Deepfake technology can be used to produce videos of real individuals, saying and doing things that they never in fact said or did, that appear highly authentic. Having accepted the premise that Deepfake content can constitute a legitimate form of expression, it is not immediately clear where the rights of content producers and distributors end, and where the rights of individuals whose likenesses are used in this content begin. This paper explores the question of whether it can be plausibly argued (...) that Deepfake content involving the likenesses of real individuals violates the rights of these individuals. (shrink)

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 (...) ever-present possibility of recordings of the events they testify about. As deepfakes erode the epistemic value of recordings, we may then face an even more consequential challenge to the reliability of our testimonial practices themselves. (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 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 (sections 2 and 3). I then give an overview of the papers that comprise the Collection (section 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 (section 5). (shrink)

Deepfakes are algorithmically modified video and audio recordings that project one person’s appearance on to that of another, creating an apparent recording of an event that never took place. Many scholars and journalists have begun attending to the political risks of deepfake deception. Here we investigate other ways in which deepfakes have the potential to cause deeper harms than have been appreciated. First, we consider a form of objectification that occurs in deepfaked ‘frankenporn’ that digitally fuses the parts (...) of different women to create pliable characters incapable of giving consent to their depiction. Next, we develop the idea of ‘illocutionary wronging’, in which an individual is forced to engage in speech acts they would prefer to avoid in order to deny or correct the misleading evidence of a publicized deepfake. Finally, we consider the risk that deepfakes may facilitate campaigns of ‘panoptic gaslighting’, where many systematically altered recordings of a single person's life undermine their memory, eroding their sense of self and ability to engage with others. Taken together, these harms illustrate the roles that social epistemology and technological vulnerabilities play in human ethical life. (shrink)

The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask participants to identify which is which. We compare the performance of ordinary human observers with the leading computer vision deepfake detection model and find them similarly accurate, while making different kinds of mistakes. Together, participants with access to the model’s (...) prediction are more accurate than either alone, but inaccurate model predictions often decrease participants’ accuracy. To probe the relative strengths and weaknesses of humans and machines as detectors of deepfakes, we examine human and machine performance across video-level features, and we evaluate the impact of preregistered randomized interventions on deepfake detection. We find that manipulations designed to disrupt visual processing of faces hinder human participants’ performance while mostly not affecting the model’s performance, suggesting a role for specialized cognitive capacities in explaining human deepfake detection performance. -/- . (shrink)

[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)

We investigate the question of whether (and if so why) creating or distributing deepfake pornography of someone without their consent is inherently objectionable. We argue that nonconsensually distributing deepfake pornography of a living person on the internet is inherently pro tanto wrong in virtue of the fact that nonconsensually distributing intentionally non-veridical representations about someone violates their right that their social identity not be tampered with, a right which is grounded in their interest in being able to exercise autonomy over (...) their social relations with others. We go on to suggest that nonconsensual deepfakes are especially worrisome in connection with this right because they have a high degree of phenomenal immediacy, a property which corresponds inversely to the ease with which a representation can be doubted. We then suggest that nonconsensually creating and privately consuming deepfake pornography is worrisome but may not be inherently pro tanto wrong. Finally, we discuss the special issue of whether nonconsensually distributing deepfake pornography of a deceased person is inherently objectionable. We argue that the answer depends on how long it has been since the person died. (shrink)

