The DOI matches its Crossref record; 26 of the 28 references it cites were found in a registry or an index.
Introducing the pervert’s dilemma: a contribution to the critique of Deepfake Pornography
Open accessAbstract
Recent technological innovation has made video doctoring increasingly accessible. This has given rise to Deepfake Pornography, an emerging phenomenon in which Deep Learning algorithms are used to superimpose a person’s face onto a pornographic video. Although to most people, Deepfake Pornography is intuitively unethical, it seems difficult to justify this intuition without simultaneously condemning other actions that we do not ordinarily find morally objectionable, such as sexual fantasies. In the present article, I refer to this contradiction as the pervert’s dilemma. I propose that the method of Levels of Abstraction, a philosophical mode of enquiry inspired by Formal Methods in computer science, can be employed to formulate at least one possible solution to the dilemma. From this perspective, the permissibility of some actions appears to depend on the degree to which they are abstracted from their natural context. I conclude that the dilemma can only be solved when considered at low levels of abstractions, when Deepfakes are situated in the macro-context of gender inequality.
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“However, it should be kept in mind that, as highlighted by several scholars, deepfake intimate images can still harm even if manifestly false .”
From Designed to abuse? Deepfakes and the non-consensual diffusion of intimate images (2023) · cites this paper as Öhman, 2020
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Deepfake Detection: A Systematic Literature Review
Rana, M. S., Nobi, M. N., Murali, B., & Sung, A. H. (2022) · IEEE Access · doi:10.1109/access.2022.3154404 · Cited by 573
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The Distinct Wrong of Deepfakes
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Seeing is Believing: Exploring Perceptual Differences in DeepFake Videos
Tahir, R., Batool, B., Jamshed, H., Jameel, M., Anwar, M., Ahmed, F., Zaffar, M. A., & Zaffar, M. F. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445699 · Cited by 79
Metadata
- Authors
- Öhman, C.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Öhman, Carl
- ORCID
- Öhman, Carl
- Venue
- Ethics and Information Technology
- Published
- 2019-11-19
- Volume
- 22
- Issue
- 2
- Pages
- 133-140
- ISSN
- 1388-1957 (ISSN-L)
- 1572-8439
- OpenAlex
- W2989861661
- Cited by
- 130
- References
- 28
- Citations by year
- 2026: 36 · 2025: 21 · 2024: 22 · 2023: 22 · 2022: 17 · 2021: 9 · 2020: 3
- FWCI
- 12.67
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Ethics and Information Technology (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Bioethics and Human Rights Issues
- Social Sciences › Arts and Humanities › Philosophy › Philosophical Ethics and Theory
- Keywords
- deepfake pornography, deep learning, sexual fantasies, levels of abstraction, formal methods, gender inequality, ethics of pornography, moral intuitions
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