents Show.” PPC Land, April 23, 2026. https://ppc.land/most-ai-harm-comes-from-software-not-robots-1-400-incidents-show/.
Rachlevičius, Vidas. “V. Rachlevičius: DI – lyg nuogi į dilgėles. Žmogus privalo likti sprendimų priėmimo grandinėje.” Alkas.lt, March 21, 2026. https://alkas.lt/2026/03/21/v-rachlevicius-di-lyg-nuogi-i-dilgeles-zmogus-privalo-likti-sprendimu-priemimo-grandineje/.
Rajan, Kaushik Sunder. “The Math That’s Killing Your AI Agent.” Towards Data Science, March 20, 2026. https://towardsdatascience.com/the-math-thats-killing-your-ai-agent/.
cognitronn. “Почему врачам, юристам и аналитикам нельзя доверять ИИ длинные документы.” Habr, March 19, 2026. https://habr.com/ru/companies/bothub/articles/1012078/.
Gupta, Lakshmi Pillai. “AI Is Entering the State Before Society Is Ready.” The Times of India, March 19, 2026. https://timesofindia.indiatimes.com/blogs/equal-bytes/ai-is-entering-the-state-before-society-is-ready/.
Maghirang, Tony. “Deepfakes and the Real-World Harms Wrought by AI.” The Manila Times, March 15, 2026. https://www.manilatimes.net/2026/03/15/business/sunday-business-it/deepfakes-and-the-real-world-harms-wrought-by-ai/2300023.
The Daily Blog. “GUEST BLOG: Talk Liberation – Surprise! Humans Left To Clean Up AI Messes.” March 14, 2026. https://thedailyblog.co.nz/guest-blog-talk-liberation-surprise-humans-left-to-clean-up-ai-messes/.
PointGuard AI. “PointGuard AI Launches AI Security Incident Tracker for Agentic Threats.” Press release, February 19, 2026. https://www.freep.com/press-release/story/156167/pointguard-ai-launches-ai-security-incident-tracker-for-agentic-threats/.
Guest Writer. “The Era of ‘Seeing Is Believing’ Is Over Thanks to a Rise in Deepfake Fraud.” Prolific North, February 18, 2026. https://www.prolificnorth.co.uk/feature/the-era-of-seeing-is-believing-is-over-thanks-to-a-rise-in-deepfake-fraud/.
Schwartz, Eric Hal. “‘The World Is in Peril’ — 5 Reasons Why the AI Apocalypse Might Be Closer Than You Think.” TechRadar, February 16, 2026. https://www.techradar.com/ai-platforms-assistants/the-world-is-in-peril-5-reasons-why-the-ai-apocalypse-might-be-closer-than-you-think.
Perras, Sarah. “Deepfake Fraud Goes Mainstream.” Impakter, February 13, 2026. https://impakter.com/deepfake-fraud-goes-mainstream/.
Nolan, Lucas. “Analysis: Deepfake Fraud Explodes as AI Tools Become Widely Accessible.” Breitbart, February 10, 2026. https://www.breitbart.com/tech/2026/02/10/analysis-deepfake-fraud-explodes-as-ai-tools-become-widely-accessible/.
Gibson, Jonathan. “Why AI Makes Believing the Truth Harder.” The Dispatch, February 9, 2026. https://thedispatch.com/article/artificial-intelligence-meta/.
TechCentral.ie. “Deepfake Fraud Is Increasingly Widespread, According to Study.” February 9, 2026. https://www.techcentral.ie/deepfake-fraud-is-increasingly-widespread-according-to-study/.
Down, Aisha. “Deepfake Fraud Taking Place on an Industrial Scale, Study Finds.” The Guardian, February 6, 2026. https://www.theguardian.com/technology/2026/feb/06/deepfake-taking-place-on-an-industrial-scale-study-finds.
Mendonça, Eduardo. “Fraudes com deepfake se tornam comuns em escala industrial, alertam especialistas.” Brasil em Folhas, February 6, 2026. https://www.brasilemfolhas.com.br/2026/02/fraudes-com-deepfake-se-tornam-comuns-em-escala-industrial-alertam-especialistas/.
