Should artificial intelligences ever be included as co-authors of democratic decisions? According to the conventional view in democratic theory, the answer depends on the relationship between the political unit and the entity that is either affected or subjected to its decisions. The relational conditions for inclusion as stipulated by the all-affected and all-subjected principles determine the spatial extension of democratic inclusion. Thus, AI qualifies for democratic inclusion if and only if AI is either affected or subjected to decisions by the (...) political unit in relevant ways. This paper argues that the conventional view is too simple; that it neglects democratic reasons to recognize only agents and/or moral patients as participants in decision-making. The claim defended is that AAP and ASP implicitly affirm requirements for agency and patiency. In ASP, the entity included must be an agent understood either in terms of legal status, capacity to comply with the law or ability to recognize legitimate authority. In AAP, the entity included must be a patient, understood either in terms of capacity for sentience or consciousness. Thus, the idea here is to explore the potential democratic inclusion of artificial intelligences by an updated account of the relevant conditions of agency and patiency that are implicit in democratic theory. Although conceivable that AI is or will be either affected or subjected in relevant ways to decisions made by political units, it is far less clear that AI will ever be agents or patients in the sense required for democratic inclusion. (shrink)

Deep learning AI systems have proven a wide capacity to take over human-related activities such as car driving, medical diagnosing, or elderly care, often displaying behaviour with unpredictable consequences, including negative ones. This has raised the question whether highly autonomous AI may qualify as morally responsible agents. In this article, we develop a set of four conditions that an entity needs to meet in order to be ascribed moral responsibility, by drawing on Aristotelian ethics and contemporary philosophical research. We encode (...) these conditions and generate a flowchart that we call the Moral Responsibility Test. This test can be used as a tool both to evaluate whether an entity is a morally responsible agent and to inform human moral decision-making over the influencing variables of the context of action. We apply the test to the case of Artificial Moral Advisors and conclude that this form of AI cannot qualify as morally responsible agents. We further discuss the implications for the use of AMAs as moral enhancement and show that using AMAs to offload human responsibility is inadequate. We argue instead that AMAs could morally enhance users if they are interpreted as enablers for moral knowledge of the contextual variables surrounding human moral decision-making, with the implication that such a use might actually enlarge human moral responsibility. (shrink)

Christian List argues that responsibility gaps created by viewing artificial intelligence as intentional agents are problematic enough that regulators should only permit the use of autonomous AI in high-stakes settings where AI is designed to be moral or a liability transfer agreement will fill any gaps. This work challenges List’s proposed condition. A requirement for “moral” AI is too onerous given technical challenges and other ways to check AI quality. Moreover, transfer agreements only plausibly fill responsibility gaps by applying independently (...) justified group responsibility attribution norms such that AI does not raise unique regulatory norms. (shrink)

There is a concern that the widespread deployment of autonomous machines will open up a number of ‘responsibility gaps’ throughout society. Various articulations of such techno-responsibility gaps have been proposed over the years, along with several potential solutions. Most of these solutions focus on ‘plugging’ or ‘dissolving’ the gaps. This paper offers an alternative perspective. It argues that techno-responsibility gaps are, sometimes, to be welcomed and that one of the advantages of autonomous machines is that they enable us to embrace (...) certain kinds of responsibility gap. The argument is based on the idea that human morality is often tragic. We frequently confront situations in which competing moral considerations pull in different directions and it is impossible to perfectly balance these considerations. This heightens the burden of responsibility associated with our choices. We cope with the tragedy of moral choice in different ways. Sometimes we delude ourselves into thinking the choices we make were not tragic ; sometimes we delegate the tragic choice to others ; sometimes we make the choice ourselves and bear the psychological consequences. Each of these strategies has its benefits and costs. One potential advantage of autonomous machines is that they enable a reduced cost form of delegation. However, we only gain the advantage of this reduced cost if we accept that some techno-responsibility gaps are virtuous. (shrink)

In a recent reply to our article, “What is Interpretability?,” Prasetya argues against our position that artificial neural networks are explainable. It is claimed that our indefeasibility thesis—that adding complexity to an explanation of a phenomenon does not make the phenomenon any less explainable—is false. More precisely, Prasetya argues that unificationist explanations are defeasible to increasing complexity, and thus, we may not be able to provide such explanations of highly complex AI models. The reply highlights an important lacuna in our (...) original paper, the omission of the unificationist account of explanation, and affords us the opportunity to respond. Here, we argue that artificial neural networks are explainable in a way that should satisfy unificationists and that interpretability methods present ways in which ML theories can achieve unification. (shrink)

The aim of this article is to highlight and discuss two problems of the biological philosophy of technology. In particular, I will analyse the work of André Leroi-Gourhan and Gilbert Simondon, and I will show that the meaning of the analogy between technical and natural objects that underlies the approach of the biological philosophy of technology remains problematic and the biological approach to technology is very effective for analysing tools and machines, but is not sufficient to describe the so-called information (...) technologies. In the last part of the article, I will argue that, in order to understand information technologies, it is necessary to integrate the biological approach to technology with a grammatological approach. I will try to show that, next to the tool and the machine, there is a third category of technical objects that can be better described using the notion of “writing” proposed by one of the masters of the so-called French Thought, Jacques Derrida. (shrink)

