Autonomous Vehicles: Navigating the Complexities of Responsible AI

In an interesting turn of events, a drunken driving suspect in San Jose claimed that his Tesla was on autopilot during the incident. This raises questions about the safety and reliability of autonomous vehicles' AI systems, emphasizing the need for robust AI governance and trustworthy AI models. The HISPI Project Cerebellum TAIM offers resources for managing such incidents and improving the overall safety and security of AI applications.

Matched TAIM controls

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

GOVERN 6.2 — similarity 0.478, rank 1. TAIM detail and related incidents →
GOVERN 4.3 — similarity 0.467, rank 2. TAIM detail and related incidents →
MEASURE 2.7 — similarity 0.457, 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.