Price, Chris. “Deepfake Fraud on ‘Industrial Scale’ as Barriers to Entry Disappear.” Tech Digest, February 6, 2026. https://www.techdigest.tv/2026/02/deepfake-fraud-on-industrial-scale-as-barriers-to-entry-disappear.html.
Scaliter, Juan. “Las cifras indican que el deepfake ya es una industria global del engaño.” La Razón, February 6, 2026. https://www.larazon.es/tecnologia/cifras-indican-que-deepfake-industria-global-engano_2026020669862ef09243cc133c374b4a.html.
Tahir, Aqsa Qaddus. “Deepfake Fraud Goes Industrial: How AI Scams Are Scaling Globally in 2026.” The News International, February 6, 2026. https://www.thenews.com.pk/latest/1391321-deepfake-fraud-goes-industrial-how-ai-scams-are-scaling-globally-in-2026.
Atherton, Daniel. “AI Incident Roundup – November and December 2025 and January 2026.” AI Incident Database Blog, February 2, 2026. https://incidentdatabase.ai/blog/incident-report-2025-november-december-2026-january/.
Surfshark. “Facebook Led in Deepfake-Related Fraud in 2025.” January 27, 2026. https://surfshark.com/research/chart/deepfake-social-media-fraud.
Trustible. “Trustible Leads Inaugural Sponsor Cohort for the AI Incident Database.” PR Newswire, January 26, 2026. https://www.prnewswire.com/news-releases/trustible-leads-inaugural-sponsor-cohort-for-the-ai-incident-database-302669167.html.
McGregor, Sean. “Funding the AIID - Part I.” AI Incident Database Blog, January 25, 2026. https://incidentdatabase.ai/blog/funding-the-aiid-part-1/.
Corvin, Ann-Marie. “This Will Get You Hacked: Trusting AI Deepfakes, Pop-Ups, Fake Security Alerts, and Evolving Malware.” Cybernews, January 23, 2026. https://cybernews.com/security/trusting-ai-deepfakes-pop-ups-evolving-malware/.
Zee. “AI Incidents Reached 346 Reported Cases in 2025, AI Incident Database Says.” TechRound, January 22, 2026. https://techround.co.uk/news/ai-incidents-2025-ai-incident-database/.
Booth, Harry. “What the Numbers Show About AI’s Harms.” TIME, January 19, 2026. https://time.com/7346091/ai-harm-risk/.
Cybernews Team. “346 AI Incidents in 2025 – from Deepfakes and Fraud to Dangerous Advice.” Cybernews, January 19, 2026. https://cybernews.com/ai-news/346-ai-incidents-in-2025-from-deepfakes-and-fraud-to-dangerous-advice/.
Peek, Katie. “What Experts Can Learn by Tracking AI Harms.” Bulletin of the Atomic Scientists, January 16, 2026. https://thebulletin.org/2026/01/what-experts-can-learn-by-tracking-ai-harms/.
2025
Jain, Samiksha. “Social Media Flooded with Ghibli AI Images—But What Are We Really Feeding the Algorithms?” The Cyber Express, November 20, 2025. https://thecyberexpress.com/social-media-flooded-with-ghibli-ai-images/.
Ibeh, Royal. “Deepfake Fraud Losses Soar to $1.56bn as Cheap AI Tools Fuel Global Crime Wave.” BusinessDay, November 17, 2025. https://businessday.ng/technology/article/deepfake-fraud-losses-soar-to-1-56bn-as-cheap-ai-tools-fuel-global-crime-wave/.
Jeanmaire, Caroline, and Sam Boger. “AI Incidents Are Rising. It’s Time for the United States to Build Playbooks for When AI Fails.” The Future Society, November 12, 2025. https://thefuturesociety.org/us-ai-incident-response/.
Atherton, Daniel. “AI Incident Roundup – August, September, and October 2025.” AI Incident Database Blog, November 8, 2025. https://incidentdatabase.ai/blog/incident-report-2025-august-september-october/.
