Autopilot's Limits Exposed: The Case of a Sleeping Tesla Driver

An incident involving a Tesla driver sleeping while using Autopilot serves as a stark reminder of the need for responsible AI governance in autonomous driving systems. This event underscores the importance of trustworthy AI models, especially in high-risk scenarios where human oversight can make all the difference. The HISPI Project Cerebellum TAIM aims to facilitate harm prevention and establish guardrails for AI like this incident. By joining us JOIN US, you can contribute to our efforts in ensuring safe and secure AI development.

Matched TAIM controls

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

MAP 1.6 — similarity 0.496, rank 1. TAIM detail and related incidents →
MEASURE 2.5 — similarity 0.495, rank 2. TAIM detail and related incidents →
MEASURE 2.6 — similarity 0.495, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/67

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.