Values Statement: We believe AI should cause no harm, but enhance the quality of human life, by proactively adopting our AI Governance framework.
Evidence-based Transparent For governance
AI Incidents
Data source & citationBias in AI: UK Passport Photo Checker Shows Preference Against Dark-Skinned Women - A Case for Responsible AI
Read moreGovernment Grading: Assessing Accountability in Algorithm Usage
Read moreFootball Match Disrupted by Misguided AI: An Example of AI Accountability
Read moreLawsuit Filed Over Google Instant's Alleged Anti-Semitic Search Results: A Case for Safe and Secure AI
Read moreTracking Children Suspected of Criminal Activity Using Live Facial Recognition: An Unwarranted Invasion of Privacy
Read moreAI-Powered Police Robot Sings Instead of Addressing Crime Report – Emphasizing the Need for Responsible AI
Read moreExploring an AI Model that Determines College Admissions: A Look into Responsible AI Governance
Read moreExamining AI Bias: The Case of Algorithm-Imposed Barriers for Black Kidney Transplant Recipients
Read moreThe Lekki Massacre: Examining Facebook's Labeling of Content as 'False' – A Case for Responsible AI Governance
Read moreFacebook's Struggle to Combat Misinformation: COVID-19 and Voting Claims
Read moreUnveiling the Controversies behind Spam Filters: A Closer Look
Read moreData source
Incident data is from the AI Incident Database (AIID).
When citing the database as a whole, please use:
McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.
Pre-print on arXiv · Database snapshots & citation guide
We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.