Near miss between autonomous vehicles underscores the importance of responsible AI

A recent near-miss incident involving self-driving cars highlights the growing sophistication of artificial intelligence (AI). However, it also serves as a reminder about the need for trustworthy AI governance to ensure safe and secure operations. The HISPI Project Cerebellum TAIM aims to prevent such incidents by establishing guardrails for AI development and deployment.

Matched TAIM controls

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

MEASURE 2.6 — similarity 0.551, rank 1. TAIM detail and related incidents →
MEASURE 2.5 — similarity 0.538, rank 2. TAIM detail and related incidents →
MEASURE 4.3 — similarity 0.527, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/25

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.