[Author note: There is a video explainer of this paper on youtube at the new work in philosophy channel (search for surname+deepfakes).] -/- It is widely thought that deepfake videos are a significant and unprecedented threat to our epistemic practices. In some writing about deepfakes, manipulated videos appear as the harbingers of an unprecedented _epistemic apocalypse_. In this paper I want to take a critical look at some of the more catastrophic predictions about deepfake videos. I will argue for three (...) claims: (1) that once we recognise the role of social norms in the epistemology of recordings, deepfakes are much less concerning, (2) that the history of photographic manipulation reveals some important precedents, correcting claims about the novelty of deepfakes, and (3) that proposed solutions to deepfakes have been overly focused on technological interventions. My overall goal is not so much to argue that deepfakes are not a problem, but to argue that behind concerns around deepfakes lie a more general class of social problems about the organisation of our epistemic practices. (shrink)

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 (...) of why deepfakes are such a serious threat to knowledge. Utilizing the account of information carrying recently developed by Brian Skyrms, I argue that deepfakes reduce the amount of information that videos carry to viewers. I conclude by drawing some implications of this analysis for addressing the epistemic threat of deepfakes. (shrink)

Political deepfakes have prompted outcry about the diminishing trustworthiness of visual depictions, and the epistemic and political threat this poses. Yet this new technique is being used overwhelmingly to create pornography, raising the question of what, if anything, is wrong with the creation of deepfake pornography. Traditional objections focusing on the sexual abuse of those depicted fail to apply to deepfakes. Other objections—that the use and consumption of pornography harms the viewer or other (non-depicted) individuals—fail to explain the objection that (...) a depicted person might have to the creation of deepfake pornography that utilises images of them. My argument offers such an explanation. It begins by noting that the creation of sexual images requires an act of consent, separate from any consent needed for the acts depicted. Once we have separated these out, we can see that a demand for consent can arise when a sexual image is of us, even when no sexual activity was actually engaged in, as in the case of deepfake pornography. I then demonstrate that there are two ways in which an image can be ‘of us’, both of which can exist in the case of deepfakes. Thus, I argue: if a person, their likeness, or their photograph is used to create pornography, their consent is required. Whenever the person depicted does not consent (or in the case of children, can’t consent), that person is wronged by the creation of deepfake pornography and has a claim against its production. (shrink)

This paper defends two main theses related to emerging deepfake technology. First, fears that deepfakes will bring about epistemic catastrophe are overblown. Such concerns underappreciate that the evidential power of video derives not solely from its content, but also from its source. An audience may find even the most realistic video evidence unconvincing when it is delivered by a dubious source. At the same time, an audience may find even weak video evidence compelling so long as it is delivered by (...) a trusted source. The growing prominence of deepfake content is unlikely to change this fundamental dynamic. Thus, through appropriate patterns of trust, whatever epistemic threat deepfakes pose can be substantially mitigated. The second main thesis is that focusing on deepfakes that are intended to deceive, as epistemological discussions of the technology tend to do, threatens to overlook a further effect of this technology. Even where deepfake content is not regarded by its audience as veridical, it may cause its viewers to develop psychological associations based on that content. These associations, even without rising to the level of belief, may be harmful to the individuals depicted and more generally. Moreover, these associations may develop in cases in which the video content is realistic, but the audience is dubious of the content in virtue of skepticism toward its source. Thus, even if—as I suggest—epistemological concerns about deepfakes are overblown, deepfakes may nonetheless be psychologically impactful and may do great harm. (shrink)

Deepfakes are extremely realistic audio/video media. They are produced via a complex machine-learning process, one that centrally involves training an algorithm on hundreds or thousands of audio/video recordings of an object or person, S, with the aim of either creating entirely new audio/video media of S or else altering existing audio/video media of S. Deepfakes are widely predicted to have deleterious consequences (principally, moral and epistemic ones) for both individuals and various of our social practices and institutions. In this introduction (...) to the Topical Collection, I first survey existing philosophical research on deepfakes (Sects. 2 and 3). I then give an overview of the papers that comprise the Collection (Sect. 4). Finally, I conclude with remarks on a line of argument made in a number of papers in the Topical Collection: that deepfakes may cause their own demise (Sect. 5). (shrink)

Deepfakes and other forms of synthetic media are widely regarded as serious threats to our knowledge of the world. Various technological responses to these threats have been proposed. The reactive approach proposes to use artificial intelligence to identify synthetic media. The proactive approach proposes to use blockchain and related technologies to create immutable records of verified media content. I argue that both approaches, but especially the reactive approach, are vulnerable to a problem analogous to the ancient problem of the criterion—a (...) line of argument with skeptical implications. I argue that, while the proactive approach is relatively resistant to this objection, it faces its own serious challenges. In short, the proactive approach would place a heavy burden on users to verify their own content, a burden that is exacerbated by and is likely to exacerbate existing inequalities. (shrink)

