AIAAIC Repository – AI Incidents, Controversies & Risks

web

OECD·oecd.ai/en/catalogue/tools/aiaaic-repository

Credibility Rating

4/5

High(4)

High quality. Established institution or organization with editorial oversight and accountability.

Rating inherited from publication venue: OECD

A practical reference for AI safety researchers and policymakers seeking empirical evidence of real-world AI failures and harms; complements theoretical safety work with documented incidents.

Metadata

Importance: 62/100tool pagedataset

Summary

The AIAAIC (AI, Algorithmic, and Automation Incidents and Controversies) Repository is an independent public database cataloguing real-world incidents and controversies involving AI and algorithmic systems. It serves as a transparency resource for tracking harms, failures, and risks that have emerged from deployed AI systems. The repository is hosted on the OECD AI catalogue as a tool for researchers, policymakers, and practitioners.

Key Points

•Maintains a public, searchable database of AI-related incidents, controversies, and systemic risks drawn from real-world deployments.
•Covers a wide range of harm categories including bias, misinformation, surveillance, safety failures, and misuse of AI systems.
•Supports AI governance and policy work by providing documented evidence of AI risks and failure modes.
•Useful for red-teaming, risk assessment, and informing safety standards by grounding concerns in empirical case studies.
•Independent and freely accessible, making it a key reference for transparency and accountability in AI development.

Review

The AIAAIC Repository represents a critical initiative in AI safety by systematically collecting and analyzing incidents related to artificial intelligence, algorithms, and automation. Started in 2019 as a private project, it has evolved into a comprehensive, open-access platform that serves researchers, academics, journalists, and policymakers worldwide in understanding AI's complex risk landscape. By cataloging real-world AI incidents across sectors like social welfare, education, and corporate governance, the repository offers a unique transparency mechanism for identifying potential systemic risks. Its independent nature, coupled with an open-source approach, enables broad collaboration and knowledge sharing. While the tool primarily functions as an educational and awareness-building resource, it significantly contributes to responsible AI development by providing empirical evidence of AI system failures and potential ethical challenges.

Resource ID: f4e336365b5dfda9 | Stable ID: NDA5Yjg3Yz