Resources on real-world AI incidents, alongside descriptions of key risks and potential harms. Whether you’re assessing impacts, raising awareness, or developing safeguards, these materials offer practical insights into the challenges of AI deployment.
Incident trackers:
Risks:
- MIT AI Risk repository
- IBM AI Risk Atlas
- Generative AI Models: Opportunities and Risks for Industry and Authorities (DE BSI, 2025)
- Risks and Mitigation Strategies for Adversarial Artificial Intelligence Threats (US DHS, 2023)
- AI & Algorithmic Risks Report Netherlands (2023/2024)
- AI Privacy risks and mitigations Large Language Models (EDPB, 2025)
- International AI Safety Report (Jan 2025)
- A Taxonomy of Systemic Risks from General-Purpose AI (RAND WP, 2025)
- Towards a Standard for Identifying and Managing Bias in Artificial Intelligence (NIST SP 1270)
- Reducing risks posed by synthetic content (NIST AI 100-4)
- Managing Misuse Risk for Dual-Use Foundation Models (NIST AI 800-1 2pd – draft)
- Adversarial Machine Learning – A Taxonomy and Terminology of Attacks and Mitigations (NIST AI 100-2e2025)
Model providers’ risk management