Research citations and mentions

The AIAAIC Repository is regularly cited and mentioned by academic, non-profit, advocacy, government, and commercial research institutes, associations, and agencies. Below is a selection of recent reports, studies, books, statements, campaigns, briefings, and position papers. 

You can find media coverage here. 

2025

• Saxena D. et al. AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development

• Shen L. Not the machine’s fault: taxonomising AI failure as computational (mis)use

• Mansi G., Karusala N., Riedl M. Legally-Informed Explainable AI

• Rao P.S.B., Šćepanović S., Zhou K., Bogucka E.P., Daniele Quercia. RiskRAG: A Data-Driven Solution for Improved AI Model Risk Reporting

• Elliott, M. T. J., & MacCarthaigh, M. Accountability and AI: Redundancy, Overlaps and Blind-Spots

• Srinivasan S., Laird E. To AI or Not to AI: A Practice Guide for Public Agencies to Decide Whether to Proceed with Artificial Intelligence (pdf)

• Laufer B. et al. The Backfiring Effect of Weak AI Safety Regulation

• Yi Zeng, Enmeng Lu, Xin Guan, Cunqing Huangfu, Zizhe Ruan, Ammar Younas, Kang Sun, Xuan Tang, Yuwei Wang , Hongjie Suo, Dongqi Liang, Zhengqiang Han, Aorigele Bao, Xiaoyang Guo, Jin Wang, Jiawei Xie & Yao Liang. AI Governance International Evaluation Index (AGILE Index)

• Pratt J., Tanjaya A. Documenting the Impacts of Foundation Models (pdf)

• Yu Y., et al. Understanding Generative AI Risks for Youth: A Taxonomy Based on Empirical Data

• Saxena D., et al. AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development

• Martineau A., Turner L. Legal Scholarship Through the Lens of Generative AI, Darkly

• Bengio Y, et al. International AI Safety Report (pdf)

• Coglianese C., Crum C. Leashes, Not Guardrails: A Management-Based Approach to Artificial Intelligence Risk Regulation

• Hammond L. et al. Multi-Agent Risks from Advanced AI

• Sioumalas‑Christodoulou K., Tympas A. AI metrics and policymaking: assumptions and challenges in the shaping of AI

• Hadan H. et al. Who is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidents

• Stefania Romenti S., Colleoni E., Murtarelli G., Moroni C. Artificial Intelligence Ethical Violations and Corporate Response Strategies

• Chan A. et al. Infrastructure for AI agent

• Knight, S., McGrath, C., Viberg, O. et al. Learning about AI ethics from cases: a scoping review of AI incident repositories and cases

• Jurowetzki R., Hain DS., Wirtz K., Bianchini S. The private sector is hoarding AI researchers: what implications for science?

• Bach T. B., Kaarstad M., Solberg E., Babic A. Insights into suggested Responsible AI (RAI) practices in real-world settings: a systematic literature review

• Wang J. N., Liu H. C., Hsu Y.T. Do AI incidents and hazards matter for AI-themed cryptocurrency returns?

2024

• Al Busaidi A.S. et al. Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights

• Corneliussen H.G., Seddighi G., Arora C. “OF COURSE AI DISCRIMINATES”: IDENTIFYING COMMUNICATION GAPS  AND CROSS-DISCIPLINARY TRANSLATION CHALLENGES

• Waltersdorfer L., Sabou M. Leveraging Knowledge Graphs for AI system auditing and transparency

• Tuovinen l., Halunen K. What Is an AI Vulnerability, and Why Should We Care? Unpacking the Relationship Between AI Security and AI Ethics

• Avinash A., Manisha N. Advancing Trustworthy AI for Sustainable Development: Recommendations for Standardising AI Incident Reporting

• Cox A. Ethics Case Studies of Artificial Intelligence for Library and Information Professionals

• De Miguel Velázquez J. Šćepanović S., Gvirtz A., Quercia D. Decoding Real-World Artificial Intelligence Incidents

• Hollanek T., Gandhi I. Easy Wins and Low Hanging Fruit. Blueprints, Toolkits, and Playbooks to Advance Diversity and Inclusion in AI

• Hilliard A. et al. Are the robots taking over? On AI and perceived existential risk

