Unveiling Lessons Learned: GDC Talk on Resilience in AI

In a riveting discussion at the Game Developers Conference, we delved into real-life anecdotes of AI disasters and their aftermath. These stories underscore the importance of responsible AI governance, harm prevention, and safe and secure AI practices. By learning from these incidents, we can better implement guardrails for AI and improve our Trusted AI Models through HISPI Project Cerebellum TAIM. Engage with us—JOIN US—to contribute to this ongoing conversation.

Matched TAIM controls

Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

MEASURE 2.6 — similarity 0.648, rank 1. TAIM detail and related incidents →
MEASURE 3.1 — similarity 0.641, rank 2. TAIM detail and related incidents →
MANAGE 4.1 — similarity 0.641, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/29

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.