Deepfakes, fake barns, and knowledge from videos
Deepfakes, fake barns, and knowledge from videos
Recent develops in AI technology have led to increasingly sophisticated forms of video manipulation. One such form has been the advent of deepfakes. Deepfakes are AI-generated videos that typically depict people doing and saying things they never did. In this paper, I demonstrate that there is a close structural relationship between deepfakes and more traditional fake barn cases in epistemology. Specifically, I argue that deepfakes generate an analogous degree of epistemic risk to that which is found in traditional cases. Given that barn cases have posed a long-standing challenge for virtue-theoretic accounts of knowledge, I consider whether a similar challenge extends to deepfakes. In doing so, I consider how Duncan Pritchard’s recent anti-risk virtue epistemology meets the challenge. While Pritchard’s account avoids problems in traditional barn cases, I claim that it leads to local scepticism about knowledge from online videos in the case of deepfakes. I end by considering how two alternative virtue-theoretic approaches might vindicate our epistemic dependence on videos in an increasingly digital world.
Cognitive ability, Deepfakes, Environmental luck, Epistemic risk, Knowledge
Matthews, Taylor
fe7b28dd-5d3d-4cb5-a464-66c5a1e83e6d
2023
Matthews, Taylor
fe7b28dd-5d3d-4cb5-a464-66c5a1e83e6d
Abstract
Recent develops in AI technology have led to increasingly sophisticated forms of video manipulation. One such form has been the advent of deepfakes. Deepfakes are AI-generated videos that typically depict people doing and saying things they never did. In this paper, I demonstrate that there is a close structural relationship between deepfakes and more traditional fake barn cases in epistemology. Specifically, I argue that deepfakes generate an analogous degree of epistemic risk to that which is found in traditional cases. Given that barn cases have posed a long-standing challenge for virtue-theoretic accounts of knowledge, I consider whether a similar challenge extends to deepfakes. In doing so, I consider how Duncan Pritchard’s recent anti-risk virtue epistemology meets the challenge. While Pritchard’s account avoids problems in traditional barn cases, I claim that it leads to local scepticism about knowledge from online videos in the case of deepfakes. I end by considering how two alternative virtue-theoretic approaches might vindicate our epistemic dependence on videos in an increasingly digital world.
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Accepted/In Press date: 27 December 2022
e-pub ahead of print date: 23 January 2023
Published date: 2023
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I would like to thank audiences at the University of Nottingham and Cardiff University, respectively, for valuable feedback on earlier iterations of this paper. I would also like to extend my upmost thanks to J. Adam Carter, Dan Cavedon-Taylor, Michael Hannon, Ian James Kidd, and two anonymous referees at Synthese for their constructive feedback that helped improve this paper. This paper was written whilst in receipt of a Midlands4Cities Doctoral Training Scholarship, for which I very grateful.
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© 2023, The Author(s).
Keywords:
Cognitive ability, Deepfakes, Environmental luck, Epistemic risk, Knowledge
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Local EPrints ID: 483682
URI: http://eprints.soton.ac.uk/id/eprint/483682
ISSN: 0039-7857
PURE UUID: 8bed36ad-8bad-4a3f-b1e8-927a3058ca8f
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Date deposited: 03 Nov 2023 17:51
Last modified: 17 Mar 2024 05:36
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Taylor Matthews
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