This paper takes up the question of how videographic public announcements (VPAs)---i.e. videos that a wide swath of the public sees and knows that everyone else can see too--- have functioned to mobilize people politically, and how the presence of deepfakes in our information environment stands to change the dynamics of this mobilization. Existing work by Regina Rini, Don Fallis and others has focused on the ways that deepfakes might interrupt our acquisition of first-order knowledge through videos. But (...) I point out that even where every audience member takes a video to be veridical, where first-order knowledge acquisition is secure, an audience aware of deepfakes in their environment will not acquire higher order knowledge in the way that has erstwhile been characteristic for audiences of VPAs. Engaging with ideas from the literatures on public announcement logic, common knowledge, and convention, I enumerate a variety of ways in which we should expect this absence of higher order knowledge to throw up barriers to political mobilization. I go on to apply my analysis of VPAs to the mechanisms by which an uptick in publicly available videos of police brutality over the last decade, mediated by camera phones and social media, was responsible for the largest mass protests in US history in summer 2020. This makes vivid the stakes of the transformation in our mobilizing environment that I've claimed deepfakes effect: where we lose the common-knowledge-generating effects of VPAs, there are fresh obstacles to this sort of mass mobilization. (shrink)

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. (shrink)

Deepfakes are fake recordings generated by machine learning algorithms. Various philosophical explanations have been proposed to account for their epistemic harmfulness. In this paper, I argue that deepfakes are epistemically harmful because they undermine trust in recording technology. As a result, we are no longer entitled to our default doxastic attitude of believing that P on the basis of a recording that supports the truth of P. Distrust engendered by deepfakes changes the epistemic status of recordings to (...) resemble that of handmade images. Their credibility, like that of testimony, depends partly on the credibility of the source. I consider some proposed technical solutions from a philosophical perspective to show the practical relevance of these suggestions. (shrink)

In recent years, a number of philosophers have turned their attention to developments in Artificial Intelligence, and in particular to deepfakes. A deepfake is a portmanteau of ‘deep learning' and ‘fake', and for the most part they are videos which depict people doing and saying things they never did. As a result, much of the emerging literature on deepfakes has turned on questions of trust, harms, and information-sharing. In this paper, I add to the emerging concerns around (...) class='Hi'>deepfakes by drawing on resources from vice epistemology. As deepfakes become more sophisticated, I claim, they will develop to be a source of online epistemic corruption. More specifically, they will encourage consumers of digital online media to cultivate and manifest various epistemic vices. My immediate focus in this paper is on their propensity to encourage the development of what I call ‘intellectual cynicism'. After sketching a rough account of this epistemic vice, I go on to suggest that we can partially offset such cynicism – and fears around deceptive online media more generally – by encouraging the development what I term a trained ‘digital sensibility'. This, I contend, involves a calibrated sensitivity to the epistemic merits of online content. (shrink)

Deepfake technology can be used to produce videos of real individuals, saying and doing things that they never in fact said or did, that appear highly authentic. Having accepted the premise that Deepfake content can constitute a legitimate form of expression, it is not immediately clear where the rights of content producers and distributors end, and where the rights of individuals whose likenesses are used in this content begin. This paper explores the question of whether it can be plausibly argued (...) that Deepfake content involving the likenesses of real individuals violates the rights of these individuals. (shrink)

The recent proliferation of deepfakes and other digitally produced deceptive representations has revived the debate on the epistemic robustness of photography and other mechanically produced images. Authors such as Rini (2020) and Fallis (2021) claim that the proliferation of deepfakes pose a serious threat to the reliability and the epistemic value of photographs and videos. In particular, Fallis adopts a Skyrmsian account of how signals carry information (Skyrms, 2010) to argue that the existence of deepfakes significantly reduces (...) the information that images carry about the world, which undermines their reliability as a source of evidence. In this paper, we focus on Fallis’ version of the challenge, but our results can be generalized to address similar pessimistic views such as Rini’s. More generally, we offer an account of the epistemic robustness of photography and videos that allows us to understand these systems of representation as continuous with other means of information transmission we find in nature. This account will then give us the necessary tools to put Fallis’ claims into perspective: using a richer approach to animal signaling based on the signaling model of communication (Maynard-Smith and Harper, 2003), we will claim that, while it might be true that deepfake technology increases the probability of obtaining false positives, the dimension of the epistemic threat involved might still be negligible. (shrink)

