The Social Impact of Deepfakes
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Prior research has largely focused on the potential societal consequences of AI-generated misinformation rather than its real-world prevalence.
“However, prior research has largely focused on its potential societal consequences rather than its real-world prevalence.”
From Characterizing AI-Generated Misinformation on Social Media (2025) · cites this paper as Hancock and Bailenson 2021
AI-generated content has become increasingly prevalent on social media.
“AIgenerated content (e. g., deepfakes) - artificially generated videos, images, and audio designed to mimic real individuals - has become increasingly prevalent on social media, raising critical concerns about their role in spreading misinformation (Hancock and Bailenson 2021; Groh et al. 2024; Vaccari and Chadwick 2020).”
From Characterizing AI-Generated Misinformation on Social Media (2025) · cites this paper as Hancock and Bailenson 2021
The characteristics of AI-generated misinformation on social media are poorly understood.
“Despite growing concerns, the characteristics of AIgenerated misinformation on social media are poorly understood.”
From Characterizing AI-Generated Misinformation on Social Media (2025) · cites this paper as Hancock and Bailenson 2021
There is a lack of robust detection techniques for text deepfakes.
“highlighting the lack of robust detection techniques for text deepfakes and the overlap with human-generated fake content.”
From Deepfake forensics: a survey of digital forensic methods for multimodal deepfake identification on social media (2024) · cites this paper as Hancock & Bailenson (2021)
Recent advances in technology for hyper-realistic manipulations to video pose a threat to traditional standards of evidence and trust in media.
“Recent advances in technology for algorithmically applying hyper-realistic manipulations to video are simultaneously enabling new forms of interpersonal communication and posing a threat to traditional standards of evidence and trust in media1–8.”
From Human detection of political speech deepfakes across transcripts, audio, and video (2024) · cites this paper as [1]
Deepfake videos have the power to modify and implant false memories, altering people's attitudes toward each other without valid reasons.
“Interpersonally, deepfake videos have the power to modify and implant false memories, altering people's attitudes toward each other without valid reasons.”
From Examining the Societal Impact and Legislative Requirements of Deepfake Technology: A Comprehensive Study (2024) · cites this paper as [6]
The UK government announced its intention to criminalize online self-harm content in late 2022 following the Molly Russell case.
“A notable example is the tragic case of Molly Russell, where the UK government announced its intention to criminalize online self-harm content in late 2022 [6].”
From Examining the Societal Impact and Legislative Requirements of Deepfake Technology: A Comprehensive Study (2024) · cites this paper as [6]
Audiovisual content is met with credulity as videos are accepted almost axiomatically as accurate depictions of reality by journalists, politicians, jurisprudence, and everyday citizens.
“Audiovisual content is met with credulity as videos are accepted almost axiomatically as accurate depictions of reality by journalists, politicians, jurisprudence, and everyday citizens (Farish, 2020;Fallis, 2021;Hancock & Bailenson, 2021).”
From The detection of political deepfakes (2022) · cites this paper as Hancock & Bailenson, 2021
Deepfakes pose significant problems across various domains, such as misinformation, political manipulation, propaganda, reputational damage, and fraud.
“Deepfakes can be used for entertainment, education, and research; however, they pose a range of significant problems across various domains, such as misinformation, political manipulation, propaganda, reputational damage, and fraud.”
From Deepfake Attacks: Generation, Detection, Datasets, Challenges, and Research Directions (2023) · cites this paper as [1]
Cites
Deepfakes and beyond: A Survey of face manipulation and fake detection
Tolosana, R., Vera-Rodriguez, R., Fierrez, J., Morales, A., & Ortega-Garcia, J. (2020) · Information Fusion · doi:10.1016/j.inffus.2020.06.014 · Cited by 1,237 · see citing works
Vaccari, C., & Chadwick, A. (2020) · Social Media + Society · doi:10.1177/2056305120903408 · Cited by 978 · cited 1× · see citing works
“In a study looking at the effect of deepfakes on trust in the news, Vaccari and Chadwick 19 found that although people were unlikely to be completely misled by a deepfake (at least with the technology they were using), exposure to the deepfake increased their uncertainty about media in general.”
Do (microtargeted) deepfakes have real effects on political attitudes?
