Unauthorized Access Raised by Face ID Incident: A Concern for Responsible AI Governance

A recent incident involving unauthorized access to Face ID systems has raised concerns about the safety and security of this popular facial recognition technology. The breach, which allowed individuals to unlock devices without the rightful owner's consent, underscores the need for robust AI governance mechanisms and trustworthy AI management practices. The HISPI Project Cerebellum TAIM (Trusted AI Model) offers a platform to manage, measure, and map such incidents, promoting harm prevention and safe AI implementation. Contribute—JOIN US—to learn more about our efforts in fostering trustworthy AI.

Matched TAIM controls

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

MEASURE 2.10 — similarity 0.621, rank 1. TAIM detail and related incidents →
MAP 1.6 — similarity 0.616, rank 2. TAIM detail and related incidents →
MAP 4.2 — similarity 0.585, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/26

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.