Recent advances in artificial intelligence offer many beneficial prospects. However, concerns have been raised about the opacity of decisions made by these systems, some of which have turned out to be biased in various ways. This article makes a contribution to a growing body of literature on how to make systems for automated decision-making more transparent, explainable, and fair by drawing attention to and further elaborating a distinction first made by Nozick between first-level bias in the application of standards and (...) second-level bias in the choice of standards, as well as a second distinction between discrimination and arbitrariness. Applying the typology developed, a number of illuminating observations are made. First, it is observed that some reported bias in automated decision-making is first-level arbitrariness, which can be alleviated by explainability techniques. However, such techniques have only a limited potential to alleviate first-level discrimination. Second, it is argued that second-level arbitrariness is probably quite common in automated decision-making. In contrast to first-level arbitrariness, however, second-level arbitrariness is not straightforward to detect automatically. Third, the prospects for alleviating arbitrariness are discussed. It is argued that detecting and alleviating second-level arbitrariness is a profound problem because there are many contrasting and sometimes conflicting standards from which to choose, and even when we make intentional efforts to choose standards for good reasons, some second-level arbitrariness remains. (shrink)

In recent years, there has been an intense public debate about whether and, if so, to what extent investments in nuclear energy should be part of strategies to mitigate climate change. Here, we address this question from an ethical perspective, evaluating different strategies of energy system development in terms of three ethical criteria, which will differentially appeal to proponents of different normative ethical frameworks. Starting from a standard analysis of climate change as arising from an intergenerational collective action problem, we (...) evaluate whether contributions from nuclear energy will, on expectation, increase the likelihood of successfully phasing out fossil fuels in time to avert dangerous global warming. For many socio-economic and geographic contexts, our review of the energy system modeling literature suggests the answer to this question is “yes.” We conclude that, from the point of view of climate change mitigation, investments in nuclear energy as part of a broader energy portfolio will be ethically required to minimize the risks of decarbonization failure, and thus the tail risks of catastrophic global warming. Finally, using a sensitivity analysis, we consider which other aspects of nuclear energy deployment, apart from climate change, have the potential to overturn the ultimate ethical verdict on investments in nuclear energy. Out of several potential considerations, we suggest that its potential interplay — whether beneficial or adverse — with the proliferation of nuclear weapons is the most plausible candidate. (shrink)

Algorithmic systems are increasingly used by state agencies to inform decisions about humans. They produce scores on risks of recidivism in criminal justice, indicate the probability for a job seeker to find a job in the labor market, or calculate whether an applicant should get access to a certain university program. In this contribution, we take an interdisciplinary perspective, provide a bird’s eye view of the different key decisions that are to be taken when state actors decide to use an (...) algorithmic system, and illustrate these decisions with empirical examples from case studies. Building on these insights, we discuss the main pitfalls and promises of the use of algorithmic system by the state and focus on four levels: The most basic question whether an algorithmic system should be used at all, the regulation and governance of the system, issues of algorithm design, and, finally, questions related to the implementation of the system on the ground and the human–machine-interaction that comes with it. Based on our assessment of the advantages and challenges that arise at each of these levels, we propose a set of crucial questions to be asked when such intricate matters are addressed. (shrink)

This paper presents an African relational view of social robots’ moral standing which draws on the philosophy of ubuntu. The introduction places the question of moral standing in historical and cultural contexts. Section 2 demonstrates an ubuntu framework by applying it to the fictional case of a social robot named Klara, taken from Ishiguro’s novel, Klara and the Sun. We argue that an ubuntu ethic assigns moral standing to Klara, based on her relational qualities and pro-social virtues. Section 3 introduces (...) a second fictional case, taken from McKeown’s novel, Machines Like Me, in which a social robot named Adam displays intrinsic qualities, such as sentience, rationality, and deductive moral reasoning, yet lacks close social ties to particular people. We argue that Adam is not a person in the African sense; however, he qualifies as a person according to many standard Western views, such as Kantian and utilitarian ethics. Section 4 further elaborates the African relational view by comparing the moral standing of social robots and humans in a forced choice scenario. Section 5 replies to objections. We conclude that an African relational approach captures important insights about the moral standing of social robots that many Western accounts miss and should be better incorporated into global frameworks for designing and deploying social robots. (shrink)

The German Act on Autonomous Driving constitutes the first national framework on level four autonomous vehicles and has received attention from policy makers, AI ethics scholars and legal experts in autonomous driving. Owing to Germany’s role as a global hub for car manufacturing, the following paper sheds light on the act’s position within the ethical discourse and how it reconfigures the balance between legislation and ethical frameworks. Specifically, in this paper, we highlight areas that need to be more worked out (...) in the future either through ethical conventions, corporate measures or legal measures and examine how the law can be incorporated into the existing discourse on the regulation of technologies. Based on this examination, we derive implications for future discourse and elaborate on companies’ responsibilities in developing autonomous driving technologies in an ethical sense. (shrink)