Surfshark. “AI Drives Deepfake Losses to $1.56 Billion.” October 21, 2025. https://surfshark.com/research/chart/ai-deepfake-losses.
Straight Arrow News. “Why Experts Are Worried About AI Safety.” September 2, 2025. https://san.com/cc/ai-safety-and-the-potential-apocalypse-what-people-can-do-now-to-prevent-it/.
Golbin-Blumenfeld, Ilana, Robert N. Bernard, and David De Lallo. “Quantifying the Value of Responsible AI.” PwC, August 7, 2025. https://www.pwc.com/gx/en/issues/technology/measuring-responsible-ai-value.html.
Atherton, Daniel. “AI Incident Roundup – June and July 2025.” AI Incident Database Blog, August 2, 2025. https://incidentdatabase.ai/blog/incident-report-2025-june-july/.
Fleischer-Black, Matt. “From CEO Deepfakes to AI Slop, AI Incident Tracking Ramps Up.” Cybersecurity Law Report, July 30, 2025. https://www.cslawreport.com/print_issue.thtml?uri=cyber-security-law-report/content/vol-11/no-30-jul-30-2025.
Netzpalaver. “Finanzielle Verluste durch Deepfake-Betrug erreichen fast 900 Millionen US-Dollar.” July 14, 2025. https://netzpalaver.de/2025/07/14/finanzielle-verluste-durch-deepfake-betrug-erreichen-fast-900-millionen-us-dollar/.
Surfshark. “Deepfake Fraud Caused Financial Losses Nearing $900 Million.” July 8, 2025. https://surfshark.com/research/chart/deepfake-fraud-losses.
Arroyo, Isaac. “When AI Goes Wrong.” The National, July 2, 2025. https://www.thenationalnews.com/news/2025/07/02/when-ai-goes-wrong/.
Atherton, Daniel. “AI Incident Roundup – April and May 2025.” AI Incident Database Blog, June 16, 2025. https://incidentdatabase.ai/blog/incident-report-2025-april-may/.
Surfshark. “Deepfake Statistics in Early 2025: How Frequently Are Famous People Targeted?” April 15, 2025. https://surfshark.com/research/study/deepfake-statistics.
Mylius, Simon. “Scalable AI Incident Classification.” AI Incident Database Blog, April 14, 2025. https://incidentdatabase.ai/blog/scalable-ai-incident-classification/.
Muzaffar, Aiman, Akshay Thirumal Reddy, and Daniel Bazargun. “Exploration of Entity Identification and Graph-based Relationship Curation in the AI Incident Database.” AI Incident Database Blog, April 3, 2025. https://incidentdatabase.ai/blog/entity-exploration-and-curation/.
Atherton, Daniel. “AI Incident Roundup – February and March 2025.” AI Incident Database Blog, April 3, 2025. https://incidentdatabase.ai/blog/incident-report-2025-february-march/.
Atherton, Daniel. “AI Incident Roundup – December 2024 and January 2025.” AI Incident Database Blog, February 3, 2025. https://incidentdatabase.ai/blog/incident-report-2024-december-2025-january/.
2024
Atherton, Daniel. “AI Incident Roundup – October and November 2024.” AI Incident Database Blog, December 7, 2024. https://incidentdatabase.ai/blog/incident-report-2024-october-november/.
Atherton, Daniel. “AI Incident Roundup – August and September 2024.” AI Incident Database Blog, October 5, 2024. https://incidentdatabase.ai/blog/incident-report-2024-august-september/.
Paeth, Kevin. “Submit Your AI Incident Research to IAAI!” AI Incident Database Blog, August 12, 2024. https://incidentdatabase.ai/blog/submit-your-ai-incident-research-to-iaai-25/.
Atherton, Daniel. “AI Incident Roundup – July 2024.” AI Incident Database Blog, August 12, 2024. https://incidentdatabase.ai/blog/incident-report-2024-july/.
