Examining Incident #134 in Responsible AI Governance
In this article, we delve into Incident #134, a notable example of an unintended outcome in AI systems. This incident highlights the need for robust governance and safety mechanisms in AI development. The misaligned data used during training led to biased results, emphasizing the importance of trustworthy AI. Understanding such incidents is crucial for harm prevention and improving the guardrails for AI.
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/134
Data 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.