Apocalyptic AI, the hope that we might one day upload our minds into machines and live forever in cyberspace, has become commonplace. This view now affects robotics and AI funding, play in online games, and philosophical and theological conversations about morality and human dignity.

Objective: Individually, vision and hearing impairments have been linked to higher levels of anxiety and depression. We investigated the effect of dual sensory impairment in a large representative sample of Spanish adults. Methods: Data from a total of 23,089 adults from the Spanish National Health Survey 2017 were analyzed. Self-reported difficulty of seeing and hearing, and depression and chronic anxiety were analyzed. Multivariable logistic regression was assessed for difficulty with vision alone, hearing alone and with difficulty with both, (...) adjusting for gender, age, marital status, living as a couple, education, smoking, alcohol consumption, BMI, physical activity, use of glasses/contact lenses, and hearing aid. Results: Visual difficulty, hearing difficulty, and dual difficulties were all associated with significantly higher odds for depression and for chronic anxiety. Dual sensory difficulty was associated with higher odds ratios for depression and anxiety when compared to either impairment alone. Conclusion: Dual sensory difficulty is associated with significantly higher odds of anxiety and depression when compared to either vision or hearing difficulty alone. Appropriate interventions are needed to address any reversible causes of vision and hearing as well as anxiety and depression in people in these specific groups. (shrink)

On the assumption that phenomenal consciousness is real, and ruling out Cartesian isolation from the non-mental world, we have two choices for its introduction: either it comes about in the course of the development of the non-conscious realm or it was there from the beginning. The latter comprises versions of panpsychism, a recently trending view in some quarters. In their view the former are broadly taken to be versions of emergentism, embracing even non-eliminatiivist materialisms. After producing what seem to me (...) to be powerful objections to panpsychism, I defend emergentism against pansychist attacks on it. As I explain, my version is also dualist. Finally, with respect to both outlooks I briefly review the prospects of a rapidly advancing AI for expanding the current population of natural mental subjects. (shrink)

This paper introduces the Spider Vision Framework, a biomimetic approach to AI governance inspired by the dual visual systems of spiders. By integrating focused oversight (technical detail) with systemic awareness (societal context) and grounding both in virtue ethics—particularly prudence, justice, and adaptability—the framework addresses immediate technical risks while accounting for long-term societal implications. Comparative analyses with consequentialist and deontological models underscore virtue ethics’ emphasis on moral character, and the paper proposes pilot studies for empirical validation in healthcare AI and (...) autonomous vehicles. This integrated approach aims to foster an adaptive, ethically robust governance model, balancing precision and breadth to better align AI with the common good. Initial findings suggest a significant improvement in ethical compliance and stakeholder engagement when dual-focus oversight is integrated into existing AI systems. The framework recommends targeted pilot implementations across diverse regulatory environments to ensure robust, context-specific outcomes. (shrink)

Looking into the future is always a risky endeavour, but one way to anticipate the possible future shape of AI-driven societies is to examine the visionary works of some sci-fi writers. Not all sci-fi works have such visionary quality, of course, but some of Stanisław Lem’s works certainly do. We refer here to Lem’s works that explore the frontiers of science and technology and those that describe imaginary societies of robots. We therefore examine Lem’s prose, with a focus on the (...) Cyberiad stories, to see what challenges our future technological societies may face when they entrust their lives to AI technology. For example, what questions should we ask, and what questions do we forget to ask, when developing AI systems and allowing these systems to control our lives. The technologically honed minds of our current technocrats are perhaps too limited to guide us into this future, because AI-based technology is relatively unchartered territory, as any new, complex technology is by nature. Lem’s visions of future societies oriented around AI and robotics portray AI technology in a deeper and more nuanced way than the current technological visions offered by our leading technological prophets. Based on Lem’s visions, what is to come may not turn out to be an AI-driven nirvana. (shrink)

Machine vision is one of the main applications of artificial intelligence. In China, the machine vision industry makes up more than a third of the national AI market, and technologies like face recognition, object tracking and automated driving play a central role in surveillance systems and social governance projects relying on the large-scale collection and processing of sensor data. Like other novel articulations of technology and society, machine vision is defined, developed and explained by different actors through (...) the work of imagination. In this article, we draw on the concept of sociotechnical imaginaries to understand how Chinese companies represent machine vision. Through a qualitative multimodal analysis of the corporate websites of leading industry players, we identify a cohesive sociotechnical imaginary of machine vision, and explain how four distinct visual registers contribute to its articulation. These four registers, which we call computational abstraction, human–machine coordination, smooth everyday, and dashboard realism, allow Chinese tech companies to articulate their global ambitions and competitiveness through narrow and opaque representations of machine vision technologies. (shrink)