In the spirit of Slavoj Žižek’s book, Hegel in a Wired Brain, this article asks how the questions central to Hans-Georg Gadamer’s philosophical hermeneutics are changed and complicated by the possibility of brain-to-brain communication and the datafication of thought made potential through brain-computer interfaces. By taking a phenomenological approach to understanding the nature of communication through a technology that does not require language for the transmission of ideas, this article explores how BCI communication confronts the ontological character of interpretation as (...) presented by Gadamer while also juxtaposing how the insights of Gadamer and Heidegger concerning temporality problematize materialist foundations of BCI communication. In the final analysis, it is argued that thought only becomes meaningful in accord with the temporality of Dasein and that hermeneutics remains central in BCI communication because the material replication of thought does not overcome the particular temporalities of historically effected consciousnesses. (shrink)

Search engines are important contemporary sources of information and contribute to shaping our beliefs about the world. Each time they are consulted, various algorithms filter and order content to show us relevant results for the inputted search query. Because these search engines are frequently and widely consulted, it is necessary to have a clear understanding of the distinctively epistemic role that these algorithms play in the background of our online experiences. To aid in such understanding, this paper argues that search (...) engine algorithms are providers of “bent testimony”—that, within certain contexts of interactions, users act as if these algorithms provide us with testimony—and acquire or alter beliefs on that basis. Specifically, we treat search engine algorithms as if they were asserting as true the content ordered at the top of a search results page—which has interesting parallels with how we might treat an ordinary testifier. As such, existing discussions in the philosophy of testimony can help us better understand and, in turn, improve our interactions with search engines. By explicating the mechanisms by which we come to accept this “bent testimony,” our paper discusses methods to help us control our epistemic reliance on search engine algorithms and clarifies the normative expectations one ought to place on the search engines that deploy these algorithms. (shrink)

Some artificial intelligence systems can display algorithmic bias, i.e. they may produce outputs that unfairly discriminate against people based on their social identity. Much research on this topic focuses on algorithmic bias that disadvantages people based on their gender or racial identity. The related ethical problems are significant and well known. Algorithmic bias against other aspects of people’s social identity, for instance, their political orientation, remains largely unexplored. This paper argues that algorithmic bias against people’s political orientation can arise in (...) some of the same ways in which algorithmic gender and racial biases emerge. However, it differs importantly from them because there are strong social norms against gender and racial biases. This does not hold to the same extent for political biases. Political biases can thus more powerfully influence people, which increases the chances that these biases become embedded in algorithms and makes algorithmic political biases harder to detect and eradicate than gender and racial biases even though they all can produce similar harm. Since some algorithms can now also easily identify people’s political orientations against their will, these problems are exacerbated. Algorithmic political bias thus raises substantial and distinctive risks that the AI community should be aware of and examine. (shrink)

In the last decades, supervised machine learning has seen the widespread growth of highly complex, non-interpretable models, of which deep neural networks are the most typical representative. Due to their complexity, these models have showed an outstanding performance in a series of tasks, as in image recognition and machine translation. Recently, though, there has been an important discussion over whether those non-interpretable models are able to provide any sort of understanding whatsoever. For some scholars, only interpretable models can provide understanding. (...) More popular, however, is the idea that understanding can come from a careful analysis of the dataset or from the model’s theoretical basis. In this paper, I wish to examine the possible forms of obtaining understanding of such non-interpretable models. Two main strategies for providing understanding are analyzed. The first involves understanding without interpretability, either through external evidence for the model’s inner functioning or through analyzing the data. The second is based on the artificial production of interpretable structures, through three main forms: post hoc models, hybrid models, and quasi-interpretable structures. Finally, I consider some of the conceptual difficulties in the attempt to create explanations for these models, and their implications for understanding. (shrink)

In a recent article, Erasmus, Brunet, and Fisher (2021) argue that Artificial Neural Networks (ANNs) are explainable. They survey four influential accounts of explanation: the Deductive-Nomological model, the Inductive-Statistical model, the Causal-Mechanical model, and the New-Mechanist model. They argue that, on each of these accounts, the features that make something an explanation is invariant with regard to the complexity of the explanans and the explanandum. Therefore, they conclude, the complexity of ANNs (and other Machine Learning models) does not make them (...) less explainable. In this reply, it is argued that Erasmus et al. left out one influential account of explanation from their discussion: the Unificationist model. It is argued that, on the Unificationist model, the features that makes something an explanation is sensitive to complexity. Therefore, on the Unificationist model, ANNs (and other Machine Learning models) are not explainable. It is emphasized that Erasmus et al.’s general strategy is correct. The literature on explainable Artificial Intelligence can benefit by drawing from philosophical accounts of explanation. However, philosophical accounts of explanation do not settle the problem of whether ANNs are explainable because they do not unanimously declare that explanation is invariant with regard to complexity. (shrink)

