The identification game: deepfakes and the epistemic limits of identity

Author:

Öhman CarlORCID

Abstract

AbstractThe fast development of synthetic media, commonly known as deepfakes, has cast new light on an old problem, namely—to what extent do people have a moral claim to their likeness, including personally distinguishing features such as their voice or face? That people have at least some such claim seems uncontroversial. In fact, several jurisdictions already combat deepfakes by appealing to a “right to identity.” Yet, an individual’s disapproval of appearing in a piece of synthetic media is sensible only insofar as the replication is successful. There has to be some form of (qualitative) identity between the content and the natural person. The question, therefore, is how this identity can be established. How can we know whether the face or voice featured in a piece of synthetic content belongs to a person who makes claim to it? On a trivial level, this may seem an easy task—the person in the video is A insofar as he or she is recognised as being A. Providing more rigorous criteria, however, poses a serious challenge. In this paper, I draw on Turing’s imitation game, and Floridi’s method of levels of abstraction, to propose a heuristic to this end. I call it the identification game. Using this heuristic, I show that identity cannot be established independently of the purpose of the inquiry. More specifically, I argue that whether a person has a moral claim to content that allegedly uses their identity depends on the type of harm under consideration.

Funder

Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society

Uppsala University

Publisher

Springer Science and Business Media LLC

Subject

General Social Sciences,Philosophy

Reference37 articles.

1. Bakker, J. (2020). Deepfakes affecting reputation a study comparing effects of different levels of (fake) media on reputation. MSc Thesis, Einhoven University, Industrial Engineering and Innovation Sciences

2. Bitouk, D., Kumar, N., Dhillon, S., Belhumeur, P., & Nayar, S. K. (2008). Face swapping: Automatically replacing faces in photographs. ACM Transactions on Graphics. https://doi.org/10.1145/1360612.1360638

3. Butler, J. (1999). Gender trouble: Feminism and the subversion of identity. Routledge.

4. Citron, D. K., & Chesney, R. (2019). Deep fakes: A looming challenge for privacy, democracy, and deep fakes: A looming challenge for privacy, democracy, and national security national security. HeinOnline. https://scholarship.law.bu.edu/faculty_scholarship/640

5. Corcoran, M., Henry, M. (2021). The Tom Cruise deepfake that set off 'terror' in the heart of Washington DC. ABC News. Retrieved 13 October 2021 from: https://www.abc.net.au/news/2021-06-24/tom-cruise-deepfake-chris-ume-security-washington-dc/100234772

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deepfakes: a survey and introduction to the topical collection;Synthese;2024-06-26

2. NFTs for combating deepfakes and fake metaverse digital contents;Internet of Things;2024-04

3. Deepfake Pornography and the Ethics of Non-Veridical Representations;Philosophy & Technology;2023-08-26

4. On the Philosophy of Unsupervised Learning;Philosophy & Technology;2023-04-21

5. The Spiral of Digital Falsehood in Deepfakes;International Journal for the Semiotics of Law - Revue internationale de Sémiotique juridique;2023-01-19

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3