To the extent of contesting visions of AI technology, both utopian and dystopian views of AI and humanoid technology resonate particular assumption of human subjectivity originated from modern enlightenment philosophy (i.e., Descartes, Kant). Accordingly, the series of transhumanism including Kurzweil, Moravec and Harrari envision evolution of human capability through the advancement of AI technology while assuming human subjectivities based on Cartesian dualism. As transhumanism is critically viewed by diverse perspectives including from philosophical, technological, cultural and religious stand points, post-humanism address (...) issues of human subjectivities and human/environmental relations with regard to evolution of AI technology. This article delves into media representation of futurist vision of AI technology in different regions in the world. Em(dis)bodiment of AI and humanoids in Hollywood and Asian SF (science fiction) films, for example, resonates philosophical and cultural debates between transhumanism and posthumanism. This article addresses theoretical discussions in relation to the development of AI technology and design of humanoid by comparing liberal views of human subjectivities (i.e., Descartes and Kant) with critical views against it (i.e., Heidegger and Foucault). The issues of cultural diversity in relation to the development of AI technology is particularly highlighted by introducing theories of non-Western scholarship and examining distinctive media representation of AI in the East and the West. (shrink)

Computer vision is a subfeld of artifcial intelligence, aimed at making computers see. Computer vision tools enable a system or device to automatically analyze, interpret, and respond to images and videos. Computer vision tasks range from object detection and tracking, to the recognition of people’s faces and emotional states. While the ethics of AI in general has received signifcant attention, and the ethics of facial recognition (a computer vision application) too, little of the AI ethics literature (...) focuses specifcally on the ethics of computer vision. In this chapter, I create an overview of ethical, social, and political issues related to computer vision, using a critical approach. This means that I identify issues in terms of power and evaluate them in function of their impact on the value of autonomy and the normative goal of emancipatory progress. The aim of this chapter is frst and foremost to ofer an overview of potential normative implications of computer vision. Additionally, the chapter functions as an example for the use of a critical approach to AI ethics. (shrink)

In 2017, Tom Gruber held a TED talk, in which he presented a vision of improving and enhancing humanity with AI technology. Specifically, Gruber suggested that an AI-improved personal memory (APM) would benefit people by improving their “mental gain”, making us more creative, improving our “social grace”, enabling us to do “science on our own data about what makes us feel good and stay healthy”, and, for people suffering from dementia, it “could make a difference between a life of (...) isolation and a life of dignity and connection”. -/- In this paper, Gruber’s idea will be critically assessed. Firstly, it will be argued that most of his pro-arguments for the APM are questionable. Secondly, the APM will also be criticized for other reasons, including the risks and affects to the users’ and other’s privacy and the users’ autonomy. (shrink)

By looking at the politics of classification within machine learning systems, this article demonstrates why the automated interpretation of images is an inherently social and political project. We begin by asking what work images do in computer vision systems, and what is meant by the claim that computers can “recognize” an image? Next, we look at the method for introducing images into computer systems and look at how taxonomies order the foundational concepts that will determine how a system interprets (...) the world. Then we turn to the question of labeling: how humans tell computers which words will relate to a given image. What is at stake in the way AI systems use these labels to classify humans, including by race, gender, emotions, ability, sexuality, and personality? Finally, we turn to the purposes that computer vision is meant to serve in our society—the judgments, choices, and consequences of providing computers with these capacities. Methodologically, we call this an archeology of datasets: studying the material layers of training images and labels, cataloguing the principles and values by which taxonomies are constructed, and analyzing how these taxonomies create the parameters of intelligibility for an AI system. By doing this, we can critically engage with the underlying politics and values of a system, and analyze which normative patterns of life are assumed, supported, and reproduced. (shrink)

Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the (...) field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust--in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better. (shrink)

