Research citations and mentions

AIAAIC is regularly cited and mentioned in reports, studies, books, statements, campaigns, briefings, and position papers by academic, non-profit, advocacy, and government research institutes, associations, agencies, and commercial entities. 

You can also find research papers citing AIAAIC on Google Scholar, Google Books, and RefSeek.

2025

• Bengio Y, et al. International AI Safety Report

• Center for Democracy & Technology. To AI or Not to AI: A Practice Guide for Public Agencies to Decide Whether to Proceed with Artificial Intelligence

• European Union Intellectual Property Office. THE DEVELOPMENT OF GENERATIVE ARTIFICIAL INTELLIGENCE FROM A COPYRIGHT PERSPECTIVE

• Global Partnership on Artificial Intelligence. Algorithmic Transparency in the Public Sector A state-of-the-art report of algorithmic transparency instruments

• ICAAD, King & Wood Mallesons. Artificial Intelligence Harm and Human Rights

• International Monetary Fund (IMF). Advances in Artificial Intelligence Implications for Capital Market Activities

• Partnership on AI. Documenting the Impacts of Foundation Models

• 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

• Ashkinaze J. et al. Plurals: A System for Guiding LLMs via Simulated Social Ensembles

• Attard-Frost B. Transfeminist AI governance

• Attard-Frost B., et al. The Ethics of AI Value Chains

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

• Breznik L. OpenAI and Environmental Responsibility

• de Carvalho A.M., Waldman R.L. Proteção à saúde no meio ambiente digital: o princípio da precaução e as neurotecnologias

• Chan A., et al. Infrastructure for AI agents

• Chang T., et al. Opaque Transparency: Gaps and Discrepancies in the Report of Social Media Harms

• Chapman K. et al. Beyond the Legal Lens: A Sociotechnical Taxonomy of Lived Privacy Incidents and Harms

• Chen J., et al. On the Literary Landscapes of Vector Embeddings

• Chin Z.S. Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks

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

• Corvi E., et al. Taxonomizing Representational Harms using Speech Act Theory

• Denecke, K., Lopez-Campos, G., & May, R. The unintended harm of Artificial Intelligence (AI): exploring critical incidents of AI in healthcare

• Denecke K. et al. The Unexpected Harms of Artificial Intelligence in Healthcare: Reflections on Four Real-World Cases

• DLAUK JIN, GN SAMY, FA RAHIM. Framework-Driven Guideline Generation for AI Adoption: A Risk-Based Perspective

• Gupta, A., Papyshev, G., & T. Kwok, J. Bubble, Bubble, AI’s Rumble: Why Global Financial Regulatory Incident Re-Porting Is Our Shield Against Systemic Stumbles

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

• Fernandes M. et al. Co-creating an Ontology of Online Gender-Based Harms: An Interdisciplinary Perspective

• Ezell C., Xavier Roberts-Gaal X., Chan A. Incident Analysis for AI Agents

• Gupta, M., & Chhabria, A. (2025). Allusions of Dystopian Technocultures: AI in Sex and Care Work

• Goktas P., Grzybowski A. Shaping the Future of Healthcare: Ethical Clinical Challenges and Pathways to Trustworthy AI

• Golpayegani D. Semantic Frameworks to Support the EU AI Act's Risk Management and Documentation

• Gong Z., Han X., Zheng Y. Recovery from AI government service failures: Is disclosing the identity of the AI agent an effective strategy?

• Kaminski M., Brennan R. Enhancing AI Incident Data Sharing Using Cyber Threat Intelligence Feeds

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

• Knox W.B. Harmful Traits of AI Companions

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

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

• Jelveh Z., Huang F., Nguyen T. Theory and Metrics for Law-informed Attribution of Human - Generative AI Liability

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

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

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

• Li M. et al. A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents

• Lee H-P., et al. Privy: Envisioning and Mitigating Privacy Risks for Consumer-facing AI Product Concepts

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

• Mansi G., Riedl M. Implications of Current Litigation on the Design of AI Systems for Healthcare Delivery

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

• McGrath Q., et al. Designing an Enhanced Enterprise Risk Management System to Mitigate Ethical Risks of Artificial Intelligence Applications

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

• Paeth K, McGregor S. AI Risk, Safety, and Incident Reporting

• Parthasarathy R. et al. STRIFE: A Socio-Technical Framework for Threat Modeling of Artificial Intelligence Systems

• Piorkowski D., et al. Developing a Risk Identification Framework for Foundation Model Uses

• Prabhakar M., Xu L., Saxena P. Model Inversion Attacks Meet Cryptographic Fuzzy Extractors

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

• Proşcanu C., Proşcanu M. The AI Paradox: Balancing Free Speech with Online Safety in the Era of Automated Moderation

• Rao P.S.B., Šćepanović S., Jayagopi D.B., Cherubini M., Quercia D. The AI Model Risk Catalog: What Developers and Researchers Miss About Real-World AI Harms

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

• Reid C., Sutherland M. Looking back: gifted young people’s reflections on learning in areas of deprivation 

• Richards I., Benn C., Zilka M. From Incidents to Insights: Patterns of Responsibility following AI Harms

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

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

• Selvadurai N. Seeing the full picture: an integrated regulatory model for AI

• Shi Y., et al. The Siren Song of LLMs: How Users Perceive and Respond to Dark Patterns in Large Language Models

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

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

• Stoica A.A. The Legal Challenges of Laws and Drones

• Sutherland M., Reid C. Looking back: gifted young people's reflections on learning in areas of deprivation

• Swanström N., Logan T.J. G7 Strategy for Countering Russian Information Operations in the Indo-Pacific Region: A Framework for Enhanced Multilateral Coordination and Response

• Schwartz R. et al. Reality Check: A New Evaluation Ecosystem Is Necessary to Understand AI’s Real World Effects 

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

• Taik A., et al. Fairness in Federated Learning: Fairness for Whom?