• Lassiter T.B. The Role of Algorithmic Audits and Other Soft Law Approaches in Informing Users’ Calibrated Trust in Artificial Intelligence Tools 

• Center for War Studies, University of Southern Denmark. AI in Military Decision Support Systems: A Review of Developments and Debate (pdf)

• Song D., et al. Are companies better off with AI? The effect of AI service failure events on firm value

• Xu W., Gao Z. An Intelligent Sociotechnical Systems (iSTS) Framework: Enabling a Hierarchical Human-Centered AI (hHCAI) Approach

• Hickok M. et al. From Trustworthy AI Principles to Public Procurement Practices

• Jeon J. Standardization Trends on Safety and Trustworthiness Technology for Advanced AI

• Zhang R. et al. "My Replika Cheated on Me and She Liked It": A Taxonomy of Algorithmic Harms in Human-AI Relationships

• Walsh M. A Framework for Detection in an Era of Rising Deepfakes

• Lysen F., Wyatt S. Refusing participation: hesitations about designing responsible patient engagement with artificial intelligence in healthcare

• T20 Brazil 2024. Dataset Discrimination in Government Surveillance: A Threat to Equality and Justice (pdf)

• International Monetary Fund. Global Financial Stability Report - Advances in Artificial Intelligence: Implications for Capital Market Activities

• Bracket Foundation, Value for Good GmbH. Generative AI. A New Threat For Online Child Sexual Exploitation and Abuse (pdf)

• Han C. et al. Characterizing the MrDeepFakes Sexual Deepfake Marketplace

• Alizadeh F. et al. When the“Matchmaker” Does Not Have Your Interest at Heart: Perceived Algorithmic Harms, Folk Theories, and Users’ Counter-Strategies on Tinder (pdf)

• Mejía-Trejo J. Artificial Intelligence: Fundamentals of Prompt Engineering with ChatGPT as a Creativity-Driving Innovation

• Shcherbakov G.A. Artificial Intelligence: the dichotomy of technology development

• Durongkadej I. Wenyao H., Wang H.E. How Artificial Intelligence Incidents Affect Banks and Financial Services Firms? A Study of Five Firms

• Balendran A. et al. Algorithmovigilance, lessons from pharmacovigilance

• Sengputa U. Black Box Algorithmic Decision-Making and Transparency Challenges in Policing Practice: Lessons from Implementation of New Technologies by the Toronto Police Service

• Bogucka E. et al. The Atlas of AI Incidents in Mobile Computing: Visualizing the Risks and Benefits of AI Gone Mobile

• Papyshev G., Chan J.K.D. Corporate Digital Responsibility for AI

• Zheng Q et al. EvAlignUX: Advancing UX Research through LLM-Supported Exploration of Evaluation Metrics

• Morales M. et al. A DSL for Testing LLMs for Fairness and Bias

• Cox A. Developing a library strategic response to Artificial Intelligence

• Paeth K., Atherton D., Pittaras N., Frase H., McGregor S. Addressing AI Risks in Critical Infrastructure: Formalising the AI Incident Reporting Process

• Agarwal A., Nene M.J., Addressing AI Risks in Critical Infrastructure: Formalising the AI Incident Reporting Process

• OdiseIA. Another Inconvenient Truth: The Societal Emergency of AI Incidents - We Should Do Something About It

• Narayan A., Kapoor S. AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference

• Silva S. et al. Teoria Crítica da Raça na Regulação de Inteligência Artificial

• JIN D. LAU. K., GN SAMY G.N., RAHIM F.A., RAMAN V. A Framework for Artificial Intelligence Risk Management (pdf)

• Westrén-Doll N. The computer knows best: AI-powered personalization in marketing through the lens of data privacy

• Geneva Academy/ICRC. Expert Consultation Report on AI and Related Technologies in Military Decision-Making on the Use of Force in Armed Conflicts (pdf)

• Innovate UK BridgeAI. Bridging the AI Divide (pdf)

• Knight S., McGrath C., Viberg O, Pargman T.C. Learning about AI ethics from cases: A scoping review of AI incident repositories and cases

• Adler S. et al. Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online

• Munk A.K., Jacomy M., Ficozzi M., Jensen T. E. Beyond artificial intelligence controversies: What are algorithms doing in the scientific literature?