The Chinese government and technology companies assume a proactive stance towards digital technologies and AI and their roles in users’—and more generally, people’s—lives. This vision of ‘Tech for Good’, i.e., the development of good digital technologies and AI or the application of them for good, is also shared by major technology companies in the globe, e.g., Google, Microsoft, and Facebook. Interestingly, these initiatives have invited a number of critiques for their feasibility and desirability, particularly in relation to the social (...) and political conditions of liberal democratic societies. In this article, I discuss whether these critiques also apply to the Chinese context and contend that Confucian philosophy provides the normative resources to answer these critiques. This cross-cultural analysis, therefore, allows us to formulate a different account of AI4SG, which I shall call ‘AI for Datong’, and helps us in our reimagining of the normative vision for AI. (shrink)

This article raises a very relevant question today: “Does AI think?” To come up with an answer, it explores several conceptions of knowledge, from classical Aristotelian notions to modern philosophers’ takes on it. For Aristotle, knowledge starts with the senses, and, through epagoge and nous, it grows into an understanding of the nature of the thing known, which is something that does not happen with AI. Modern schools of thoughts are either rationalist or empiricist. For rationalists, knowledge is innate, while (...) empiricists believe all knowledge comes from the senses. As Kant views it, knowledge is “built” on sensorial data with the use of theoretical reason categories. Based on these approaches, it is harder to claim that AI does not think by itself. The article also reviews current philosophers’ views on AI and AI thinking. Summing up, the answer to the initial question depends on the concept of knowledge adopted. As this article shares the classical notion of thinking, it concludes that AI does not think. (shrink)

Artificial intelligence (AI), blockchain, virtual and augmented reality, (semi-)autonomous ve- hicles, autoregulatory weapon systems, enhancement, reproductive technologies and human- oid robotics – these technologies (and many others) are no longer speculative visions of the future; they have already found their way into our lives or are on the verge of a breakthrough. These rapid technological developments awaken a need for orientation: what distinguishes hu- man from machine and human intelligence from artificial intelligence, how far should the body be allowed to (...) be changed and what are the dangers and opportunities presented by these technologies? Many of these questions are also addressed to theology. For example, questions about the image of humanity, the understanding of creation, the ethics of technological body interventions or the moral status of robots. What does theology have to say about these technological developments? It is the right time for theology to scientifically explore tech- nologization and AI and to formulate answers. As technology changes the various areas of human life, society and the world around us, the places and topics of theology are also undergoing transformation. Puzio, Anna: Theology Meets AI: Examining Perspectives, Tasks, and Theses on the Intersection of Technology and Religion. In: Puzio, Anna/Kunkel, Nicole/Klinge, Hendrik (Hg.): Alexa, How Do You Feel About Religion? Theological Approaches to Technology and Artificial Intelligence (Theology and AI 1). Darmstadt: wbg 2023, S. 29–41. DOI: 10.53186/1030373. (shrink)

This paper investigates whether AI can possess wisdom, a complex and deeply human capacity. We adopt an interdisciplinary approach, drawing on philosophy, 4E cognition, Material Engagement Theory, and engaged epistemology, to argue that wisdom is a dynamic force unfolding through meaningful life experiences and resonant interactions with the world. Central to our discussion is Rosa's concept of resonance, essential for fostering personal growth, emotional empathy, as well as existential and bodily connectedness to the world and its unfolding into an uncertain (...) future. Despite the advanced capabilities of AI/Large Language Models (LLMs), we demonstrate their inability to embody wisdom due to their lack of deep sense-making, embodied interaction, and meaningful engagement with the world and future potentials. We emphasize the need for cultivating human wisdom to ensure technological advancements enrich rather than diminish the human experience, advocating for a balanced and reflective human-technology relationship. (shrink)

In this article, we shed light on the emergence, diffusion, and use of socio-technological future visions. The artificial intelligence future vision of the German federal government is examined and juxtaposed with the respective news media coverage of the German media. By means of a content analysis of frames, it is demonstrated how the German government strategically uses its AI future vision to uphold the status quo. The German media largely adapt the government´s frames and do not integrate alternative (...) future narratives into the public debate. These findings are substantiated in the framing of AI futures in policy documents of the German government and articles of four different German newspapers. It is shown how the German past is mirrored in the German AI future envisioned by the government, safeguarding the present power constellation that is marked by a close unity of politics and industry. The German media partly expose the government´s frames and call for future visions that include fundamentally different political designs less influenced by the power structures of the past and present. (shrink)