Audio and video footage produced with the help of AI can show politicians doing discreditable things that they have not actually done. This is deepfaked material. Deepfakes are sometimes claimed to have special powers to harm the people depicted and their audiences—powers that more traditional forms of faked imagery and sound footage lack. According to some philosophers, deepfakes are particularly “believable,” and widely available technology will soon make deepfakes proliferate. I first give reasons why deepfake technology is (...) not particularly well suited to producing “believable” political misinformation in a sense to be defined. Next, I challenge claims from Don Fallis and Regina Rini about the consequences of the wide availability of deepfakes. My argument is not that deepfakes are harmless, but that their power to do major harm is highly conditional in liberal party political environments that contain sophisticated mass-media. (shrink)

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 the digital sphere. (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)

Would suppressing deepfakes violate freedom of expression norms? The question is pressing because the deepfake phenomenon in its more poisonous manifestations appears to call for a response, and automated targeting of some kind looks to be the most practically viable. Two simple answers are rejected: that deepfakes do not deserve protection under freedom of expression legislation because they are fake by definition; and that deepfakes can be targeted if but only if they are misleadingly presented as authentic. (...) To make progress, following a discussion of why freedom of expression deserves protection in a democracy, the question is reframed. At issue is not whether the arrival of deepfakes brings new and potentially serious dangers (it does), nor whether these dangers call for measures that potentially limit freedom of expression (they do), but whether the need for such measures raises any new and unfamiliar freedom-of-expression challenges. The answer to that question, surprisingly, is no. The balancing act needed to cope with the arrival of deepfakes brings plenty of difficulties, certainly, but none of the measures likely to be effective in tackling deepfake harms raises freedom-of-expression concerns that aren’t familiar from consideration of non-deepfake harms. In that respect, at least, the arrival of deepfakes makes no difference. (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)

In this paper, I present an analysis of the depictive properties of deepfakes. These are videos and pictures produced by deep learning algorithms that automatically modify existing videos and photographs or generate new ones. I argue that deepfakes have an intentional standard of correctness. That is, a deepfake depicts its subject only insofar as its creator intends it to. This is due to the way in which these images are produced, which involves a degree of intentional control similar (...) to that involved in the production of other intentional pictures such as drawings and paintings. This aspect distinguishes deepfakes from real videos and photographs, which instead have a non-intentional standard: their correct interpretation corresponds to the scenes that were recorded by the mechanisms that produced them, and not to what their producers intended them to represent. I show that these depictive properties make deepfakes fit for communicating information in the same way as language and other intentional pictures. That is, they do not provide direct access to the communicated information like non-intentional pictures (e.g., videos and photographs) do. Rather, they convey information indirectly, relying only on the viewer's assumptions about the communicative intentions of the creator of the deepfake. Indirect communication is indeed a prominent function of such media in our society, but it is often overlooked in the philosophical literature. This analysis also explains what is epistemically worrying about deepfakes. With the introduction of this technology, viewers interpreting photorealistic videos and pictures can no longer be sure of which standard to select (i.e., intentional or non-intentional), which makes misinterpretation likely (i.e., they can take an image to have a standard of correctness that it does not have). (shrink)

The illicit diffusion of intimate photographs or videos intended for private use is a troubling phenomenon known as the diffusion of Non-Consensual Intimate Images (NCII). Recently, it has been feared that the spread of deepfake technology, which allows users to fabricate fake intimate images or videos that are indistinguishable from genuine ones, may dramatically extend the scope of NCII. In the present essay, we counter this pessimistic view, arguing for qualified optimism instead. We hypothesize that the growing diffusion of (...) class='Hi'>deepfakes will end up disrupting the status that makes our visual experience of photographic images and videos epistemically and affectively special; and that once divested of this status, NCII will lose much of their allure in the eye of the perpetrators, probably resulting in diminished diffusion. We conclude by offering some caveats and drawing some implications to better understand, and ultimately better counter, this phenomenon. (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)

The moral questions raised by synthetic media are considered in the context of posthumous documentary biography. Two possibilities are explored: firstly, that synthesis of the voice in biographical documentary deceives in a distinctive way and secondly, that it is possible for synthetic media to harm the subject of posthumous documentary.