Dobber, T., Metoui, N., Trilling, D., Helberger, N., & de Vreese, C. (2021) · The International Journal of Press/Politics · doi:10.1177/1940161220944364 · Cited by 256 · see citing works
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Fooled twice: People cannot detect deepfakes but think they can
Köbis, N. C., Doležalová, B., & Soraperra, I. (2021) · iScience · doi:10.1016/j.isci.2021.103364 · Cited by 193 · see citing works
Deepfake Attacks: Generation, Detection, Datasets, Challenges, and Research Directions
Naitali, A., Ridouani, M., Salahdine, F., & Kaabouch, N. (2023) · Computers · doi:10.3390/computers12100216 · Cited by 117 · see citing works
The detection of political deepfakes
Appel, M., & Prietzel, F. (2022) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmac008 · Cited by 95 · see citing works
Gamage, D., Ghasiya, P., Bonagiri, V., Whiting, M. E., & Sasahara, K. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517446 · Cited by 79 · see citing works
Human detection of political speech deepfakes across transcripts, audio, and video
Groh, M., Sankaranarayanan, A., Singh, N., Kim, D. Y., Lippman, A., & Picard, R. (2024) · Nature Communications · doi:10.1038/s41467-024-51998-z · Cited by 89 · see citing works
Qureshi, S. M., Saeed, A., Almotiri, S. H., Ahmad, F., & Al Ghamdi, M. A. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2037 · Cited by 71 · see citing works
They Would Never Say Anything Like This! Reasons To Doubt Political Deepfakes
Hameleers, M., van der Meer, T. G. L. A., & Dobber, T. (2024) · European Journal of Communication · doi:10.1177/02673231231184703 · Cited by 47 · see citing works
Understanding fraudulence in online qualitative studies: From the researcher's perspective
Panicker, A., Nurain, N., Ibrahim, Z., Wang, C.-H. (., Ha, S. W., Wu, Y., Connelly, K., Siek, K. A., & Chung, C.-F. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642732 · Cited by 31 · see citing works
Political Deepfakes Are As Credible As Other Fake Media And (Sometimes) Real Media
Barari, S., Lucas, C., & Munger, K. (2021) · doi:10.31219/osf.io/cdfh3 · Cited by 51 · see citing works
Alanazi, S., Asif, S., & Moulitsas, I. (2024) · International Journal of Social Science and Humanity · doi:10.18178/ijssh.2024.14.2.1194 · Cited by 26 · see citing works
“This can alter a person’s attitude towards another without any actual reason [6].”
BackgroundInfluentialFooled twice – people cannot detect deepfakes but think they can
Köbis, N., Doležalová, B., & Soraperra, I. (2021) · doi:10.2139/ssrn.3832978 · Cited by 194 · see citing works
Wani, T. M., Qadri, S. A. A., Wani, F. A., & Amerini, I. (2024) · Foundations and Trends® in Privacy and Security · doi:10.1561/3300000048 · Cited by 16 · see citing works
Deepfakes and Society: What Lies Ahead?
Gamage, D., Chen, J., Ghasiya, P., & Sasahara, K. (2022) · Studies in Autonomic, Data-driven and Industrial Computing · doi:10.1007/978-981-19-1524-6_1 · Cited by 14 · see citing works
Characterizing AI-Generated Misinformation on Social Media
Drolsbach, C., Demirel, E., & Pröllochs, N. (2025) · arXiv · doi:10.48550/arxiv.2505.10266
“…deepfakes) – artificially generated videos, images, and audio designed to mimic real individuals – have become increasingly prevalent on social media, raising critical concerns about their role in spreading misinformation (Hancock and Bailenson 2021; Groh et al. 2024; Vaccari and Chadwick 2020).”
Influential
- Authors
- Hancock, J. T., & Bailenson, J. N.
- Affiliations
- Stanford University (US)
- Corresponding author
- Hancock, Jeffrey T.
- Bailenson, Jeremy N.
- Venue
- Cyberpsychology, Behavior, and Social Networking
- Publisher
- SAGE Publications
- Published
- 2021-03-01
- Volume
- 24
- Issue
- 3
- Pages
- 149-152
- ISSN
- 2152-2715 (ISSN-L)
- 2152-2723
- OpenAlex
- W3136860328
- Cited by
- 214
- References
- 3
- Citations by year
- 2026: 47 · 2025: 58 · 2024: 54 · 2023: 37 · 2022: 15 · 2021: 3
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cyberpsychology Behavior and Social Networking (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Keywords
- deepfakes, social impact, synthetic media, misinformation, media manipulation
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