Unresponsive Tesla Driver: Examining the Role of AI Guardrails

In a recent incident, a driver of a Tesla S operating on Autopilot evaded police pursuit over seven miles in California. The episode raises concerns about the safety and reliability of autonomous vehicles, underscoring the need for robust AI governance. While this technology promises significant benefits, ensuring safe and secure AI is crucial to prevent incidents like these. JOIN US to learn more about HISPI Project Cerebellum TAIM – a platform dedicated to responsible AI incident management.

Matched TAIM controls

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

MEASURE 2.6 — similarity 0.479, rank 1. TAIM detail and related incidents →
GOVERN 6.2 — similarity 0.462, rank 2. TAIM detail and related incidents →
MEASURE 2.7 — similarity 0.458, 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.