Deepfakes, Fake Barns, and Knowledge from Videos

被引:6
|
作者
Matthews, Taylor [1 ]
机构
[1] Univ Nottingham, Dept Philosophy, Nottingham, England
关键词
Deepfakes; Knowledge; Environmental luck; Epistemic risk; Cognitive ability;
D O I
10.1007/s11229-022-04033-x
中图分类号
N09 [自然科学史]; B [哲学、宗教];
学科分类号
01 ; 0101 ; 010108 ; 060207 ; 060305 ; 0712 ;
摘要
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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页数:18
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