Skip to content
Longterm Wiki
Back

Chesney & Citron: "Deep Fakes and the Infocalypse"

paper

Credibility 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

PageTypeQuality
AI-Driven Legal Evidence CrisisRisk43.0

Cached Content Preview

HTTP 200Fetched Apr 9, 202619 KB
Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security by Robert Chesney, Danielle Keats Citron :: SSRN
 

 

 
 
 
 
 
 
 
 
 
 
 

 

 
 

 

 

 

 

 
 
 
 

 Mar
 APR
 May
 

 
 

 
 09
 
 

 
 

 2025
 2026
 2027
 

 
 
 

 

 

 
 
success

 
fail

 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
 
 

 

 About this capture
 

 

 

 

 

 

 
COLLECTED BY

 

 

 
 
Collection: Media Cloud

 

 

 A longitudinal web archival collection based on URIs from the daily feed of Media Cloud that maps news media coverage of current events.
 

 

 

 

 

 
TIMESTAMPS

 

 

 

 

 

 

The Wayback Machine - https://web.archive.org/web/20260409071731/https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3213954

 

 
 

 

 

 

 
 

 
 

 
 

 
 

 

 
 
 
 
 
 
 
 
 
 

 
 
 

 

 

 
 
 
 

 

 

 Skip to main content

 
 

 
 

 

 
 

 
 

 

 

 
 

 

 
 

 

 

 

 

 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 

 

 
 

 

 

 
 

 

 
 

 
 

 
 
 
 

 

 
 

 
 

 
 

 
 

 

 

 
 
 
 
 
 

 

 

 

 

 

 

 

 
 

 

 

 

 

 

 

 
 

 
 Download This Paper
 
 
 

 
 
 
 

 
 
 

 

 

 

 

 

 

 

 
 

 

 

 

 

 

 

 
 

 
 Open PDF in Browser
 
 
 

 
 
 
 
 
 

 

 
 
 

 
 

 
 
 
 
 
 Add Paper to My Library
 
 

 

 

 
 

 

 

 

 

 

 

 

 
 
 
 
 
 
 
 
 
 

 Share:
 
 

 

 
 

 
 

 
 

 
 
 
 
 

 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 

 
 

 
 

 

 

 
 

 

 

 
Permalink

 
Using these links will ensure access to this page indefinitely

 

 
 Copy URL
 

 
 

 
 Copy DOI
 

 

 
 

 
 

 

 

 

 
 

 
 
 
 

 
 
 
 
 

 
 

 
 
 
 
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

... (truncated, 19 KB total)
Resource ID: d3ad96f069ddc77e | Stable ID: sid_CCCEroYjIL