How Tesla's Autonomous Driving Tech Struggles with Visual Distractions: A Cautionary Tale on Safe AI
Exploring the challenges faced by Tesla's Full Self-Driving technology, this incident illustrates the importance of robust visual perception in autonomous vehicles. This AI issue highlights the need for trustworthy AI and strong governance in autonomous systems. JOIN US To contribute to improving safe and secure AI, join Project Cerebellum, our AI incident database dedicated to harm prevention. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/145
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.