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Chesney & Citron: "Deep Fakes and the Infocalypse"
paperCredibility Rating
3/5
Good(3)Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.
Rating inherited from publication venue: SSRN
A widely cited foundational paper in AI governance circles on synthetic media risks; relevant to AI safety researchers studying misuse of generative AI and the societal consequences of capability proliferation.
Metadata
Importance: 72/100working paperanalysis
Summary
Chesney and Citron provide a foundational legal and policy analysis of deepfake technology, examining how AI-generated synthetic media creates harms across privacy, democracy, and national security. They argue deepfakes will accelerate 'truth decay' and propose a multi-layered response involving law, platform governance, and technical countermeasures.
Key Points
- •Deepfakes leverage machine learning to produce increasingly realistic synthetic audio/video, becoming both more convincing and more accessible to non-expert actors.
- •Harms span multiple domains: non-consensual intimate imagery, political disinformation, fraud, and destabilization of international relations.
- •The 'liar's dividend' effect is a key concern: deepfakes allow bad actors to dismiss genuine evidence as fabricated, eroding epistemic trust broadly.
- •Existing legal frameworks (defamation, fraud, privacy torts) offer partial but insufficient remedies, requiring new legislative and regulatory approaches.
- •Technical detection countermeasures are in an arms race with generation capabilities, necessitating platform-level authentication and provenance standards.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| AI-Driven Legal Evidence Crisis | Risk | 43.0 |
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Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security by Robert Chesney, Danielle Keats Citron :: SSRN
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Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security
107 California Law Review 1753 (2019)
U of Texas Law, Public Law Research Paper No. 692
U of Maryland Legal Studies Research Paper No. 2018-21
68 Pages
Posted: 21 Jul 2018
Last revised: 17 Dec 2019
See all articles by Robert Chesney
Robert Chesney
University of Texas School of Law
Danielle Keats Citron
University of Virginia School of Law
Date Written: July 14, 2018
Abstract
Harmful lies are nothing new. But the ability to distort reality has taken an exponential leap forward with “deep fake” technology. This capability makes it possible to create audio and video of real people saying and doing things they never said or did. Machine learning techniques are escalating the technology’s sophistication, making deep fakes ever more realistic and increasingly resistant to detection. Deep-fake technology has characteristics that enable rapid and widespread diffusion, putting it into the hands of both sophisticated and unso
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