• Schleris B.. Weaknesses and vulnerabilities in modern AI

• Piyatumrong A. Building a Responsible AI Ecosystem: Thailand’s Journey Towards Ethical AI

• Shams R. A., Zowghi D., Bano M. AI for All: Identifying AI incidents Related to Diversity and Inclusion

• Danyk Y. An Approach to the Formation of Artificial Intelligence Development Threat Indicators

• Maheswari V. U., Aluvalu R. Sustainable Development Using Private AI: Security Models and Applications

• Reuel A. et al. Open Problems in Technical AI Governance

• Batool A., Zowghi D., Bano M. AI Governance: A Systematic Literature Review

• Bogucka E. et al. The Atlas of AI Incidents in Mobile Computing: Visualizing the Risks and Benefits of AI Gone Mobile

• Sayre M.A., Glover K. Machines Make Mistakes Too: Planning for AI Liability in Contracting

• Tan J. Introducing the AI Risk Series (pdf)

• Waltersdorfer L et al. AuditMAI: Towards An Infrastructure for Continuous AI Auditing

• Marchal M. et al. Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data

• Ressel J. et al. Addressing the notion of trust around ChatGPT in the high-stakes use case of insurance

• Bastidas J., Schooling V. Socio-Technical AI Design For Public Value

• Moro Visconti R. Sustainable Artificial Intelligence Issues: From ESG Valuation to Ethical Concerns

• May, R., Krüger, J., Leich, T. SoK: How Artificial-Intelligence Incidents Can Jeopardize Safety and Security

• Benbouzid D. et al. Pragmatic auditing: a pilot-driven approach for auditing Machine Learning systems (pdf)

• DeVrio A. et al. Building, Shifting, & Employing Power: A Taxonomy of Responses From Below to Algorithmic Harm (pdf)

• Adalton Cicero Teim Junior et al. Utilizacao da inteligencia artificial na medicina

• Center for News, Technology & Innovation. Artificial Intelligence in Journalism

• Consumers International. Our vision for Fair and Responsible AI for Consumers (pdf)

• Ajaykumar S. et al. A Roadmap for AI Governance: Lessons from G20 National Strategies (pdf)

• Lee Dixon R.B., Frase H. An Argument for Hybrid AI Incident Reporting (pdf)

• von Ulmenstein U.F. et al. Zu viel Gewissheit? Herausforderungen künstlich-intelligenter Gesundheitsprädiktionen für die öffentliche Gesundheitsversorgung

• UK Competition & Markets Authority. AI Foundation Models - Technical update report

• Wang A., Tan J., Murarka R., Sean Shu S. Xiong Lim Z. Enterprise-Industries Mapping of Gen AI Use Cases

• Mishra A., Sinha S., George C. P. Shielding against online harm: A survey on text analysis to prevent cyberbullying

• Torkamaan, H., Tahaei, M., Buijsman, S., Xiao, Z., Wilkinson, D. & Knijnenburg, B. The Role of Human-Centered AI in User Modeling, Adaptation, and Personalization—Models, Frameworks, and Paradigms

• Falconer J. Knowledge Management at a Precipice: The Precarious State of Ideas, Facts, and Truth in the AI Renaissance

• AFL-CIO Equity Index Funds. Paramount Group Shareholder Proposal (pdf)

• Johnson N, et al. The Fall of an Algorithm: Characterizing the Dynamics Toward Abandonment

• Kreutz H, Jahankhani H. Impact of Artificial Intelligence on Enterprise Information Security Management in the Context of ISO 27001 and 27002: A Tertiary Systematic Review and Comparative Analysis

• Kramme M. Regulierung von ChatGPT & Co.: Neue Regeln für eine neue Technik? (pdf)

• Czech National Bank. The rise of artificial intelligence: Does humanity have a revolutionary yet double-edged weapon

• Grinblat R. Digitalisierung in der Sozial- und Gesundheitswirtschaft. Zum normativen Rahmen der künstlichen Intelligenz

• Ortega-Bolaños R., Bernal-Salcedo J., Germán Ortiz M., Galeano Sarmiento J., Ruz G.A., Tabares-Soto R. Applying the ethics of AI: a systematic review of tools for developing and assessing AI-based systems