Jacques Lafitte occupies an odd place in the philosophy of technology. He was a French engineer who made a significant and conceptually innovative contribution to this field, yet his influence has been elusive and largely ignored until relatively recently. Many of Lafitte’s ideas find echoes in the work of later philosophers, yet, notably in the case of Simondon, apparently without any direct line of influence. Lafitte placed the machine at the centre of his thinking about technology and articulated various layers (...) of analysis around it; for example, he considered machines in the broader context of an artificial world or “mechanosphere”, which encompassed certain aspects of philosophical anthropology. In this work we seek to reconstruct Lafitte’s ideas and briefly trace some of their later impact. We identify three dimensions in Lafitte’s analysis: epistemological, ontological and anthropological. We argue that the most remarkable fact about Lafitte’s thought is the way it inaugurates, and anticipates, the approach of later currents, not just in the “French tradition”, who also made an effort to integrate machine theory into broader philosophical, anthropological and political aspects, in terms that echo Lafitte’s. In particular, we will focus on Gilbert Simondon and cybernetics. (shrink)

The term exaptation, describing the phenomenon that an existing trait or tool proves to be of new adaptive value in a new context, is flourishing in recent literature from cultural evolution and cognitive archaeology. Yet there also exists an older literature from the nineteenth and twentieth centuries which studied more or less systematically the phenomenon of “change of function” in culture and tool use. Michel Foucault and Ludwig Noiré, who devoted themselves to the history of social institutions and material tools, (...) respectively, occupy an important place among them. This article offers a brief overview of this literature and attempts to show that it provided ideas that remain relevant to current approaches to cognitive archaeology, in particular regarding attempts to understand the impact of technological evolution on the human mind. (shrink)

A recurrent theme of human–machine interaction is how interaction is defined and what kind of information is relevant for successful communication. In accordance with the theoretical strategies of social cognition and technical philosophy, we propose a pragmatic interactive approach, to understand the concept of information in human–machine interaction. We start with the investigation of interpersonal interaction and human–machine interaction by concerning triangulation as guiding principle. To illustrate human–machine interaction, we will mainly focus on the interactive relationship between human cognitive skills (...) and their technological environments. In triadic interaction, the concept of information cannot only be understood as a syntactic transformation as in the dyadic relationship. We argue that information as pragmatic action patterns can be understood as physically embodied units that is not purely formal but generated in interactive processes and stabilized in use. By exploring how the concept of affordance is applied in psychology, anthropology and human-centered design, we provide a notion of pragmatic information, focusing on users in the development and use of machines or software systems. The triadic interaction of end user, development team, and product leads to a successful human–machine interaction. This theoretical framework enables us to understand how the new socio-technological environments expand our scope of action and how we form, interpret, and learn to deal with patterns of action among ourselves and with machines. (shrink)

It is widely acknowledged that high-level AI principles are difficult to translate into practices via explicit rules and design guidelines. Consequently, many AI research and development groups that claim to adopt ethics principles have been accused of unwarranted “ethics washing”. Accordingly, there remains a question as to if and how high-level principles should be expected to influence the development of safe and beneficial AI. In this short commentary I discuss two roles high-level principles might play in AI ethics and governance. (...) The first and most often discussed “start-point” function quickly succumbs to the complaints outlined above. I suggest, however, that a second “cultural influence” function is where the primary value of high-level principles lies. (shrink)

This investigation provides an in-depth exploration of the dialectics of action and technology in the works of French philosopher Jean-Paul Sartre, both in terms of the concrete use contexts of technological artifacts and the entanglement between individual agents and their sociotechnical surroundings. Furthermore, it briefly outlines some potentials of Sartre’s thoughts for debates in contemporary philosophy of technology. Throughout his works, Sartre approaches human action from different yet dialectically interrelated perspectives that are always accompanied by and developed in relation to (...) reflections about technology. Against the background of a complementary conception of human action that is derived from Sartre’s major works, the implementation of matter in the course of action primarily represents an instrumentalization. Things are thus always disclosed as implement things due to the practical character of human existence. Although things do not prescribe action, the material characteristics and properties of these things render them more useful for attaining some and more adverse for attaining other ends. Despite the ontological freedom of human beings, their position in societal forms of organization, to which Sartre refers to as practical ensembles, delimits their choice of means and necessitates them to satisfy their needs and desires with the limited means available. In this way, la force des choses arises, not as a result of the characteristics of technology but as an outcome of sociality and politics. (shrink)

