Facial Transformation App FaceApp: Addressing Privacy Concerns in Responsible AI

Recent privacy concerns have been raised about the popular facial transformation app, FaceApp. The app, which allows users to alter their faces digitally, has gained significant traction, leading experts to scrutinize its AI governance and data security practices. These concerns stem from the fact that users must grant full access to their device's photo library in order to use the app, potentially exposing sensitive images without adequate safeguards.

By promoting transparency and implementing robust trustworthy AI models (TAIM), FaceApp can alleviate these worries and solidify its position as a responsible AI tool. The HISPI Project Cerebellum TAIM provides an ideal platform for harmonizing AI incident management, offering mechanisms to Measure, Map, Govern, and Manage such incidents.
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Matched TAIM controls

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

MEASURE 2.10 — similarity 0.569, rank 1. TAIM detail and related incidents →
MAP 1.6 — similarity 0.557, rank 2. TAIM detail and related incidents →
MAP 4.1 — similarity 0.495, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/60

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.