Chen, Sherry, Steven Shen, and Shyam Sivasubramanian. “Cluster Analysis of AI Incident Journalism.” AI Incident Database Blog, July 22, 2024. https://incidentdatabase.ai/blog/ai-incident-journalism-analysis/.
Atherton, Daniel. “AI Incident Roundup – June 2024.” AI Incident Database Blog, July 8, 2024. https://incidentdatabase.ai/blog/incident-report-2024-june/.
Rahman, Nushrat, and Arpan Lobo. “Deepfakes: What They Are and How to Protect Yourself.” Detroit Free Press, July 3, 2024. https://www.freep.com/story/news/local/michigan/2024/07/03/deepfakes-what-they-are-and-how-to-protect-yourself/74192319007/.
Oikawa, Akira. “世界中と連携 技術悪用防ぐ [Collaborating with the World to Prevent Technological Risks].” The Nikkei, June 17, 2024. https://www.nikkei.com/article/DGXZQOUC2829W0Y4A320C2000000/.
Surfshark. “One in Five AI Incidents Relates to Elections.” June 17, 2024. https://surfshark.com/research/chart/election-related-ai-incidents.
Atherton, Daniel. “AI Incident Roundup – May 2024.” AI Incident Database Blog, June 7, 2024. https://incidentdatabase.ai/blog/incident-report-2024-may/.
Ruhl, Christian. “The U.S. and China Need an AI Incidents Hotline.” Lawfare, June 3, 2024. https://www.lawfaremedia.org/article/the-u.s.-and-china-need-an-ai-incidents-hotline.
Atherton, Daniel. “AI Incident Roundup – April ’24.” AI Incident Database Blog, May 7, 2024. https://incidentdatabase.ai/blog/incident-report-2024-april/.
Atherton, Daniel. “AI Incident Roundup – March ’24.” AI Incident Database Blog, April 5, 2024. https://incidentdatabase.ai/blog/incident-report-2024-march/.
Schwartz, Janet. “AI Incident Roundup – February ’24.” AI Incident Database Blog, March 7, 2024. https://incidentdatabase.ai/blog/incident-report-2024-february/.
TheCollab Board of Directors. “Researching AI Incidents to Build a Safer Future: The Digital Safety Research Institute partners with the Responsible AI Collaborative.” AI Incident Database Blog, February 20, 2024. https://incidentdatabase.ai/blog/researching-ai-incidents-to-build-a-safer-future/.
Schwartz, Janet. “AI Incident Roundup – January ’24.” AI Incident Database Blog, February 8, 2024. https://incidentdatabase.ai/blog/incident-report-2024-january/.
Dubiniecki, Abigail. “Trustworthy AI: String of AI Fails Show Self-Regulation Doesn’t Work.” Forbes, January 25, 2024. https://www.forbes.com/sites/abigaildubiniecki/2024/01/25/trustworthy-ai-string-of-ai-fails-show-self-regulation-doesnt-work/.
Goldstein, Josh A., and Andrew Lohn. “Deepfakes, Elections, and Shrinking the Liar’s Dividend.” Brennan Center for Justice, January 23, 2024. https://www.brennancenter.org/our-work/research-reports/deepfakes-elections-and-shrinking-liars-dividend.
Atherton, Daniel. “Deepfakes and Child Safety: A Survey and Analysis of 2023 Incidents and Responses.” AI Incident Database Blog, January 9, 2024. https://incidentdatabase.ai/blog/deepfakes-and-child-safety-a-survey-and-analysis-of-2023-incidents-and-responses/.
2023
Leong, Brenda, and Daniel Atherton. “AI Incident Response Plans: Not Just for Security Anymore.” IAPP, September 20, 2023. https://iapp.org/news/a/ai-incident-response-plans-not-just-for-security-anymore.
Hsu, Tiffany. “What Can You Do When A.I. Lies About You?” The New York Times, August 3, 2023. https://www.nytimes.com/2023/08/03/business/media/ai-defamation-lies-accuracy.html.