• Cusenza G.G. Litigating Governmental use of AI

• Mishra A., Sinha S., Pazhayidam George C. Shielding against online harm: A survey on text analysis to prevent cyberbullying

• Ananny M. Making Generative Artificial Intelligence a Public Problem. Seeing Publics and Sociotechnical Problem-Making in Three Scenes of AI Failure

• Turchi t, Prencipe G., Malizia A., Filogna S., Latrofa F., Sgandurra G. Pathways to democratized healthcare: Envisioning human-centered AI-as-a-service for customized diagnosis and rehabilitation

• Xu, W. (2024). A New Design Philosophy: Human-Centered Artificial Intelligence

• Bagchi K.J. Testimony of K.J. Bagchi Before the U.S. Commission on Civil Rights on the Use of Facial Recognition Technologies

• Anurag A.S. The Evolution of AI and Data Science

• Williamson B. Molnar A., Boninger F. Time for a Pause: Without Effective Public Oversight, AI in Schools Will Do More Harm Than Good

• McGrath Q., Hevner A.R., de Vreede G.J. Managing Ethical Risks of Artificial Intelligence in Business Applications 

• TenSquared Research. Web3 and Artificial Intelligence: The State of Play (pdf)

• Ojewale V., Steed R., Vecchione B., Birhane A., Raji D. Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling (pdf)

• Wells Fargo. The ascent of generative AI - what investors should know

• Grupo 1MillionBot. IA en las Universidades: retos y oportunidades

• FTI Consulting. Bridging the Gap Between Artificial Intelligence Implementation, Governance, and Democracy: An Operational and Regulatory Perspective

• Center for Long-term Artificial Intelligence, International Research Center for AI Ethics and Governance, Institute of Automation, Chinese Academy of Sciences. AI Governance International Evaluation Index (pdf)

• AFL-CIO Equity Index Funds. Apple Inc Shareholder Proposal (pdf)

• AFL-CIO Equity Index Funds. Disney Shareholder Proposal (pdf)

• Lones M. Why Doesn’t My Model Work?

• Hutiri W., Papakriakoplous O., Xiang A. Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generators (pdf)

• Tapscott B. TRIVERGENCE. Accelerating Innovation with AI, Blockchain, and the Internet of Things

• Lysen F., Wyatt S. Refusing participation: hesitations about designing responsible patient engagement with artificial intelligence in healthcare

• Savur S.G. Business Ethics. The Sustainable and Responsible Way

• Batool A., Zowghi D., Bano M. Responsible AI Governance: A Systematic Literature Review (pdf)

• Plummer D. Ethical AI and the Future of Healthcare: Combining Academic Theory and Industry Practice to Ensure Patient-Centered Care

• Lazzeroni L. Responsabilità sociale d'impresa 2.0 e sostenibilità digitale. Una lettura giuslavoristica

• Faina E. L’intelligenza artificiale: un’opportunità per il sistema produttivo italiano (pdf)

• Mauricio Sánchez R. Riesgos en el uso de la inteligencia artificial generativa

2023

• IFLA. Developing a library strategic response to Artificial Intelligence

• Altalex. Intelligenza artificiale generativa, boom di cause

• Project Management Institute. Leading AI-driven Business Transformation: Are You In?

• McKinsey & Co. Technology Trends Outlook 2023

• Rodrigues R., Resseguier A., Santiago N. When Artificial Intelligence Fails. The Emerging Role of Incident Databases

• Gutiérrez Rodríguez J.D., Castellanos-Sánchez M. Transparencia algorítmica y Estado Abierto en Colombia

• Santacaterina M. Adaptive Resilience: How to Thrive in a Digital Era 

• Czjaikovski A., Ribeiro Alves A., ‎Moser M. EDUCAÇÃO E TECNOLOGIAS: Formação Docente, Inteligência Artificial e Humanismo em Tempos de Desafios (pdf)

• Carnegie Mellon University. Impact Assessment / Harms Analysis Templates (pdf)

• Zhan X., Sun H., Miranda S.M. How Does AI Fail Us? A Typological Theorization of AI Failures

• Tanriverdi H., Akinyemi J-P., Neumann T. Mitigating Bias in Organizational Development and Use of Artificial Intelligence

• Wingard E., Oswego S. The Impact of Biases in Facial Recognition Artificial Neural Networks