Deepfake technology presents significant ethical challenges. The ability to produce realistic looking and sounding video or audio files of people doing or saying things they did not do or say brings with it unprecedented opportunities for deception. The literature that addresses the ethical implications of deepfakes raises concerns about their potential use for blackmail, intimidation, and sabotage, ideological influencing, and incitement to violence as well as broader implications for trust and accountability. While this literature importantly identifies and signals the potentially (...) far-reaching consequences, less attention is paid to the moral dimensions of deepfake technology and deepfakes themselves. This article will help fill this gap by analysing whether deepfake technology and deepfakes are intrinsically morally wrong, and if so, why. The main argument is that deepfake technology and deepfakes are morally suspect, but not inherently morally wrong. Three factors are central to determining whether a deepfake is morally problematic: whether the deepfaked person would object to the way in which they are represented; whether the deepfake deceives viewers; and the intent with which the deepfake was created. The most distinctive aspect that renders deepfakes morally wrong is when they use digital data representing the image and/or voice of persons to portray them in ways in which they would be unwilling to be portrayed. Since our image and voice are closely linked to our identity, protection against the manipulation of hyper-realistic digital representations of our image and voice should be considered a fundamental moral right in the age of deepfakes. (shrink)

Deepfakes raise various concerns: risks of political destabilization, depictions of persons without consent and causing them harms, erosion of trust in video and audio as reliable sources of evidence, and more. These concerns have been the focus of recent work in the philosophical literature on deepfakes. However, there has been almost no sustained philosophical analysis of deepfakes from the perspective of concerns about honesty and dishonesty. That deepfakes are potentially deceptive is unsurprising and has been noted. But under what conditions (...) does the use of deepfakes fail to be honest? And which human agents, involved in one way or another in a deepfake, fail to be honest, and in what ways? If we are to understand better the morality of deepfakes, these questions need answering. Our first goal in this paper, therefore, is to offer an analysis of paradigmatic cases of deepfakes in light of the philosophy of honesty. While it is clear that many deepfakes are morally problematic, there has been a rising counter-chorus claiming that deepfakes are not essentially morally bad, since there might be uses of deepfakes that are not morally wrong, or even that are morally salutary, for instance, in education, entertainment, activism, and other areas. However, while there are reasons to think that deepfakes can supply or support moral goods, it is nevertheless possible that even these uses of deepfakes are dishonest. Our second goal in this paper, therefore, is to apply our analysis of deepfakes and honesty to the sorts of deepfakes hoped to be morally good or at least neutral. We conclude that, perhaps surprisingly, in many of these cases the use of deepfakes will be dishonest in some respects. Of course, there will be cases of deepfakes for which verdicts about honesty and moral permissibility do not line up. While we will sometimes suggest reasons why moral permissibility verdicts might diverge from honesty verdicts, we will not aim to settle matters of moral permissibility. (shrink)

Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of synthetic audiovisual (...) media, its place within a broader taxonomy of audiovisual media, and how deep learning techniques differ from more traditional approaches to media synthesis. After reviewing important etiological features of deep learning pipelines for media manipulation and generation, I argue that “deepfakes” and related synthetic media produced with such pipelines do not merely offer incremental improvements over previous methods, but challenge traditional taxonomical distinctions, and pave the way for genuinely novel kinds of audiovisual media. (shrink)

Deepfakes are audio, video, or still-image digital artifacts created by the use of artificial intelligence technology, as opposed to traditional means of recording. Because deepfakes can look and sound much like genuine digital recordings, they have entered the popular imagination as sources of serious epistemic problems for us, as we attempt to navigate the increasingly treacherous digital information environment of the internet. In this paper, I attempt to clarify what epistemic problems deepfakes pose and why they pose these problems, by (...) drawing parallels between recordings and our own senses as sources of evidence. I show that deepfakes threaten to undermine the status of digital recordings as evidence. The existence of deepfakes thus encourages a kind of skepticism about digital recordings that bears important similarities to classic philosophical skepticism concerning the senses. However, the skepticism concerning digital recordings that deepfakes motivate is also importantly different from classical skepticism concerning the senses, and I argue that these differences illuminate some possible strategies for solving the epistemic problems posed by deepfakes. (shrink)

There is a wealth of resources— ideas, insights, discoveries, inventions, traditions, cultures, languages, arts, religions, sciences, narratives, stories, poems, customs and norms, music and songs, games and personal experiences, and advertisements—that we produce, curate, consume, transmit, and inherit as humans. This wealth, which I define as semantic capital, gives meaning to, and makes sense of, our own existence and the world surrounding us. It defines who we are and enables humans to develop an individual and social life. This paper discusses (...) the shift from analog to digital semantic capital, and the extent to which this might affect the semanticisation of our identities, our lives and our realities. -/- . (shrink)

The recent success of Generative AI (GenAI) has heralded a new era in content creation, dissemination, and consumption. This technological revolution is reshaping our understanding of content, challenging traditional notions of authorship, and transforming the relationship between content producers and consumers. As we approach an increasingly AI-integrated world, examining the implications of this paradigm shift is crucial. This article explores the future of content in the age of GenAI, analysing the evolving definition of content, the transformations brought about by GenAI (...) systems, and emerging models of content production and dissemination. By examining these aspects, we can gain valuable insights into the challenges and opportunities that lie ahead in the realm of content creation and consumption and, hopefully, manage them more successfully. (shrink)