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)

The 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 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. (shrink)

Deepfakes are a new form of synthetic media that broke upon the world in 2017. Bringing photoshopping to video, deepfakes replace people in existing videos with someone else’s likeness. Currently most of their reach is limited to pornography, and they are also used to discredit people. However, deepfake technology has many epistemic promises and perils, which concern how we fare as knowers. Our goal is to help set an agenda around these matters, to make sure this technology can (...) help realize epistemic rights and epistemic justice and unleash human creativity, rather than inflict epistemic wrongs of any sort. Our project is exploratory in nature, and we do not aim to offer conclusive answers at this early stage. There is a need to remain vigilant to make sure the downsides do not outweigh the upsides, and that will be a tall order. (shrink)

Deepfakes pose a multi-faceted threat to the acquisition of knowledge. It is widely hoped that technological solutions—in the form of artificially intelligent systems for detecting deepfakes—will help to address this threat. I argue that the prospects for purely technological solutions to the problem of deepfakes are dim. Especially given the evolving nature of the threat, technological solutions cannot be expected to prevent deception at the hands of deepfakes, or to preserve the authority of video footage. Moreover, (...) the success of such technologies depends on institutional trust that is in short supply. Finally, outsourcing the discrimination between the real and the fake to automated, largely opaque systems runs the risk of undermining epistemic autonomy. (shrink)

In this paper, I draw a distinction between two types of deepfake, and unpack the deceptive strategies that are made possible by the second. The first category, which has been the focus of existing literature on the topic, consists of those deepfakes that act as a fabricated record of events, talk, and action, where any utterances included in the footage are not addressed to the audience of the deepfake. For instance, a fake video of two politicians conversing with one (...) another. The second category consists of those deepfakes that direct an illocutionary speech act - such as a request, injunction, invitation, or promise - to an addressee who is located outside of the recording. For instance, fake footage of a company director instructing their employee to make a payment, or of a military official urging the populace to flee for safety. Whereas the former category may deceive an audience by giving rise to false beliefs, the latter can more directly manipulate an agent's actions: the speech act's addressee may be moved to accept an invitation or a summons, follow a command, or heed a warning, and in doing so further a deceiver's unethical ends. (shrink)

Everyday (mis)uses of deepfakes define prevailing conceptualizations of what they are and the moral stakes in their deployment. But one complication in understanding deepfakes is that they are not photographic yet nonetheless manipulate lens-based recordings with the intent of mimicking photographs. The harmfulness of deepfakes, moreover, significantly depends on their potential to be mistaken for photographs and on the belief that photographs capture actual events, a tenet known as the transparency thesis, which scholars have somewhat ironically attacked (...) by citing digital imaging techniques as counterexamples. Combining these positions, this paper sets out two core points: (1) that conceptions about the nature of photography introduce imperatives about its uses; and (2) that popular cultural understandings of photography imply normative ideas that infuse our encounters with deepfakes. Within this, I further raise the question of what moral ground deepfakes occupy that allows them to have such a potentially devastating effect. I show that answering this question involves reinstating the notion that photographs are popularly conceived of as transparent. The rejoinder to this argument, however, is that to take the sting out of deepfakes we must, once again, become skeptical of the veracity of all images, including photoreal ones. This kind of critical mindedness was warranted before the invention of photography for both pictorial imprints and written accounts from various media sources. Given this, along with the fact that photographic trickery is nothing new, deepfakes need not push us into a post-truth epistemic abyss, for they imply a decidedly old turn. (shrink)