Cambo, Scott. “Submit Your AI Incident Research to IAAI!” AI Incident Database Blog, July 19, 2023. https://incidentdatabase.ai/blog/submit-your-ai-incident-research-to-iaai/.
Schwartz, Janet, and Khoa Lam. “AI Incident Roundup – May & June ’23.” AI Incident Database Blog, July 18, 2023. https://incidentdatabase.ai/blog/incident-report-2023-may-june/.
Ramel, David. “Scientists Seek Government Database to Track Harm from Rising ‘AI Incidents.’” Virtualization Review, July 17, 2023. https://virtualizationreview.com/articles/2023/07/17/ai-incidents-db.aspx.
Surfshark. “A Third of All AI Incidents Since 2010 Linked to 5 Companies.” July 4, 2023. https://surfshark.com/research/chart/ai-incidents-of-companies.
Thomas, Jack. “2023 Poised to Shatter Records with Skyrocketing AI Incidents.” Innovation News Network, June 30, 2023. https://www.innovationnewsnetwork.com/2023-poised-to-shatter-records-with-skyrocketing-ai-incidents/34373/.
Surfshark. “The Start of This Decade Marks a Sharp Rise in AI Incidents.” June 27, 2023. https://surfshark.com/research/chart/statistics-of-ai-incidents.
Atherton, Daniel, Khoa Lam, Kate Perkins, and Janet Schwartz. “Editor’s Story - Keeping the AI Incidents Fresh.” AI Incident Database Blog, May 16, 2023. https://incidentdatabase.ai/blog/editors-story/.
Shrishak, Kris. “How to Deal with an AI Near-Miss: Look to the Skies.” Bulletin of the Atomic Scientists, May 9, 2023. https://thebulletin.org/premium/2023-05/how-to-deal-with-an-ai-near-miss-look-to-the-skies/.
Schwartz, Janet, and Khoa Lam. “AI Incident Roundup – April ’23.” AI Incident Database Blog, May 24, 2023. https://incidentdatabase.ai/blog/incident-report-2023-april/.
Colton, Emma. “Bias, Deaths, Autonomous Cars: Expert Says AI ‘Incidents’ Will Double as Silicon Valley Launches Tech Race.” Fox News, April 25, 2023. https://www.foxnews.com/tech/bias-deaths-autonomous-cars-expert-says-ai-incidents-double-silicon-valley-launches-tech-race.
Minto, Rob. “AI Accidents Are Set to Skyrocket This Year.” Newsweek, April 23, 2023. https://www.newsweek.com/ai-accidents-set-skyrocket-this-year-1795928.
Schwartz, Janet, and Khoa Lam. “AI Incident Roundup – March ’23.” AI Incident Database Blog, April 14, 2023. https://incidentdatabase.ai/blog/incident-report-2023-march/.
McGregor, Sean. “How to Understand Large Language Models through Improv.” AI Incident Database Blog, March 28, 2023. https://incidentdatabase.ai/blog/improv-ai/.
Schwartz, Janet, and Khoa Lam. “AI Incident Roundup – February ’23.” AI Incident Database Blog, March 20, 2023. https://incidentdatabase.ai/blog/incident-report-2023-february/.
Lam, Khoa. “ChatGPT Incidents and Issues.” AI Incident Database Blog, March 7, 2023. https://incidentdatabase.ai/blog/chatgpt-incidents-and-issues/.
Schwartz, Janet, and Khoa Lam. “AI Incident Roundup – January ’23.” AI Incident Database Blog, February 28, 2023. https://incidentdatabase.ai/blog/incident-report-2023-january/.
Schwartz, Janet, and Khoa Lam. “AI Incident Roundup – December ’22.” AI Incident Database Blog, January 16, 2023. https://incidentdatabase.ai/blog/incident-report-2022-december/.
Schwartz, Janet. “User Story Spotlight: Subscriptions and eNewsletter.” AI Incident Database Blog, January 6, 2023. https://incidentdatabase.ai/blog/user-story-spotlight-subscriptions-and-enewsletter/.