Essentialists understand authenticity as an inherent quality of a person, object, artifact, or place, whereas constructionists consider authenticity as a social creation without any pre-given essence, factuality, or reality. In this paper, we move beyond the essentialist-constructionist dichotomy. Rather than focusing on the question whether authenticity can be found or needs to be constructed, we hook into the idea that authenticity is an interactive, culturally informed process of negotiation. In addition to essentialist and constructionist approaches, we discuss a third, less (...) well-known approach that cannot be reduced to any of the two forms. This approach celebrates the authenticity of inauthenticity by amplifying the made. We argue that the value of authenticity lies not in choosing for one of these approaches, but in the degree to which the process of negotiating authenticity enables a critical formation of selves and societies. Authenticity is often invoked as a method of social control or a mark of power relations: once something is defined as authentic, it is no longer questioned. Emerging technologies—especially data-driven technologies—have the capacity to conceal these power relations, propel a shift in power, and dominate authentication processes. This raises the question how processes of authentication can contribute to a critical formation of selves and societies, against the backdrop of emerging technologies. We argue in favor of an interactionist approach of authenticity and discuss the importance of creating space in authentication processes that are increasingly influenced by technology as an invisible actor. (shrink)

Las Falsificaciones Profundas (Deep fake) constituyen una evolución tecnológica, que expresa un cambio radical en la manera en que se produce, se divulga y maneja de manera inadecuada la información. Ello podría llevar a que este hecho, mal maniobrado, se convierta en una amenaza cada vez más grave para individuos, organizaciones y la sociedad en su conjunto, al formar parte de un desarrollo sin precedentes en el ecosistema de la desinformación. A partir de esta inquietud, el objetivo de este artículo (...) es incursionar en el debate sobre las preocupaciones y soluciones educativas frente a los usos maliciosos de la “Tecnología Deep Fake” (TDF), colocando la atención en que los problemas que se puedan generar en estos ámbitos, es desde la transformación y puesta en práctica de la consolidación de valores que enarbolen la ética como principio básico que distingue la naturaleza humana en su expresión más civilizada, en lo cual no se descartan las funciones que podrían desempeñar la tecnología, el componente legal y las políticas gubernamentales y privadas. Se empleó el método de análisis documental aplicando la triangulación de autores lo que permitió deslindar las causas y soluciones educativas frente al Deep Fake, obteniendo como resultado, una propuesta de soluciones educativas frente a sus usos maliciosos. La conclusión central es que el enfrentamiento a los problemas que causa el inapropiado empleo de la “Tecnología Deep Fake” (TDF), pasa por el trabajo educativo que se realice en los escenarios en que convivimos. (shrink)

Deepfakes, as hyperrealistic digital fabrications, reveal gaps and uncertainties in existing ontological frameworks. Neither simply images nor realities, deepfakes occupy an ambiguous metaphysical position between concepts such as representation/simulation, human/machine, and real/artificial. Their emergent generation via AI and experiential traction as credible synthetic media underscores limitations in prevailing paradigms reliant on purified binaries and anthropocentric assumptions. Rather than anomalies, deepfakes epitomize the imperative for new ontological cartographies and conceptual vocabularies attuned to increasingly unbounded algorithmic creation. The paper surveys debates about (...) digital objects and theories of representation to contextualize this argument. Deepfakes’ ontological novelty stems from their ambiguous origins, autonomous proliferation, and infiltration of perceivable situations with credible fictions. This destabilizes ontological foundations such as creative intentionality and indexical truth. I conclude deepfakes signal the insufficiency of existing ontology for navigating realities transformed by generative technologies. New paradigms are needed that grapple with their radical metaphysical challenges. (shrink)

El “Foro de Montreal sobre el desarrollo socialmente responsable de la inteligencia artificial” fue una conferencia que inició en noviembre de 2017, donde más de 400 participantes de diversos sectores y disciplinas discutieron las implicaciones éticas y sociales de la IA. La conferencia también condujo a la creación de la “Declaración de Montreal para un desarrollo responsable de la inteligencia artificial” que se dio a conocer a finales de 2018 con más de 500 signatarios. La declaración describe 10 principios y (...) 59 recomendaciones para guiar el desarrollo de la IA de manera que respete la dignidad humana, la autonomía, la justicia y la democracia. Los principios de la ética de la IA de Montreal también han sido criticados. Por ejemplo, se argumenta que no cubre el posible uso malicioso de la IA para actividades como la guerra, la vigilancia o la propaganda personalizada, y no ofrecen orientaciones ni mecanismos específicos para su aplicación y cumplimiento. De cualquier modo, se considera un importante paso en el desarrollo de la ética de la IA y ha sido amplia- mente reconocida por su enfoque global e integrador, y como punto de referencia para los esfuerzos posteriores. (shrink)