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. (...) I propose that the method of Levels of Abstraction, a philosophical mode of enquiry inspired by Formal Methods in computer science, can be employed to formulate at least one possible solution to the dilemma. From this perspective, the permissibility of some actions appears to depend on the degree to which they are abstracted from their natural context. I conclude that the dilemma can only be solved when considered at low levels of abstractions, when Deepfakes are situated in the macro-context of gender inequality. (shrink)

The article defines the research field of a semiotically oriented philosophy of digital communication. It lays out its methodological perspective, pointing out how the fake has always been at the center of semiotic research. It traces the origin of deepfakes back to the conception of GANs, whose essential semiotic workings it expounds on. It enucleates the specificities of the digital fake, especially in the production of artificial faces. It reviews the deepfake phenomenon, enunciating its most recent statistics, prevalent areas (...) of application, risks, and opportunities. It surveys the most current literature. It concludes by emphasizing the novelty of a situation in which the fake, in human societies and cultures, is produced mostly by machines. It stresses the desirability for a semiotic and interdisciplinary study of these productions. (shrink)

This paper argues that Michael Polányi’s account of how science, as an institution, establishes knowledge can provide a structure for a future institution capable of countering misinformation, or fake news, and deepfakes. I argue that only an institutional approach can adequately take up the challenge against the corresponding institution of fake news. The fact of filtering news and information may be bothering. It is the threat of censorship and free speech limitation. Instead, I propose that we should indicate reliable (...) information with a trademark and news signing-approved information and brand equity. I offer a method of creating a standard for online news that people can rely on (similar to high-quality shopping products). (shrink)

Deepfakes are highly realistic, albeit fake, audiovisual contents created with AI. This technology allows the use of deceptive audiovisual material that can impersonate someone’s identity to erode their reputation or manipulate the audience. Deepfakes are also one of the applications of AI that can be used in cultural industries and even to produce works of art. On the one hand, it is important to clarify whether deepfakes in arts and culture are free from the ethical dangers mentioned (...) above. On the other hand, there are specific ethical issues in this field of application. Deepfake technologies can be used to include the performance of deceased persons in audiovisual materials for the dissemination of cultural heritage, and to generate images or sounds in the style of real authors, but deepfakes are also potentially misleading by blurring the boundary between artwork and reality, and raise questions about the relationship between technology, artificial creativity and authorship. The answer to these problems requires an analysis of the normative foundations of copyright to accommodate the new role of AI. (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)

Many of our beliefs are acquired online. Online epistemic environments are replete with fake news, fake science, fake photographs and videos, and fake people in the form of trolls and social bots. The purpose of this paper is to investigate the threat that such online fakes pose to the acquisition of knowledge. I argue that fakes can interfere with one or more of the truth, belief, and warrant conditions on knowledge. I devote most of my attention to the effects of (...) online fakes on satisfaction of the warrant condition, as these have received comparatively little attention. I consider three accounts of the conditions under which fakes compromise the warrant condition. I argue for the third of these accounts, according to which the propensity of fakes to exist in an environment threatens warrant acquisition in that environment. Finally, I consider some limitations on the epistemic threat of fakes and suggest some strategies by which this threat can be mitigated. (shrink)

In contrast to China’s efforts to upgrade its system of governance around a stupefying amount of data collection and electronic scoring, countries committed to democracy and human rights did not upgrade their systems. Instead, those countries ended up with surveillance capitalism. It is vital for the survival of those ideas about governance to perform such an upgrade. This paper aims to contribute to that goal. I propose a framework of epistemic actorhood in terms of four roles and characterize digital lifeworlds (...) and what matters about them both in terms of how they fit in with Max Tegmark’s distinctions among stages of life and in terms of how they generate their own episteme, the data episteme, with its immense possibilities of infopower. Epistemic rights that strengthen existing human rights – as part of a fourth generation of rights – are needed to protect epistemic actorhood in those roles. In the long run, we might well need a new kind of right, the right to the exercise of genuinely human intelligence. (shrink)

