Merging AI Incidents Research with Political Misinformation Research: Introducing the Political Deepfakes Incidents Database
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Abstract (arXiv)
This article presents the Political Deepfakes Incidents Database (PDID), a collection of politically-salient deepfakes, encompassing synthetically-created videos, images, and less-sophisticated `cheapfakes.' The project is driven by the rise of generative AI in politics, ongoing policy efforts to address harms, and the need to connect AI incidents and political communication research. The database contains political deepfake content, metadata, and researcher-coded descriptors drawn from political science, public policy, communication, and misinformation studies. It aims to help reveal the prevalence, trends, and impact of political deepfakes, such as those featuring major political figures or events. The PDID can benefit policymakers, researchers, journalists, fact-checkers, and the public by providing insights into deepfake usage, aiding in regulation, enabling in-depth analyses, supporting fact-checking and trust-building efforts, and raising awareness of political deepfakes. It is suitable for research and application on media effects, political discourse, AI ethics, technology governance, media literacy, and countermeasures.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Sep 2024.
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Citing papers per year: 2024: 2; 2025: 1; 2026: 1.
4 papers.
- 2024The Role of Governments in Increasing Interconnected Post-Deployment Monitoring of AIcited by 6
- 2024Lessons for Editors of AI Incidents from the AI Incident Databasecited by 5
- 2025Fit for Purpose? Deepfake Detection in the Real Worldcited by 4
- 2026Why AI Harms Can't Be Fixed One Identity at a Time: What 5300 Incident Reports Reveal About Intersectionalitycited by 0
- 2026Why AI Harms Can't Be Fixed One Identity at a Time: What 5300 Incident Reports Reveal About Intersectionality27 Apr 2026
- 2025Fit for Purpose? Deepfake Detection in the Real World18 Oct 2025
- 2024The Role of Governments in Increasing Interconnected Post-Deployment Monitoring of AI7 Oct 2024
- 2024Lessons for Editors of AI Incidents from the AI Incident Database24 Sep 2024