Autonomous Vehicles: Assessing Risks and Responsibilities Post-Incident

Recent fatalities involving Tesla's Autopilot and Uber's self-driving vehicle underscore the complexities and challenges of autonomous driving technology. These incidents have sparked a renewed debate on responsible AI governance, with experts emphasizing the need for robust safety measures and guardrails to ensure the development of safe and secure AI systems.

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 →
MAP 1.6 — similarity 0.544, rank 2. TAIM detail and related incidents →
MEASURE 3.2 — similarity 0.538, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/20

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.