En el ámbito de la educación superior virtual de la Universidade de Vigo (UVigo, España) existe un servicio de videoconferencia masiva, integrado en el Campus Remoto, que puede emplearse para la docencia virtual; y, opcionalmente, también para la grabación automática de dichas clases en vídeos. La aparición de nuevas tecnologías como la del ultrafalso y la traducción cara a cara permitirán, además de la traducción/doblaje del audio en dicha videoclases, la manipulación de la imagen para que no se note el (...) cambio de idioma al hablar; de manera que la sincronización de labios se realice también de manera automatizada. (shrink)

In the last several months, several major disciplines have started their initial reckoning with what ChatGPT and other Large Language Models (LLMs) mean for them – law, medicine, business among other professions. With a heavy dose of humility, given how fast the technology is moving and how uncertain its social implications are, this article attempts to give some early tentative thoughts on what ChatGPT might mean for bioethics. I will first argue that many bioethics issues raised by ChatGPT are similar (...) to those raised by current medical AI – built into devices, decision support tools, data analytics, etc. These include issues of data ownership, consent for data use, data representativeness and bias, and privacy. I describe how these familiar issues appear somewhat differently in the ChatGPT context, but much of the existing bioethical thinking on these issues provides a strong starting point. There are, however, a few “new-ish” issues I highlight – by new-ish I mean issues that while perhaps not truly new seem much more important for it than other forms of medical AI. These include issues about informed consent and the right to know we are dealing with an AI, the problem of medical deepfakes, the risk of oligopoly and inequitable access related to foundational models, environmental effects, and on the positive side opportunities for the democratization of knowledge and empowering patients. I also discuss how races towards dominance (between large companies and between the U.S. and geopolitical rivals like China) risk sidelining ethics. (shrink)

Recent AI progress led to a boost in beneficial applications from multiple research areas including VR. Simultaneously, in this newly unfolding deepfake era, ethically and security-relevant disagreements arose in the scientific community regarding the epistemic capabilities of present-day AI. However, given what is at stake, one can postulate that for a responsible approach, prior to engaging in a rigorous epistemic assessment of AI, humans may profit from a self-questioning strategy, an examination and calibration of the experience of their own epistemic (...) agency – especially to counteract both intentional misdirection by unethical actors and unintentional epistemic self-sabotage. In this paper, we expound on a new avenue of utilizing AIVR tools to advance an AI-related misdirection awareness of humans in the deepfake era. Firstly, we harness scientific knowledge from the psychology and neuroscience of magic where the study of misdirection techniques is center stage. Secondly, we connect the latter to creativity research linking human creative potential to inspiration from the seemingly impossible. Overall, AIVR could become an empowering experiential testbed for human epistemic agency enabling a better rational evaluation of AI capabilities. However, a misuse of the same type of tools could yield AIVR safety risks if not counteracted preemptively. (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)

In The Foundations of Bioethics, former senior editor of The Journal of Medicine and Philosophy H. Tristram Engelhardt, Jr. radically reassessed the nature and scope of bioethics, as well as the possibilities for this still-young field that he helped found, in light of the prevailing sociohistorical context, which he argued had been inadequately considered by bioethicists. This issue of The Journal of Medicine and Philosophy provides a snapshot of how bioethics is developing in the wake of Engelhardt’s critique. Topics covered (...) include the relation between rule of law and US healthcare policy, the relation between autonomy and consent, the role of rights in bioethical discourse, the debate between naturalism and normativism in the theory of disease, and the question of when human individuals begin to exist. Although no single theme explicitly unites them, the papers in this issue were produced within and are fruitfully read in terms of what Engelhardt influentially characterized as a morally pluralistic postmodernity subsisting amidst the ruins of tradition. In the conclusion, I introduce a further wrinkle into this Engelhardtian picture—namely, the looming danger of a more general epistemological pluralism effected by new technologies like Deepfakes. (shrink)

