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AI Incident Database Examples in 2026: Ethics & Best Practices

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AI Incident Database Examples in 2026: Ethics & Best Practices

The AI Incident Database and OECD AI Incidents Monitor — top incident categories, illustrative cases, and how to use incident data for risk management in 2026.

Misar Team·Jun 24, 2025·5 min read
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Quick Answer

The AI Incident Database (AIID) and OECD AI Incidents Monitor (AIM) now catalogue 3,000+ real-world AI harms. Incident data is the fastest input to responsible AI risk assessments in 2026.

  • AIID maintained by Responsible AI Collaborative since 2018
  • OECD AIM launched in 2024 with G7 Hiroshima support
  • Incidents are used by NIST, EU AI Office, and UK AISI for scenario planning

What Are AI Incident Databases?

An AI incident is a situation where the development, deployment, or use of an AI system results in actual harm to people, property, or the environment. The AI Incident Database (incidentdatabase.ai) was launched in 2018 by Sean McGregor and the Partnership on AI. The OECD AI Incidents Monitor (oecd.ai/en/incidents) launched in 2024 and harmonises classification with OECD AI Principles.

The ISO/IEC/TR 5469:2024 and the EU AI Act Article 73 both require serious incident reporting for high-risk AI.

Key Details / Requirements

Common AI Incident Categories (AIID)

Category

Example

Bias and discrimination

Amazon hiring AI down-weighting women (2018)

Autonomous-vehicle safety

Uber ATG fatal crash, Tempe AZ (2018)

Misidentification

Robert Williams wrongful arrest (2019, Detroit)

Content moderation failure

YouTube recommending extremist content

Healthcare AI error

UnitedHealth nH Predict denials (2023 lawsuit)

Financial AI discrimination

Apple Card gender disparities (2019)

Deepfake fraud

Arup HKD 200M deepfake transfer (2024)

LLM hallucination

Air Canada chatbot liability (2024)

Copyright infringement

Stability AI Getty litigation (2023-2025)

Privacy breach

ChatGPT title-history leak (2023)

Mandatory Incident Reporting

Regulation

Trigger

Deadline

EU AI Act Art. 73

Serious incident in high-risk AI

15 days (3 days for widespread)

US state consumer-protection laws

Varies

Varies

India DPDP Act

Personal data breach

72 hours to Data Protection Board

China Generative AI Measures

Illegal content

24 hours

UK DPA 2018

Personal data breach

72 hours to ICO

Real-World Examples / Case Studies

Uber ATG (Tempe, 2018) — Self-driving prototype killed pedestrian Elaine Herzberg. NTSB investigation found operator and system design failures.

Robert Williams (Detroit, 2019) — Wrongful arrest after facial recognition misidentification. ACLU case became a reference for face-recognition moratoria.

nH Predict (UnitedHealth, 2023) — Class action alleges AI tool with 90%+ error rate was used to deny Medicare Advantage claims.

Air Canada Chatbot (BC, 2024) — Civil Resolution Tribunal held airline liable for misinformation about bereavement fares.

Arup deepfake (Hong Kong, 2024) — HKD 200M transferred after deepfake CFO video call.

What This Means for Organisations

In 2026, incident management is a core RAI capability. Teams should:

  • Subscribe to AIID and OECD AIM for sector-relevant incidents
  • Incorporate incident patterns into pre-deployment red-teaming
  • Establish a cross-functional incident response plan (IRP)
  • Report per applicable law (EU AI Act, DPDP, etc.)
  • Publish post-mortems to industry peers via AIID

Compliance Checklist

  • Designate an AI Incident Response Lead
  • Define "incident" and "serious incident" in policy
  • Integrate incident triage with existing cybersecurity IR
  • Maintain a 24/7 incident reporting channel
  • File to AIID and applicable regulators within mandated windows
  • Conduct quarterly tabletop exercises
  • Train deployers on incident recognition

FAQs

Q: What is a serious incident under the EU AI Act?

An incident that leads to death, serious health damage, serious property or environmental damage, or serious and irreversible disruption of critical infrastructure.

Q: Is AIID peer-reviewed?

Incidents are community-submitted and editorial-reviewed by the Responsible AI Collaborative.

Q: Is OECD AIM government data?

Maintained by the OECD AI Policy Observatory with government and multistakeholder inputs.

Q: Can an incident report be confidential?

Regulator reports can be confidential; AIID public entries can be submitted anonymously.

Q: How do incidents map to risk tiers?

Use incident severity (fatality, financial loss, privacy breach) to inform AI RMF MEASURE and MANAGE functions.

Q: Does the FTC require incident reporting?

No dedicated AI incident rule, but Section 5 enforcement often follows publicised incidents.

Q: How often should IRPs be updated?

At least annually, and after every incident.

Conclusion

Incident data is the cheapest risk-management input available. Read it, learn from it, and contribute.

Wire incident response into your AI stack with Misar AI's IRP template.

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