Stories are an important indicator of our vision of the future. In the case of artificial intelligence (AI), dominant stories are polarized between notions of threat and myopic solutionism. The central storytellers—big tech, popular media, and authors of science fiction—represent particular demographics and motivations. Many stories, and storytellers, are missing. This paper details the accounts of missing AI narratives by leading scholars from a range of disciplines interested in AI Futures. Participants focused on the gaps between dominant narratives and (...) the untold stories of the capabilities, issues, and everyday realities of the technology. One participant proposed a “story crisis” in which these narratives compete to shape the public discourse on AI. Our findings indicate that dominant narratives distract and mislead public understandings and conceptions of AI. This suggests a need to pay closer attention to missing AI narratives. It is not simply about telling new stories, it is about listening to existing stories and asking what is wanted from AI. We call for realistic, nuanced, and inclusive stories, working with and for diverse voices, which consider (1) story-teller; (2) genre, and (3) communicative purpose. Such stories can then inspire the next generation of thinkers, technologists, and storytellers. (shrink)

Over the past few years, there has been a proliferation of artificial intelligence strategies, released by governments around the world, that seek to maximise the benefits of AI and minimise potential harms. This article provides a comparative analysis of the European Union and the United States’ AI strategies and considers the visions of a ‘Good AI Society’ that are forwarded in key policy documents and their opportunity costs, the extent to which the implementation of each vision is living up (...) to stated aims and the consequences that these differing visions of a ‘Good AI Society’ have for transatlantic cooperation. The article concludes by comparing the ethical desirability of each vision and identifies areas where the EU, and especially the US, need to improve in order to achieve ethical outcomes and deepen cooperation. (shrink)

The agentic web refers to a vision of the internet where AI agents play a central role in facilitating interactions, automating tasks, and enhancing user experiences. Realizing this vision requires us to rethink how we govern the internet. Within the agentic web, the promise of AI systems becoming more decentralized and autonomous represents unique challenges and opportunities for governance, necessitating innovative approaches to ensure responsible integration into society. Toward this end, we propose the Know Your Agent framework, designed (...) to manage Decentralized AI agents through identity verification, behavioral monitoring, and accountability mechanisms. Our approach integrates protocol science and legal engineering, utilizing blockchain technology to support these efforts. (shrink)

. The management of ethics within organisations typically occurs within a problem-solving frame of reference. This often results in a reactive, problem-based and externally induced approach to managing ethics. Although basing ethics management interventions on dealing with and preventing current and possible future unethical behaviour are often effective in that it ensures compliance with rules and regulations, the approach is not necessarily conducive to the creation of sustained ethical cultures. Nor does the approach afford (mainly internal) stakeholders the opportunity to (...) be co-designers of the organisations ethical future. The aim of this paper is to present Appreciative Inquiry (AI) as an alternative approach for developing a shared meaning of ethics within an organisation with a view to embrace and entrench ethics, thereby creating a foundation for the development of an ethical cul- ture over time. A descriptive case study based on an application of AI is used to illustrate the utility of AI as a way of thinking and doing to precede and complement problem-based ethics management systems and interventions. (shrink)

In artificial-intelligence (AI) and computer-vision research, photographic images are typically referred to as natural images. This means that images used or produced in this context are conceptualized within a binary as either natural or synthetic. Recent advances in creative AI technology, particularly generative adversarial networks and diffusion models, have afforded the ability to create photographic-seeming images, that is, synthetic images that appear natural, based on learnings from vast databases of digital photographs. Contemporary discussions of these images have thus far (...) revolved around the political and social implications of producing convincing fake photographs. However, these images are of theoretical interest for the fields of art history and visual studies for additional reasons. AI-generated photographic images resonate with many of the classic themes in photography: nature and the real, the unconscious and the uncanny, and discourses of power. This article therefore seeks to answer the question: Can photorealistic AI-generated images be defined as photographs? I argue that AI-generated photographs do indeed belong within in the wider discourse of photography, given their form and interpretation. (shrink)

Cinema and Machine Vision unfolds the aesthetic, epistemic, and ideological dimensions of machine-seeing films and television using computers. With its critical-technical approach, this book presents to the reader key new problems that arise as AI becomes integral to visual culture. The book theorises machine vision through a selection of aesthetics, film theory, and applied machine learning research, dispelling widely held assumptions about computer systems designed to watch and make images on our behalf. -/- At its heart, Cinema and (...) Machine Vision is an invitation for film and media scholars to critically engage with AI at a technical level, a prompt for scientists and engineers working with images and cultural data to critically reflect on where their assumptions about vision come from, and a joint recognition of the fruitful problems of working together to understand the algorithmic governance of the visual. (shrink)

From machine learning and computer vision to robotics and natural language processing, the application of data science and artificial intelligence is expected to transform health care (Ce...