This original and interdisciplinary volume explores the contemporary semiotic dimensions of the face from both scientific and socio-cultural perspectives, putting forward several traditions, aspects, and signs of the human utopia of creating a hybrid face. The book semiotically delves into the multifaceted realm of the digital face, exploring its biological and social functions, the concept of masks, the impact of COVID-19, AI systems, digital portraiture, symbolic faces in films, viral communication, alien depictions, personhood in video games, online intimacy, and digital (...) memorials. The human face is increasingly living a life that is not only that of the biological body but also that of its digital avatar, spread through a myriad of new channels and transformable through filters, post-productions, digital cosmetics, all the way to the creation of deepfakes. The digital face expresses new and largely unknown meanings, which this book explores and analyzes through an interdisciplinary but systematic approach. The volume will interest researchers, scholars and advanced students who are interested in digital humanities, communication studies, semiotics, visual studies, visual anthropology, cultural studies, and, broadly speaking, in innovative approaches about the meaning of the face in present-day digital societies. (shrink)

The development of computer science has raised ethical concerns regarding the potential negative impacts of machine learning tools on people and society. Some examples are pornographic deepfakes used as weapons of war against women; pattern recognition designed to uncover sexual orientation; and misuse of data and deep learning by private companies to influence democratic elections. We contend that these three examples are cases of automated evil. In this article, we defend that the concept of forbidden knowledge can help to (...) inform a coherent ethical framework in the context of machine learning research. We conclude that restricting generalised access to extensive data and limiting access to ready-to-use codes would mitigate potential harms caused by machine learning tools. In addition, the notions of intersectionality and interdisciplinarity should be systematically introduced in data and computer science research. (shrink)

Until now, the mass spread of fake news and its negative consequences have implied mainly textual content towards a loss of citizens' trust in institutions. Recently, a new type of machine learning framework has arisen, Generative Adversarial Networks (GANs) – a class of deep neural network models capable of creating multimedia content (photos, videos, audio) that simulate accurate content with extreme precision. While there are several areas of worthwhile application of GANs – e.g., in the field of audio-visual production, human-computer (...) interactions, satire, and artistic creativity – their deceptive uses, at least as currently foreseeable, are just as numerous and worrying. The main concern is linked to the so-called “deepfakes”, fake images or videos that simulate real events with extreme precision. When trained on a human face, GANs can make the face assume hyper-realistic movements, expressions and (verbal and non-verbal) communication abilities. This technology poses an urgent threat to the governance of democratic processes concerning the production of public opinions and political discourses, with significant potential for reality-altering and disinformation. After a short introduction of their current technical state-of-the-art, in this paper we want to enquire the GANs` socio-technical system alongside different and intertwined philosophical accounts. Firstly, we will argue about the conditions that make perceived a GANs-generated content as trustworthy, arguing also about the general effects GANs might have on the perceived trustworthiness of individuals. Thereafter, we will discuss about the inadequacy to approach GANs only as perception-altering technology. Against this backdrop, we will propose a theoretical turn that considers the human-machine relationships of trustworthiness as elements of a broader hybrid socio-technical systems. This turn come up with political repercussions that we will discuss in the last part of the paper. (shrink)