• Tanriverdi H., Akinyemi J-P. Algorithmic Social Injustices: Antecedents and Mitigations

• Tantalaki N., Vei S., Vakali A. Echoes of AI Harms: A Human–LLM Synergistic Framework for Bias-Driven Harm Anticipation 

• Uba C. Towards an AI Incident & Response Framework: Conceptualizing Cause, Locus, and Impact of AI Incidents

• Vakali A., Dimitriadis I. FAIRTOPIA: Envisioning Multi-Agent Guardianship for Disrupting Unfair AI Pipelines

• Vasir G., Huh-Yoo J. Characterizing the Flaws of Image-Based AI-Generated Content

• Vei S., Giudici P., Sermpezis P., Vakali A., Bernadelli E.B., AI Harmonics: a human-centric and harms severity-adaptive AI risk assessment framework

• Venkatasubramanian K., Hardie H., Ranalli T-M. Toward a taxonomy of negative outcomes from the use of AI-driven systems for people with disabilities

• Waltersdorfer L., Sabou M. Leveraging Knowledge Graphs for AI System Auditing and Transparency

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

• Wei K., Heim L. Designing Incident Reporting Systems for Harms from General-Purpose AI

• Williams R.M. A Taxonomy of AI: We're Wrong About What AI Is

• Xiao, S., Zou, H., Qian Zhang, A., Kumar, D., Shen, H., Hong, J., & Eslami, M. (2025). What Comes After Harm? Mapping Reparative Actions in AI Through Justice Frameworks

• Yung J-Y., et al.  Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection

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

• Zeferino de Magalhães Neto M. O RECONHECIMENTO FACIAL E O DIREITO DE NÃO SER CONFUNDIDO PRISÕES INDEVIDAS E A RESPONSABILIZAÇÃO DO AGENTE PÚBLICO

• Zeng Y., et al. AI Governance International Evaluation Index (AGILE Index 2025)

2024

• AFL-CIO Equity Index Funds. Apple Inc Shareholder Proposal, Disney Shareholder Proposal, Paramount Group Shareholder Proposal

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

• Center for Civil Rights & Technology, The Leadership Conference on Civil & Human Rights. Testimony of K.J. Bagchi Before the U.S. Commission on Civil Rights on the Use of Facial Recognition Technologies

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

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

• Consumers International. Our vision for Fair and Responsible AI for Consumers

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

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

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

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

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

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

• Innovate UK BridgeAI. Bridging the AI Divide

• Stanford HAI. 2024 AI Index Report

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

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

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

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

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

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

• Agarwal A., Nene M.J., Advancing Trustworthy AI for Sustainable Development: Recommendations for Standardising AI Incident Reporting

• Agarwal A., Nene M.J., Standardised Schema and Taxonomy for AI Incident Databases in Critical Digital Infrastructure

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

• 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]

• 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

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

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

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

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

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

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

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

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

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

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

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

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

• Cusenza G.G. Litigating Governmental use of AI

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

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

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

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

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

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

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

• Hammond L. et al. Open Problems in Technical AI Governance

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

• Hickok M., et al. From Trustworthy AI Principles to Public Procurement Practices#Hilliard A. et al. Are the robots taking over? On AI and perceived existential risk

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

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

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

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

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

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

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

• 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

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

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

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

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

• Lones M. Why Doesn’t My Model Work?

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

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

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

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

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

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

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

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

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

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

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

• 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

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

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

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

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

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

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

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

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

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

• Schleris B.. Weaknesses and vulnerabilities in modern AI

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

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

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

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

• Tan J. Introducing the AI Risk Series

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

• Teim Junior. A.C., et al. Utilizacao da inteligencia artificial na medicina

• 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

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

• 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

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

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

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

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

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

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

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

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

• Zeng Y., et al. AI Governance International Evaluation Index (AGILE Index 2024)

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

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

2023

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

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

• IFLA. Developing a library strategic response to Artificial Intelligence

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

• McKinsey & Co. Technology Trends Outlook 2023

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

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

• Stanford HAI. 2023 AI Index Report

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

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

• 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

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

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

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

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

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

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

• 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

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

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

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

• Carnegie Mellon University. Impact Assessment / Harms Analysis Templates

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

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

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

• Farlow H. Is artificial intelligence about to be regulated?

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

• 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

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

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

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

• Hoffmann M, Frase F. Adding Structure to AI Harm

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

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

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

• Lee H-P. et al. Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks

• Leong B., Atherton D. AI incident response plans: Not just for security anymore

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

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

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

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

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

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

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

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

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

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

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

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

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

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

• Wang A., Kapoor S., Barocas S., Narayanan A. Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy

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

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

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

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

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

• Colclough CJ. Reshaping the Digitization of Public Services

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

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

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

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

• 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

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

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

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

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

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

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

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

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

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

2021

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

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

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

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

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

• Mondal M., Lalanne D. Demistifying Artificial Intelligence

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

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

2020

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