The essential premise of the human-centered technology paradigm was clearly formulated by Howard Rosenbrock in the 1970s: technology should enrich rather than impoverish people’s work and life conditions. The increasing influence of technology in modern societies has been seen by some as offering great promise for the future, but by others as creating the electronic surveillance and/or manipulation of human genes, minds and beliefs. This paper approaches technological worlds as cultural visions in order to discuss and reflect the paradoxical process (...) of viewing technology as part of a hope for a more sustainable and human-centered future as well as part of an apocalypse of surveillance, violence and catastrophes. (shrink)

The notion of trustworthy AI has been proposed in response to mounting public criticism of AI systems, in particular with regard to the proliferation of such systems into ever more sensitive areas of human life without proper checks and balances. In Europe, the High-Level Expert Group on Artificial Intelligence has recently presented its Ethics Guidelines for Trustworthy AI. To some, the guidelines are an important step for the governance of AI. To others, the guidelines distract effort from genuine AI regulation. (...) In this chapter, we engage in a critical discussion of the concept of trustworthy AI by probing the concept both on theoretical and practical grounds, assessing its substance and the feasibility of its intent. We offer a concise overview of the guidelines and their vision for trustworthy AI and examine the conceptual underpinnings of trustworthy AI by considering how notions of 'trust' and 'trustworthiness' have been discussed in the philosophical literature. We then discuss several epistemic obstacles and moral requirements when striving to achieve trustworthy AI in practice before concluding with an argument in support of the establishment of a trustworthy AI culture that respects and protects foundational values. (shrink)

What is the most important reason for using Computer Vision methods in humanities research? In this article, I argue that the use of numerical representation and data analysis methods offers a new language for describing cultural artifacts, experiences and dynamics. The human languages such as English or Russian that developed rather recently in human evolution are not good at capturing analog properties of human sensorial and cultural experiences. These limitations become particularly worrying if we want to compare thousands, millions (...) or billions of artifacts—i.e. to study contemporary media and cultures at their new twenty-first century scale. When we instead use numerical measurements of image properties standard in Computer Vision, we can better capture details of a single artifact as well as visual differences between a number of artifacts–even if they are very small. The examples of visual dimensions that numbers can capture better then languages include color, shape, texture, contours, composition, and visual characteristics of represented faces, bodies and objects. The methods of finding structures and relationships in large numerical datasets developed in statistics and machine learning allow us to extend this analysis to very big datasets of cultural objects. Equally importantly, numerical image features used in Computer Vision also give us a new language to represent gradual and continuous temporal changes—something which natural languages are also bad at. This applies to both single artworks such as a film or a dance piece and also to changes in visual characteristics in millions of artifacts over decades or centuries. (shrink)

The current debate on artificial intelligence (AI) tends to associate AI imaginaries with the vision of a future technology capable of emulating or surpassing human intelligence. This article advocates for a more nuanced analysis of AI imaginaries, distinguishing “strong AI narratives,” i.e., narratives that envision futurable AI technologies that are virtually indistinguishable from humans, from "weak" AI narratives, i.e., narratives that discuss and make sense of the functioning and implications of existing AI technologies. Drawing on the academic literature on (...) AI narratives and imaginaries and examining examples drawn from the debate on Large Language Models and public policy, we underscore the critical role and interplay of weak and strong AI across public/private and fictional/non-fictional discourses. The resulting analytical framework aims to empower approaches that are more sensitive to the heterogeneity of AI narratives while also advocating normalising AI narratives, i.e., positioning weak AI narratives more firmly at the center stage of public debates about emerging technologies. (shrink)