The research is devoted to a discussion of social and humanitarian problems associated with tectonic changes in human life against the backdrop of total digitalization. The author's attention is focused on the uniqueness of the modern situation: never before have innovative technologies had the ability to penetrate so rapidly and deeply into the foundation of modern society, have they become so widespread and accessible to almost all peoples and cultures. At the same time, the undeniable public good and the most (...) serious threats to society that digital reality technologies bring with them are in a very close relationship. This is especially true for artificial intelligence systems. Innovations transform the entire world order, bringing radical changes not only to the material sphere of life, but also to the spiritual and moral state of a person. The research notes that the introduction of information and communication technologies into the life of modern society occurs without reliable support on the results of preliminary experimental research, without taking into account a deep professional and responsible assessment of the social and psychological consequences of their impact on the individual and on society as a whole. As a result, at this stage, society is constantly faced with many negative aspects of the impact of high-tech means. The work examines some of them: a decrease in cognitive and analytical abilities, the devaluation of human labor, the criminalization of cyberspace, the spread of Deepfake technology. Particular attention is paid to the problem associated with the possibility of using information technology as a tool of psychological influence. Information and psychological warfare is implemented on the basis of social networks and artificial intelligence technologies, which provides the enemy with the opportunity to achieve superiority without the use of military force. Information and humanitarian actions in cyberspace, carried out by Western countries in order to destabilize our society, destroy its value foundations, reformat the consciousness, worldview and spiritual and moral qualities of citizens, are becoming increasingly large-scale and aggressive. The work notes that digitalization is gaining momentum, plunging society deeper into new circumstances and requiring decisive action aimed at overcoming the many threats specific to the modern high-tech era. (shrink)

The phenomenon of multi-used stock photography in the news contradicts the photojournalism professional values of truthful and emotional depictions. This reality echoes other false images increasingly appearing in the media, including deepfakes and artificial intelligence. In the present study, a two (stock and staff photo) by two (positive and negative valence) quasi-experiment is conducted. The dependent variables include: 1) credibility; 2) self-reported arousal level; 3) emotional valence perceptions; 4) fixation duration; and 5) fixation count. Participants viewed staff photos as (...) more credible in both positive and negative valences. Negative photos were perceived as slightly less credible. Stock and staff photos were similarly arousing, received similar valence perceptions, and had similar gaze fixations and durations. Overall, participants perceived the genuine emotion portrayed truthfully in photojournalism as opposed to the faux emotion acted out in stock photos. (shrink)

This paper aims to explore an overlooked aspect of deep-fake technology, specifically its application as a protective tool for concealing the identities of targeted individuals or whistleblowers. Since its emergence in 2017, deep-fakes have been intertwined with various sociotechnical imaginaries. Traditionally, deep-fake technology has been portrayed as a potential threat to privacy and a weapon for disseminating false information, evident from its definitions which emphasize its deceptive nature and malicious use. Moreover, the origins of deepfakes, such as the creation (...) and online distribution of altered pornographic material with harmful intentions, further reinforce this perception. As a result of blurring the boundaries between reality and fiction, truth and falsehood, these synthetic media forms not only pose a risk of disinformation and deception but also offer unexplored avenues for creative expression. Thus, this study examines deep-fake technology as a form of ‘digital camouflage’ by analyzing its usage in David France’s documentary film _Welcome to Chechnya_ (2020). The argument presented in this paper suggests that this illustration challenges the dominant narrative surrounding deep-fakes and highlights an ethical and potentially positive application of this technology. (shrink)

Safeguarding GenAI models against threats and aligning them with security requirements is imperative yet challenging. This chapter provides an overview of the security landscape for generative models. It begins by elucidating common vulnerabilities and attack vectors, including adversarial attacks, model inversion, backdoors, data extraction, and algorithmic bias. The practical implications of these threats are discussed, spanning domains like finance, healthcare, and content creation. The narrative then shifts to exploring mitigation strategies and innovative security paradigms. Differential privacy, blockchain-based provenance, quantum-resistant algorithms, (...) and human-guided reinforcement learning are analyzed as potential techniques to harden generative models. Broader ethical concerns surrounding transparency, accountability, deepfakes, and model interpretability are also addressed. The chapter aims to establish a conceptual foundation encompassing both the technical and ethical dimensions of security for generative AI. It highlights open challenges and lays the groundwork for developing robust, trustworthy, and human-centric solutions. The multifaceted perspective spanning vulnerabilities, implications, and solutions is intended to further discourse on securing society’s growing reliance on generative models. Frontier model security is discussed using Anthropic proposed approach. (shrink)