Germany: Assessing Accountability in an Unforeseen Incident Involving AI-Assisted Robots

In a recent incident, an AI-assisted robot at a Volkswagen plant in Germany fatally injured a worker. The occurrence highlights the pressing need for responsible AI governance and safe & secure AI practices. This event underscores the importance of implementing trustworthy AI models (TAIM) and guardrails to prevent harm and enhance overall system performance. HISPI Project Cerebellum TAIM serves as a crucial resource in this regard, offering insights on how to map, measure, manage, and govern AI incidents. By contributing through JOIN US, individuals can play an active role in fostering trustworthy AI development.

Matched TAIM controls

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

MEASURE 2.6 — similarity 0.493, rank 1. TAIM detail and related incidents →
MAP 4.2 — similarity 0.481, rank 2. TAIM detail and related incidents →
MAP 1.3 — similarity 0.476, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/24

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.