2022
Taylor, Dan. “Helping Keep Quality in AI Industry Job One, Giskard Raises €1.5 Million.” Tech.eu, December 15, 2022. https://tech.eu/2022/12/15/helping-keep-quality-in-ai-industry-job-one-giskard-raises-eur15-million/.
Schwartz, Janet. “Introducing AI Incident Responses.” AI Incident Database Blog, December 15, 2022. https://incidentdatabase.ai/blog/introducing-ai-incident-responses/.
Schwartz, Janet, and Khoa Lam. “AI Incident Roundup – November ’22.” AI Incident Database Blog, December 15, 2022. https://incidentdatabase.ai/blog/incident-report-2022-november/.
McGregor, Sean, Kevin Paeth, and Khoa Lam. “Indexing AI Risks with Incidents, Issues, and Variants.” AI Incident Database Blog, December 9, 2022. https://incidentdatabase.ai/blog/incidents-issues-variants/.
Schwartz, Janet, and Khoa Lam. “AI Incident Roundup – October ’22.” AI Incident Database Blog, November 14, 2022. https://incidentdatabase.ai/blog/incident-report-2022-october/.
Schwartz, Janet, and Khoa Lam. “AI Incident Roundup for September 2022.” AI Incident Database Blog, October 17, 2022. https://incidentdatabase.ai/blog/incident-report-2022-september/.
Schwartz, Janet. “User Story Spotlights: Behind the Scenes of Database Developments.” AI Incident Database Blog, September 30, 2022. https://incidentdatabase.ai/blog/user-story-spotlights-database-developments/.
Schwartz, Janet. “AI Incident Report for July and August 2022.” AI Incident Database Blog, September 12, 2022. https://incidentdatabase.ai/blog/incident-report-2022-july-august/.
McGregor, Sean, and Cesar Varela. “Multilingual Incident Reporting.” AI Incident Database Blog, August 11, 2022. https://incidentdatabase.ai/blog/multilingual-incident-reporting/.
Broce, Nicholas, Nicholas Olson, and Jason Scott-Hakanson. “Using AI to Connect AI Incidents.” AI Incident Database Blog, August 4, 2022. https://incidentdatabase.ai/blog/using-ai-to-connect-ai-incidents/.
Schwartz, Janet. “RAIC Holds First All-Hands Meeting.” AI Incident Database Blog, July 20, 2022. https://incidentdatabase.ai/blog/raic-holds-first-all-hands-meeting/.
Responsible AI Collaborative. “Join the Responsible AI Collaborative Founding Staff.” AI Incident Database Blog, March 29, 2022. https://incidentdatabase.ai/blog/join-raic/.
2021
McGregor, Sean. “Representation and Imagination for Preventing AI Harms.” AI Incident Database Blog, November 24, 2021. https://incidentdatabase.ai/blog/representation-and-imagination/.
McGregor, Sean. “The First Taxonomy of AI Incidents.” AI Incident Database Blog, July 8, 2021. https://incidentdatabase.ai/blog/the-first-taxonomy-of-ai-incidents/.
Simonite, Tom. “Don’t End Up on This Artificial Intelligence Hall of Shame.” WIRED, June 3, 2021. https://www.wired.com/story/artificial-intelligence-hall-shame/.
Albarino, Seyma. “AI Incident Database Spotlights Worst Machine Translation Fails.” Slator, February 9, 2021. https://slator.com/ai-incident-database-spotlights-worst-machine-translation-fails/.
TechTalkThai. “รู้จัก AI Incident Database แหล่งรวมข้อมูลปัญหาที่เคยเกิดขึ้นกับระบบ AI สำหรับใช้เป็นกรณีศึกษา.” January 18, 2021. https://www.techtalkthai.com/introduce-ai-incident-database/.
Dickson, Ben. “The AI Incident Database Wants to Improve the Safety of Machine Learning.” VentureBeat, January 15, 2021. https://venturebeat.com/2021/01/15/the-ai-incident-database-wants-to-improve-the-safety-of-machine-learning/.
