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Deepfakes (portmanteau of "deep learning" and "fake"[1]) are synthetic media[2] that have been digitally manipulated to replace one person's likeness convincingly with that of another. It can also refer to computer-generated images of human subjects that do not exist in real life.[3] While the act of creating fake content is not new, deepfakes leverage tools and techniques from machine learning and artificial intelligence,[4][5][6] including facial recognition algorithms and artificial neural networks such as variational autoencoders (VAEs) and generative adversarial networks (GANs).[5][7][8] In turn the field of image forensics develops techniques to detect manipulated images.[9]
Deepfakes have garnered widespread attention for their potential use in creating child sexual abuse material, celebrity pornographic videos, revenge porn, fake news, hoaxes, bullying, and financial fraud.[10][11][12][13] The spreading of disinformation and hate speech through deepfakes has a potential to undermine core functions and norms of democratic systems by interfering with people's ability to participate in decisions that affect them, determine collective agendas and express political will through informed decision-making.[14] This has elicited responses from both industry and government to detect and limit their use.[15][16]
From traditional entertainment to gaming, deepfake technology has evolved to be increasingly convincing[17] and available to the public, allowing the disruption of the entertainment and media industries.[18]
- ^ Brandon, John (16 February 2018). "Terrifying high-tech porn: Creepy 'deepfake' videos are on the rise". Fox News. Archived from the original on 15 June 2018. Retrieved 20 February 2018.
- ^ "Prepare, Don't Panic: Synthetic Media and Deepfakes". witness.org. Archived from the original on 2 December 2020. Retrieved 25 November 2020.
- ^ "Deepfakes, explained". MIT Sloan. 7 March 2024.
- ^ Juefei-Xu, Felix; Wang, Run; Huang, Yihao; Guo, Qing; Ma, Lei; Liu, Yang (1 July 2022). "Countering Malicious DeepFakes: Survey, Battleground, and Horizon". International Journal of Computer Vision. 130 (7): 1678–1734. doi:10.1007/s11263-022-01606-8. ISSN 1573-1405. PMC 9066404. PMID 35528632.
- ^ a b Kietzmann, J.; Lee, L. W.; McCarthy, I. P.; Kietzmann, T. C. (2020). "Deepfakes: Trick or treat?" (PDF). Business Horizons. 63 (2): 135–146. doi:10.1016/j.bushor.2019.11.006. S2CID 213818098.
- ^ Waldrop, M. Mitchell (16 March 2020). "Synthetic media: The real trouble with deepfakes". Knowable Magazine. Annual Reviews. doi:10.1146/knowable-031320-1. Retrieved 19 December 2022.
- ^ Schwartz, Oscar (12 November 2018). "You thought fake news was bad? Deep fakes are where truth goes to die". The Guardian. Archived from the original on 16 June 2019. Retrieved 14 November 2018.
- ^ Charleer, Sven (17 May 2019). "Family fun with deepfakes. Or how I got my wife onto the Tonight Show". Medium. Archived from the original on 11 February 2018. Retrieved 8 November 2019.
- ^ Farid, Hany (15 September 2019). "Image Forensics". Annual Review of Vision Science. 5 (1): 549–573. doi:10.1146/annurev-vision-091718-014827. ISSN 2374-4642. PMID 31525144. S2CID 263558880.
- ^ Banks, Alec (20 February 2018). "What Are Deepfakes & Why the Future of Porn is Terrifying". Highsnobiety. Archived from the original on 14 July 2021. Retrieved 20 February 2018.
- ^ Christian, Jon. "Experts fear face swapping tech could start an international showdown". The Outline. Archived from the original on 16 January 2020. Retrieved 28 February 2018.
- ^ Roose, Kevin (4 March 2018). "Here Come the Fake Videos, Too". The New York Times. ISSN 0362-4331. Archived from the original on 18 June 2019. Retrieved 24 March 2018.
- ^ Schreyer, Marco; Sattarov, Timur; Reimer, Bernd; Borth, Damian (October 2019). "Adversarial Learning of Deepfakes in Accounting". arXiv:1910.03810 [cs.LG].
- ^ Pawelec, M (2022). "Deepfakes and Democracy (Theory): How Synthetic Audio-Visual Media for Disinformation and Hate Speech Threaten Core Democratic Functions". Digital Society: Ethics, Socio-legal and Governance of Digital Technology. 1 (2): 19. doi:10.1007/s44206-022-00010-6. PMC 9453721. PMID 36097613.
- ^ Cite error: The named reference
Ghoshal-2018was invoked but never defined (see the help page). - ^ Cite error: The named reference
Clarke-2019was invoked but never defined (see the help page). - ^ Caramancion, Kevin Matthe (21 April 2021). "The Demographic Profile Most at Risk of being Disinformed". 2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS). IEEE. pp. 1–7. doi:10.1109/iemtronics52119.2021.9422597. ISBN 978-1-6654-4067-7. S2CID 234499888.
- ^ Lalla, Vejay; Mitrani, Adine; Harned, Zach. "Artificial Intelligence: Deepfakes in the Entertainment Industry". World Intellectual Property Organization. Retrieved 8 November 2022.