Often associated with themes in political philosophy and aesthetics, the work of Jean-François Lyotard is most known for his infamous definition of the postmodern in his best-known book, La condition postmoderne, as incredulity towards metanarratives. The claim of this article is that this famous claim of Lyotard is actually embedded in a philosophy of technology, one that is, moreover, still relevant for understanding present technoscience. The first part of the article therefore sketches Lyotard’s philosophy of technology, mainly by correcting three (...) common misconceptions: that La condition postmoderne would only be about metanarratives, whereas in fact, it is mainly about what replaces them, namely performativity; that performativity would be shorthand for capitalism, whereas in reality, capitalism is the latest instance of a longer history of performativity; and that Lyotard’s reflections on science and technology would be restricted to this book alone, whereas in reality, a well-articulated philosophy of technology, centered around the concept of technoscience, is found in his later work. The second part of the article then aims to highlight the contemporary relevance of this philosophy of technoscience through a brief examination of two contemporary technosciences: synthetic biology and data science. (shrink)

Social media technologies are routinely identified as a strong and pervasive threat to digital well-being. Extended screen time sessions, chronic distractions via notifications, and fragmented workflows have all been blamed on how these technologies ruthlessly undermine our ability to exercise quintessential human faculties. One reason SMTs can do this is because they powerfully affect our emotions. Nevertheless, how social media technology affects our emotional life and how these emotions relate to our digital well-being remain unexplored. Remedying this is important because (...) ethical insights into and open the possibility of designing for social media technologies in ways that actively reinforce our digital well-being. In this article, we examine the way social media technologies facilitate online emotions because of emotional affordances. This has important implications for evaluating the ethical implications of today’s social media platforms, as well as for how we design future ones. (shrink)

We propose a pragmatist account of value change that helps to understand how and why values sometimes change due to technological developments. Inspired by John Dewey’s writings on value, we propose to understand values as evaluative devices that carry over from earlier experiences and that are to some extent shared in society. We discuss the various functions that values fulfil in moral inquiry and propose a conceptual framework that helps to understand value change as the interaction between three manifestations of (...) value distinguished by Dewey, i.e., “immediate value,” “values as the result of inquiry” and “generalized values.” We show how this framework helps to distinguish three types of value change: value dynamism, value adaptation, and value emergence, and we illustrate these with examples from the domain of technology. We argue that our account helps to better understand how technology may induce value change, namely through the creation of what Dewey calls indeterminate situations, and we show how our account can integrate several insights on moral change offered by other authors. (shrink)

Deleuze and Guattari’s Thousand Plateaus includes some useful concepts to understand technologies and their relations to humans as individuals and as a society. This article provides an introduction to their notions of machine and becoming and places them in the context of technological use in general, with a special focus on the cellphone. The concept of machine exceeds the technological context, yet it can be still relevant to technologies, especially digital ones. The concept of becoming assists in better understanding co-shaping (...) processes in which a technology and its users change in tandem. Becoming is analyzed as a set of five characteristics: [1] transduction, a change process in both the user and the technology; [2] rhizome, no starting or end point; [3] molecularity, small movement or change that can create a big difference; [4] partial simulation, creating a non-identical copy; and [5] anti-memory, forgetting the past. Based on this analysis, the concept of becoming-mobile is introduced as a new way of understanding the interrelations between humans and their cellphones. Becoming-mobile can be further developed either with Deleuze and Guattari’s own concepts such as nomadicism or with “external” concepts such as postphenomenology’s embodiment and new mobility studies’ virtual mobility. Machine, becoming, and becoming-mobile address some basic questions in philosophy of technology, thereby enabling us to refer to Deleuze and Guattari as philosophers of technology. (shrink)

The attention economy — the market where consumers’ attention is exchanged for goods and services — poses a variety of threats to individuals’ autonomy, which, at minimum, involves the ability to set and pursue ends for oneself. It has been argued that the threat wireless mobile devices pose to autonomy gives rise to a duty to oneself to be a digital minimalist, one whose interactions with digital technologies are intentional such that they do not conflict with their ends. In this (...) paper, we argue that there is a corresponding duty to others to be an attention ecologist, one who promotes digital minimalism in others. Although the moral reasons for being an attention ecologist are similar to those that motivate the duty to oneself, the arguments diverge in important ways. We explore the application of this duty in various domains where we have special obligations to promote autonomy in virtue of the different roles we play in the lives of others, such as parents and teachers. We also discuss the consequences of our arguments for employers, software developers, and policy makers. (shrink)

We argue that explainable artificial intelligence (XAI), specifically reason-giving XAI, often constitutes the most suitable way of ensuring that someone can properly be held responsible for decisions that are based on the outputs of artificial intelligent (AI) systems. We first show that, to close moral responsibility gaps (Matthias 2004), often a human in the loop is needed who is directly responsible for particular AI-supported decisions. Second, we appeal to the epistemic condition on moral responsibility to argue that, in order to (...) be responsible for her decision, the human in the loop has to have an explanation available of the system’s recommendation. Reason explanations are especially well-suited to this end and we examine whether – and how – it might be possible to make such explanations fit with AI systems. We support our claims by focusing on a case of disagreement between human in the loop and AI system. (shrink)

This commentary argues that, in discussing the racial and cultural identities of cinematic representations of humanoid AI robots, nuances and differentiations are beneficial. It suggests that the essay on which the present text comments does not sufficiently acknowledge the range of identities found in AI films, in particular in Alex Garland's Ex Machina.

