Interactive tool
AI Incident Explorer
A faceted, filterable timeline and table of well-documented AI/ML incidents — every entry dated, classified under our taxonomy, and linked to its strongest primary source. Filter by incident type, harm domain, AI modality, actor class, source tier, date range, and free text. Copy APA or BibTeX citations; share filtered views by URL.
68 curated incidents. We do not do attribution speculation — an incident with an unknown actor stays actor unknown. Each entry links to its primary source so you can verify it yourself.
0 of 68 incidents
| Date | Incident | Src |
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Taxonomy & sourcing
Incident type: model failure, data leak, adversarial misuse, safety failure, supply chain. Harm domain: privacy, security, safety, discrimination, fraud. Modality: LLM, vision, recommender, agentic. Actor class: vendor, third-party, researcher, or unknown — never speculated. Source tier: T1 primary (advisory / court / regulator / peer-reviewed), T2 established secondary, T3 specialty secondary, T4 triangulated user reports. Entries sourced only at T3/T4 are marked partial verification.
Dates: the table sorts on the incident date (when the harm occurred); the disclosure date (when it entered the public record) is shown in the detail drawer. Catalog as of .