Fighting Deepfakes with Responsible AI Solutions

Deepfakes have become a concerning trend in today's digital landscape, raising questions about the credibility of information and privacy violations. These manipulated videos can cause harm on various levels, but advancements in Artificial Intelligence (AI) could hold the key to combating this issue.

Leveraging safe and secure AI technologies can help detect and prevent the creation of deepfakes, fostering trustworthy digital environments for all users.

Matched TAIM controls

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

MAP 1.3 — similarity 0.564, rank 1. TAIM detail and related incidents →
MAP 1.6 — similarity 0.557, rank 2. TAIM detail and related incidents →
MAP 2.2 — similarity 0.555, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/39

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.