This paper argues that machine learning and epidemiology are on collision course over causation. The discipline of epidemiology lays great emphasis on causation, while ML research does not. Some epidemiologists have proposed imposing what amounts to a causal constraint on ML in epidemiology, requiring it either to engage in causal inference or restrict itself to mere projection. We whittle down the issues to the question of whether causal knowledge is necessary for underwriting predictions about the outcomes of public health interventions. (...) While there is great plausibility to the idea that it is, conviction that something is impossible does not by itself motivate a constraint to forbid trying. We disambiguate the possible motivations for such a constraint into definitional, metaphysical, epistemological, and pragmatic considerations and argue that “Proceed with caution” is the outcome of each. We then argue that there are positive reasons to proceed, albeit cautiously. Causal inference enforces existing classification schema prior to the testing of associational claims, but associations and classification schema are more plausibly discovered in a back-and-forth process of gaining reflective equilibrium. ML instantiates this kind of process, we argue, and thus offers the welcome prospect of uncovering meaningful new concepts in epidemiology and public health—provided it is not causally constrained. (shrink)

The aim of this article is to consider biobanks through the conceptual tools of French Thought and twentieth-century French philosophy of technology. Firstly, two pairs of authors and their respective conceptions of the relationship between technics and memory are considered: on the one hand, Jacques Derrida and Bernard Stiegler, who thought of memory and technics on the model of writing; on the other hand, Henri Bergson and André Leroi-Gourhan, who thought of memory as linked to biological life, and of technics (...) as an exteriorization of life. On the basis of this discussion, a philosophical analysis of biobanks is then provided, understanding them as exteriorized memories of life, and some conceptual problems raised by biobanks are addressed: the question of exteriorization and its relation with the organic and the inorganic matter; the relation between the living and the environment; the mode of existence of biological data; and the distinction between natural and artificial memory. (shrink)

We begin by introducing our readers to the Extended Mind Thesis and briefly discuss a series of arguments in its favour. We continue by showing of such a theory can be resisted and go on to demonstrate that a more conservative account of cognition can be developed. We acknowledge a stalemate between these two different accounts of cognition and notice a couple of issues that we argue have prevented further progress in the field. To overcome the stalemate, we propose to (...) focus on the ethical implications of these theories. We link work conducted on the Extended Mind Thesis with contemporary transhumanist research and claim that extended may be ethically preferred over embedded because it is a more progressive and inclusive theory. (shrink)

In this paper, we will re-elaborate the notions of filter bubble and of echo chamber by considering human cognitive systems’ limitations in everyday interactions and how they experience digital technologies. Researchers who applied the concept of filter bubble and echo chambers in empirical investigations see them as forms of algorithmically-caused systems that seclude the users of digital technologies from viewpoints and opinions that oppose theirs. However, a significant majority of empirical research has shown that users do find and interact with (...) opposing views. Furthermore, we argue that the notion of filter bubble overestimates the social impact of digital technologies in explaining social and political developments without considering the not-only-technological circumstances of online behavior and interaction. This provides us with motivation to reconsider this notion’s validity and re-elaborate it in light of existing epistemological theories that deal with the discomfort people experience when dealing with what they do not know. Therefore, we will survey a series of philosophical reflections regarding the epistemic limitations of human cognitive systems. In particular, we will discuss how knowledge and mere belief are phenomenologically indistinguishable and how people’s experience of having their beliefs challenged is cause of epistemic discomfort. We will then go on to argue, in contrast with Pariser’s assumptions, that digital media users might tend to conform to their held viewpoints because of the “immediate” way they experience opposing viewpoints. Since online people experience others and their viewpoints as material features of digital environments, we maintain that this modality of confronting oneself with contrasting opinions prompts users to reinforce their preexisting beliefs and attitudes. (shrink)

The initial successes in recent years in harnessing machine learning technologies to improve medical practice and benefit patients have attracted attention in a wide range of healthcare fields. Particularly, it should be achieved by providing automated decision recommendations to the treating clinician. Some hopes placed in such ML-based systems for healthcare, however, seem to be unwarranted, at least partially because of their inherent lack of transparency, although their results seem convincing in accuracy and reliability. Skepticism arises when the physician as (...) the agent responsible for the implementation of diagnosis, therapy, and care is unable to access the generation of findings and recommendations. There is widespread agreement that, generally, a complete traceability is preferable to opaque recommendations; however, there are differences about addressing ML-based systems whose functioning seems to remain opaque to some degree—even if so-called explicable or interpretable systems gain increasing amounts of interest. This essay approaches the epistemic foundations of ML-generated information specifically and medical knowledge generally to advocate differentiations of decision-making situations in clinical contexts regarding their necessary depth of insight into the process of information generation. Empirically accurate or reliable outcomes are sufficient for some decision situations in healthcare, whereas other clinical decisions require extensive insight into ML-generated outcomes because of their inherently normative implications. (shrink)