• Castelonovo A., et al. Fair Enough? A map of the current limitations of the requirements to have “fair” algorithms

• Bondi-Kelly E. et al. Taking Off with AI: Lessons from Aviation for Healthcare

• Kahdan M., et al. Navigating Uncertain Waters: How Organizations Respond to Institutional Pressure in Times of the Looming EU AI Act

• Farlow F., et al. The Race to Robustness: Exploiting Fragile Models for Urban Camouflage and the Imperative for Machine Learning Security

• Buttol V. Ethical implications of artificial intelligence: the relationship between algorithms and kindness

• Xu W., Gao Z. Enabling Human-Centered AI: A Methodological Perspective

• Westminster Foundation for Democracy. A democratic approach to global artificial intelligence safety

• Bommasani R., Klyman K., Longpre S., Kapoor S., Maslej N., Xiong B., Zhang D., Liang P. The Foundation Model Transparency Index (pdf)

• Keeley N.G. Cash, Credibility, and Conversion: The Influence of Synthetic Media on Investment Behavior

• Ariffin A.S., Kamaruddin N.H., Juhari M.R.M., Jamil E.M., Dolah R., Muhtazaruddin M. N. The Reliability, Safety, and Control Principle on Recognition of Facial Expression Through Deep Learning to Support Responsible AI Implementation Policy

• Trần Khánh Lâm. Đạo đức nghề nghiệp kế toán: Xây dựng khung quy định trong thời đại công nghệ mới bùng nổ

• Arora A. et al. Risk and the future of AI: Algorithmic bias, data colonialism, and marginalization

• Ruttkamp-Bloem E. Intergenerational Justice as Driver for Responsible AI

• Hao-Ping (Hank) Lee et al. Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks (pdf)

• Groza A., Marginean A. Brave new world: Artificial Intelligence in teaching and learning

• Digital Rights Foundation. The Machine is rigged – a deep dive into AI-powered screening systems and the biases they perpetuate

• IAPP. AI incident response plans: Not just for security anymore

• Ramírez Sánchez A.M., Bhatia I., Firmino Pinto S. Navigating Artificial Intelligence from a Human Rights Lens (pdf)

• Burema D., Debowski-Weimann N., von Janowski A., Grabowski J., Maftei M., Jacobs M., van der Smagt P., Benbouzid D. A sector-based approach to AI ethics: Understanding ethical issues of AI-related incidents within their sectoral context

• Stahl B.C. Artificial Intelligence for a Better Future. An Ecosystem Perspective on the Ethics of AI and Emerging Digital Technologies

• Australian Strategic Policy Institute. Is artificial intelligence about to be regulated?

• Data & Society. Algorithms’ Transparency Problem is Everyone’s Problem

• Turri D., Dzombak R. Why We Need to Know More: Exploring the State of AI Incident Documentation Practices

• Boyle K., Berridge S. The Routledge Companion to Gender, Media and Violence

• IRPA. Un repository indipendente di incidents legati a sistemi di Intelligenza artificiale

• Shoker S, et al. Confidence-Building Measures for Artificial Intelligence: Workshop Proceedings

• Gabríela Ósk Vignisdóttir. Balancing legal liability and AI innovation: assessing the possible impact of the proposed AI liability directive

• Farlow H., Garratt M. et al. The race to robustness: Exploiting fragile models for urban camouflage and the imperative for machine learning security

• Happe A., Cito, J. Getting pwn'd by AI: Penetration Testing with Large Language Models

• Attard-Frost B., Widder D.G. The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance

• Cupertino R.T. Impactos da Inteligência Artificial na economia mundial

• Common Sense. AI and Our Kids: Common Sense Considerations and Guidance for Parents, Educators, and Policymakers 2023 (pdf)

• Center for Security and Emerging Technology. Adding Structure to AI Harm

• Lucaj J., van der Smagt P., Benbouzid D. AI Regulation Is (Not) All You Need

• UNESCO. Foundation models such as ChatGPT through the prism of the UNESCO Recommendation on the Ethics of Artificial Intelligence

• Calvara R. Un repository indipendente di incidents legati a sistemi di Intelligenza artificiale

• Bussell D., Larson A. Scaffolding the Open: Transforming an International Studies Course using Open Pedagogy