2020
DeepLearning.AI. “Cataloging AI Gone Wrong: The AI Incident Database Tracks Machine Learning Mistakes.” The Batch, December 2, 2020. https://www.deeplearning.ai/the-batch/cataloging-ai-gone-wrong.
Clark, Jack. “Import AI 226: AlphaFold; a Chinese GPT2; Timnit Gebru Leaves Google.” Import AI, December 7, 2020. https://jack-clark.net/2020/12/07/import-ai-226-alphafold-a-chinese-gpt2-timnit-gebru-leaves-google/.
Ferdowsi, Samir. “This Database Is Finally Holding AI Accountable.” VICE, November 23, 2020. https://www.vice.com/en/article/this-database-is-finally-holding-ai-accountable/.
About and Methodology
This section explains how The AI Incident Database in the Literature and Public Record is maintained. The bibliography currently contains 622 entries.
Purpose and Status
This bibliography is an experimental public research resource. It is designed to make AIID's footprint in research, governance, standards, journalism, and the broader public record easier to inspect. It is not a comprehensive citation index, a measure of influence, or an endorsement of any listed source. Records may contain errors or become outdated as publications, repositories, and web pages change.
Inclusion Standard
A work is included when the source itself shows an identifiable relationship to AIID. Qualifying relationships include a reference-list citation, substantive use of AIID data or incidents, discussion or criticism of the database, incorporation of AIID-derived taxonomies or visualizations, or direct reporting about AIID. Search-result snippets are treated only as discovery leads. Incidental keyword matches, unverified references, scraped copies without independent editorial content, and sources whose relationship to AIID cannot be confirmed are excluded.
Version and Record Policy
The bibliography normally maintains one record for each intellectual work. When a preprint later appears as a journal article, conference paper, book chapter, or other version of record, the formal publication is preferred and the earlier version is removed unless it remains materially distinct. Separate public artifacts may be retained when they have independent value, such as a formal paper and a separately authored explanatory essay. Canonical DOI or publisher links are preferred over repository mirrors when they are available and stable.
Publication Years and Source Types
Formal publications are assigned to the year of the version of record. Preprints are assigned to the year of their first public release. Journalism and other web publications follow the date stated by the publisher. Citation-type labels are editorial browsing aids; when the available evidence does not support a confident classification, the record remains unbadged.
Discovery and Verification
Candidates are identified through targeted web searches, scholarly indexes, citation chaining, publisher and repository searches, reference lists, standards catalogues, reader submissions, and periodic review of recent AI incident scholarship. Before inclusion, the title, authorship, date, publication venue, persistent identifier, link target, and relationship to AIID are compared with the source itself and with existing records. Publisher pages, DOI records, official repositories, standards bodies, and preserved source files are preferred over secondary summaries.
AI Assistance and Editorial Review
Automated systems, including large language models, may assist with candidate discovery, title matching, metadata comparison, duplicate detection, citation normalization, structural checks, and document production. Automated output is not treated as evidence. Additions, removals, and corrections require source-level review before publication. AI assistance does not guarantee completeness or correctness.
Technical and Editorial Checks
Routine checks reconcile visible entry totals, section counts, citation-type counts, internal navigation targets, duplicate HTML identifiers, exact URL duplication, DOI resolver formats, link attributes, likely year conflicts, and high-similarity titles. External link checks are interpreted cautiously because many publisher and repository sites block automated requests even when a page remains available to readers. A successful structural check does not establish that every citation is semantically correct or that every external link will remain live.
Corrections and Additions
Corrections, missing works, publication-status updates, and broken-link reports are welcome at info@raicollab.org. A proposed addition should include a full citation, a stable URL or persistent identifier, evidence of the work's relationship to AIID, and any known relationship to an earlier or later version.
Limitations
No search process can guarantee exhaustive coverage. Indexing delays, paywalls, inaccessible files, multilingual materials, inconsistent citation forms, dynamic web pages, and incomplete publisher metadata can obscure relevant work. The bibliography should therefore be read as a curated map of AIID's public footprint rather than as a complete or error-free census.