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Deep learning is currently the most prominent and widely successful method in artificial intelligence. Despite having played an active role in earlier artificial intelligence and neural network research, philosophers have been largely silent on this technology so far. This is remarkable, given that deep learning neural networks have blown past predicted upper limits on artificial intelligence performance—recognizing complex objects in natural photographs and defeating world champions in strategy games as complex as Go and chess—yet there remains no universally accepted explanation (...) |
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That photography is a supremely realistic medium may be the commonsense view, but—as Edward Steichen reminds us—it is by no means universal. Dissenters note how unlike reality a photograph is and how unlikely we are to confuse the one with the other. They point to “distortions” engendered by the photographic process and to the control which the photographer exercises over the finished product, the opportunities he enjoys for interpretation and falsification. Many emphasize the expressive nature of the medium, observing that (...) |
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That photography is a supremely realistic medium may be the commonsense view, but—as Edward Steichen reminds us—it is by no means universal. Dissenters note how unlike reality a photograph is and how unlikely we are to confuse the one with the other. They point to “distortions” engendered by the photographic process and to the control which the photographer exercises over the finished product, the opportunities he enjoys for interpretation and falsification. Many emphasize the expressive nature of the medium, observing that (...) |
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A widespread view among philosophers and scientists is that recorded sounds and assisted hearing differ fundamentally from natural sounds and direct hearing. It is commonly claimed, for example, that the sounds we hear over the phone are not sounds emitted by the voice of our interlocutor, but the sounds reproduced by the phone’s loudspeaker. According to this view, hearing distant sounds through communication and audio equipment is at best indirect and at worst illusory. In what follows, I shall reject these (...) |
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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. (...) |
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AI, especially in the case of Deepfakes, has the capacity to undermine our confidence in the original, genuine, authentic nature of what we see and hear. And yet digital technologies, in the form of databases and other detection tools also make it easier to spot forgeries and to establish the authenticity of a work. Using the notion of ectypes, this paper discusses current conceptions of authenticity and reproduction and examines how, in the future, these might be adapted for use in (...) |
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Deepfakes are realistic videos created using new machine learning techniques rather than traditional photographic means. They tend to depict people saying and doing things that they did not actually say or do. In the news media and the blogosphere, the worry has been raised that, as a result of deepfakes, we are heading toward an “infopocalypse” where we cannot tell what is real from what is not. Several philosophers have now issued similar warnings. In this paper, I offer an analysis (...) |
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Deepfake technology uses machine learning to fabricate video and audio recordings that represent people doing and saying things they've never done. In coming years, malicious actors will likely use this technology in attempts to manipulate public discourse. This paper prepares for that danger by explicating the unappreciated way in which recordings have so far provided an epistemic backstop to our testimonial practices. Our reasonable trust in the testimony of others depends, to a surprising extent, on the regulative effects of the (...) |
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