The United Nations confirmed that privacy remains a human right in the digital age, but our daily digital experiences and seemingly ever-increasing amounts of data suggest that privacy is a mundane, distributed and technologically mediated concept. This article explores privacy by mapping out different legal and conceptual approaches to privacy protection in the context of datafication. It provides an essential starting point to explore the entwinement of technological, ethical and regulatory dynamics. It clarifies why each of the presented approaches emphasises (...) particular aspects and analyses the tensions that arise. The resulting overview provides insight into the main strengths and limitations of the different approaches arising from specific traditions. This analytic overview therefore serves as a key resource to analyse the usefulness of the approaches in the context of the increasing datafication of both private and public spheres.Specifically, we contrast the approach focusing on data subjects whose data are being ‘protected’ with others, including Fair Information Practice Principles, the German right to ‘informational self-determination’, and the South American ‘habeas data’ doctrine. We also present and contrast emerging approaches to privacy and discuss their intersection with datafication. In conclusion, we put forth that rather than aiming for one single solution that works worldwide and across all situations, it is essential to identify synergies and stumbling blocks between the various regulatory settings and newly emerging approaches. (shrink)

We explore aversion to the use of algorithms in moral decision-making. So far, this aversion has been explained mainly by the fear of opaque decisions that are potentially biased. Using incentivized experiments, we study which role the desire for human discretion in moral decision-making plays. This seems justified in light of evidence suggesting that people might not doubt the quality of algorithmic decisions, but still reject them. In our first study, we found that people prefer humans with decision-making discretion to (...) algorithms that rigidly apply exogenously given human-created fairness principles to specific cases. In the second study, we found that people do not prefer humans to algorithms because they appreciate flesh-and-blood decision-makers per se, but because they appreciate humans’ freedom to transcend fairness principles at will. Our results contribute to a deeper understanding of algorithm aversion. They indicate that emphasizing the transparency of algorithms that clearly follow fairness principles might not be the only element for fostering societal algorithm acceptance and suggest reconsidering certain features of the decision-making process. (shrink)

The recent decades have seen established liberal democracies expand their surveillance capacities on a massive scale. This article explores what is problematic about government surveillance by democracies. It proceeds by distinguishing three potential sources of concern: the concern that governments diminish citizens’ privacy by collecting their data, the concern that they diminish their privacy by accessing their data, and the concern that the collected data may be used for objectionable purposes. Discussing the meaning and value of privacy, the article argues (...) that only the latter two constitute compelling independent concerns. It then focuses particularly on the third concern, exploring the risk of government surveillance being used to enforce illegitimate laws. It discusses three legitimacy-related reasons why we should be worried about the expansion of surveillance capacities in established democracies: Even established democracies might decay. There is a risk that surveillance capacities that are used for democratically legitimated purposes today will be used for poorly legitimated purposes in the future. Surveillance may be used to enforce laws that lack legitimacy due to the disproportionate punishment attached to their violation. The democratic procedures in established democracies fail to conform to the requirements formulated by mainstream theories of democratic legitimacy. Surveillance is thus used to enforce laws whose legitimacy is in doubt. (shrink)

Departing from the claim that AI needs to be trustworthy, we find that ethical advice from an AI-powered algorithm is trusted even when its users know nothing about its training data and when they learn information about it that warrants distrust. We conducted online experiments where the subjects took the role of decision-makers who received advice from an algorithm on how to deal with an ethical dilemma. We manipulated the information about the algorithm and studied its influence. Our findings suggest (...) that AI is overtrusted rather than distrusted. We suggest digital literacy as a potential remedy to ensure the responsible use of AI. (shrink)

Bernard Stiegler was the first distinguished critic to have recognized that Derrida’s deconstruction is, concurrently, a philosophy of techniques. Stiegler’s perceptive thesis is widely endorsed by Derrida's recent commentators. It is possible to locate in Derrida’s earliest writings a reflection on the genesis of the “technical supplement,” which allows us to situate Derridan philosophy in a specific tradition concerned with the philosophy of techniques. By thinking of Life—and not Man—as a producer of “technical objects,” Derrida joins a well-established philosophical lineage, (...) subsuming Bergson’s “vital impulse”’ the “general organology” of Canguilhem, Simondon and Stiegler; and Leroi-Gourhan’s “technical life.” In this article, I attend to the genesis of the technical object in Derrida’s philosophy, in order to show how and why it is possible to rethink it within the horizon of “vitalist” philosophies of techniques. (shrink)