• Keeley N.G. Cash, Credibility, and Conversion: The Influence of Synthetic Media on Investment Behavior

• Martelaro N., Smith C.J., Zilovic T. Exploring Opportunities Usable Hazard Analysis Processes for AI Engineering

• Bode I., Huelss H., Nadibaidze A. Written Evidence to House of Lords AI in Weapons Systems Select Committee (AIW0015)

• Zowghi D., da Rimini F., Diversity and Inclusion in Artificial Intelligence (pdf)

• Lupo G. Risky Artificial Intelligence: The Role of Incidents in the Path to AI Regulation

• Wingard E. M. The Impact of Biases in Facial Recognition Artificial Neural Networks

• Stanford HAI. 2023 AI Index Report

• Golpayegani D., Pandit H.J., Lewis D. To Be High-Risk, or Not To Be—Semantic Specifications and Implications of the AI Act’s High-Risk AI Applications and Harmonised Standards (pdf)

• McGregor S., Hostetler J. Data-Centric Governance

• Knight K., Shibani A., Shum S.B. A reflective design case of practical micro-ethics in learning analytics

• National Institute of Standards and Technology. NIST AI Risk Management Framework Playbook (pdf)

2022

• Ada Lovelace Institute. Looking before we leap. Expanding ethical review processes for AI and data science research

• Forrester Research. Bridge The Trust Gap Between AI And Impact

• Steimers A., Schneider M. Sources of Risk of AI Systems

• Clemente Jones C. Systematizing Discrimination: AI Vendors & Title VII Enforcement

• Padir O. AI Incidents Annotation Using Stakeholder Model Based On ISO 26000 Guidelines (pdf)

• Voeneky S., Kellmeyer P., Mueller O., Burgard W. The Cambridge Handbook of Artificial Intelligence

• Kalvaitytė M. Unregulated Negative Impacts of AI: Mixed Methods Analysis of Feedback Responses to the EU AI Act Proposal (pdf)

• Colclough CJ. Reshaping the Digitization of Public Services

• Longoni C., Cian L., Kyung EJ. Algorithmic Transference: People Overgeneralize Failures of AI in the Government

• Golpayegani D., Hovsha J., Rossmaier L., Saniei R., Mišić J. Towards a Taxonomy of Risks in the Health Domain

• Martelaro N., Smith C.J., Zilovic T. Exploring Opportunities in Usable Hazard Analysis Processes for AI Engineering

• Sengupta U. Towards a Values-Based Data Governance Theory in the Social Economy in Ontario

• Dimou A., Neumaier S., Pellegrini T., Vahdati S. Towards a Knowledge-Aware AI

• Golpayegani D., Pandit H., Lewis D. AIRO: an Ontology for Representing AI Risks based on the Proposed EU AI Act and ISO Risk Management Standards

• Raji I., Kumar I., Horowitz A., Selbst A. The Fallacy of AI Functionality

• McGrath Q., Hevner A., de Vreede J-G. An Enterprise Risk Management Framework to Design Pro-Ethical AI Solutions (pdf)

• Golpayegani D. A Knowledge-Graph for Documenting Risk of Harms in AI Systems

• Ganesh M.I., Moss E. Resistance and Refusal to Algorithmic Harms: Varieties of 'Knowledge Projects'

2021

• Crockett K.A., Gerber L., Latham A., Colyer E. Building Trustworthy AI Solutions: A Case for Practical Solutions for Small Businesses

• Stahl B.C. Artificial Intelligence for a Better Future. An Ecosystem Perspective on the Ethics of AI and Emerging Digital Technologies

• Mondal M., Lalanne D. Demistifying Artificial Intelligence

• Publications Office of the European Union. Beyond Pilots: Sustainable Implementation of AI in Public Services

• Carmichael Z. Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems

• Burri T. The New Regulation of the European Union on Artificial Intelligence: Fuzzy Ethics Diffuse into Domestic Law and Sideline International Law

• Binder N., Burri T., Lohmann M., Simmler M., Thouvenin F., Vokinger K. Künstliche Intelligenz: Handlungsbedarf im Schweizer Recht (pdf)

• Nwafor I.E. AI ethical bias: A Case for AI Vigilantism (AI-lantism) in Shaping the Regulation of AI

2020

• McGregor S. Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database