In this paper, in the first place, I aim to enquire into Bernard Stiegler’s critical appropriation of his mentor Jacques Derrida’s notion of différance, emphasizing how Stiegler’s philosophy of technology stems from an original interpretation of the main tenets of deconstruction. From this perspective, I will investigate Stiegler’s definition of technology as tertiary retention, i.e., exosomatized, artificial memory interrelating with biological memory, testing its hermeneutic strengths as well as possible weaknesses. In the second place, I aim to contrast Stiegler’s understanding (...) of technology with the concept of multistability brought forward by postphenomenological philosophies of technology such as those elaborated by Don Ihde and Peter-Paul Verbeek. This investigation will enable me to submit that Stiegler’s approach represents a peculiar and innovative way to conceive of technology. On the one hand, indeed, it does not seem to fall prey to the criticisms raised by postphenomenology against traditional philosophies of technology such as Martin Heidegger’s or Jacques Ellul’s, deemed to be overly deterministic, abstract and pessimistic in their understanding of technology. On the other, it retains important methodological precautions from deconstruction, thereby pointing at some possible blind spots of postphenomenology, especially concerning the vexed question of the empirical-transcendental divide, which Stiegler aims to develop beyond both Derrida’s and postphenomenology’s stances. (shrink)

This paper argues that the AI ethics has generally neglected the issues related to the science communication of AI. In particular, the article focuses on visual communication about AI and, more specifically, on the use of certain stock images in science communication about AI — in particular, those characterized by an excessive use of blue color and recurrent subjects, such as androgyne faces, half-flesh and half-circuit brains, and variations on Michelangelo’s The Creation of Adam. In the first section, the author (...) refers to a “referentialist” ethics of science communication for an ethical assessment of these images. From this perspective, these images are unethical. While the ethics of science communication generally promotes virtues like modesty and humility, similar images are arrogant and overconfident. In the second section, the author uses French philosopher Jacques Rancière’s concepts of “distribution of the sensible,” “disagreement,” and “pensive image.” Rancière’s thought paves the way to a deeper critique of these images of AI. The problem with similar images is not their lack of reference to the “things themselves.” It rather lies in the way they stifle any possible forms of disagreement about AI. However, the author argues that stock images and other popular images of AI are not a problem per se, and they can also be a resource. This depends on the real possibility for these images to support forms of pensiveness. In the conclusion, the question is asked whether the kind of ethics or politics of AI images proposed in this article can be applied to AI ethics tout court. (shrink)

Augmented reality (AR) technologies function to ‘augment’ normal perception by superimposing virtual objects onto an agent’s visual field. The philosophy of augmented reality is a small but growing subfield within the philosophy of technology. Existing work in this subfield includes research on the phenomenology of augmented experiences, the metaphysics of virtual objects, and different ethical issues associated with AR systems, including (but not limited to) issues of privacy, property rights, ownership, trust, and informed consent. This paper addresses some epistemological issues (...) posed by AR systems. I focus on a near-future version of AR technology called the Real-World Web, which promises to radically transform the nature of our relationship to digital information by mixing the virtual with the physical. I argue that the Real-World Web (RWW) threatens to exacerbate three existing epistemic problems in the digital age: the problem of digital distraction, the problem of digital deception, and the problem of digital divergence. The RWW is poised to present new versions of these problems in the form of what I call the augmented attention economy, augmented skepticism, and the problem of other augmented minds. The paper draws on a range of empirical research on AR and offers a phenomenological analysis of virtual objects as perceptual affordances to help ground and guide the speculative nature of the discussion. It also considers a few policy-based and designed-based proposals to mitigate the epistemic threats posed by AR technology. (shrink)

A discussion concerning whether to conceive Artificial Intelligence systems as responsible moral entities, also known as “artificial moral agents”, has been going on for some time. In this regard, we argue that the notion of “moral agency” is to be attributed only to humans based on their autonomy and sentience, which AI systems lack. We analyze human responsibility in the presence of AI systems in terms of meaningful control and due diligence and argue against fully automated systems in medicine. With (...) this perspective in mind, we focus on the use of AI-based diagnostic systems and shed light on the complex networks of persons, organizations and artifacts that come to be when AI systems are designed, developed, and used in medicine. We then discuss relational criteria of judgment in support of the attribution of responsibility to humans when adverse events are caused or induced by errors in AI systems. (shrink)

The ethics of artificial intelligence is an upcoming field of research that deals with the ethical assessment of emerging AI applications and addresses the new kinds of moral questions that the advent of AI raises. The argument presented in this article is that, even though there exist different approaches and subfields within the ethics of AI, the field resembles a critical theory. Just like a critical theory, the ethics of AI aims to diagnose as well as change society and is (...) fundamentally concerned with human emancipation and empowerment. This is shown through a power analysis that defines the most commonly addressed ethical principles and topics within the field of AI ethics as either to do with relational power or with dispositional power. Moreover, it is concluded that recognizing AI ethics as a critical theory and borrowing insights from the tradition of critical theory can help the field forward. (shrink)

Objects appear to causally interact with one another in virtual worlds, such as video games, virtual reality, and training simulations. Is this causation real or is it illusory? In this paper I argue that virtual causation is as real as physical causation. I achieve this in two steps: firstly, I show how virtual causation has all the important hallmarks of relations that are causal, as opposed to merely accidental, and secondly, I show how virtual causation is genuine according to one (...) influential metaphysical theory of causation: the mechanistic approach. (shrink)