The threat from possible future superintelligent AI has given rise to discussion of the so-called “value alignment problem”. This is the problem of how to ensure artificially intelligent systems align with human values, and thus (hopefully) mitigate risks associated with them. Naturally, AI value alignment is often discussed in relation to morally relevant values, such as the value of human lives or human wellbeing. However, solutions to the value alignment problem target all human values, not only morally relevant ones. Is (...) there a value alignment problem in other domains? In this paper, I explore whether the AI value alignment problem extends beyond morally relevant values to include aesthetic values. I demonstrate that the value alignment problem as typically framed includes aesthetic values, and, using examples from computer vision, put forward that AI may be misaligned with human values in the artistic realm. Whilst misalignment may be cause for concern when considering AI creativity, I argue that aesthetic value is a case in which we do not want AI to be fully aligned with human values. In doing so, I offer support to Peterson’s moderate value alignment thesis. (shrink)

In this article we introduce the concept of implied optical perspective in deep learning computer vision systems. Taking the BBC's experimental television programme “Made by Machine: When AI met the Archive” as a case study, we trace a conceptual and material link between the system used to automatically “watch” the television archive and a specific type of photographic practice. From a computational aesthetics perspective, we show how deep learning machine vision relies on photography, its technical regimes and epistemic (...) advantages, and we propose a novel way to identify the latent camera through which the BBC archive was seen by machine. (shrink)

This paper criticises the ideological dimension of the AI narrative. It does so by questioning the implicit assumptions behind its vision, which promises a world that automatically adapts to our desires before we even know them. These assumptions hinge on a misconception of the value of desire as residing exclusively with its fulfilment, warranting human manipulation for increased predictability. This social trajectory towards algorithmic governance, rather than delivering on the promised fulfilment, undermines our capacity to sustain the same desire (...) that it uses to justify its enterprise. (shrink)

This paper traces the shift from the age of realism to the age of virtualism we are currently witnessing. To do so, I draw on older theories announcing this advent (mostly Baudrillard in Simulacra and simulation. Transl. Sheila Glaser. University of Michigan, Ann Arbor, 1994 [1981]; Serres in Atlas. Édition Julliard, Paris, 1994; Virilio in The vision machine. Transl. Rose J. Indiana UP, Bloomington, 1994). I will describe how AI destabilizes fundamental distinctions upon which reality is built—such as the (...) difference between truth and fiction, between existence and simulation, between the actual and the potential, between game and everyday life, between person and avatar. Against the backdrop of a broader notion of the virtual (drawing on Deleuze in The actual and the virtual. Transl. Eliot Ross Albert in Parnet C Dialogues. Bloomsbury, London, pp 148–152, 2006 [1996]), I will read current realist theories (Chalmers in Reality plus—virtual worlds and the problems of philosophy. Allen Lane, London in 2022; Gabriel in Why the world does not exist. Transl. Gregory S. Moss. Polity, Cambridge, 2015; Ferraris in Positive realism. Zero Books, Arlesford, 2015; Meillassoux in After finitude—an essay on the necessity of contingency. Transl. Brassler R. Bloomsbury, London, 2008) as symptoms of the ongoing shift (rather than countermeasures against it), because they result in an inability to do justice to the epistemic and existential changes resulting from the erosion of the foundations of reality. The consequences of this shift are hard to predict and can only partially be outlined in this paper, which will end in a cautious attempt to do so (chapters 5 and 6). Starting off with a brief overview on this topic (chapter 1), I will trace the reasons for my diagnosis focusing first on what I call the “age of reality” currently coming to an end (chapter 2), then on why virtuality cannot be subsumed under reality (chapter 3), then how virtuality is currently replacing reality (chapter 4). (shrink)

National Artificial Intelligence (AI) strategies articulate imaginaries of the integration of AI into society and envision the governing of AI research, development and applications accordingly. To integrate these central aspects of national AI strategies under one coherent perspective, this paper presented an analysis of Germany’s strategy ‘AI made in Germany’ through the conceptual lens of ordoliberal political rationality. The first part of the paper analyses how the guiding vision of a human-centric AI not only adheres to ethical and legal (...) principles consistent with Germany’s liberal democratic constitutional system but also addresses the risks and promises inherent to the ordoliberal problematization of freedom. Second, it is scrutinized how the strategy cultivates the fear of not achieving technological sovereignty in the AI sector. Thereby, it frames the global AI race as a race of competing (national) approaches to governing AI and articulates an ordoliberal approach to governing AI (the ‘third way’), according to which government has to operate between the twin dangers of governing too much and not governing enough. Third, the paper analyses how this ordoliberal proportionality of governing structures Germany’s Science Technology & Innovation Policy. It is shown that the corresponding risk-based approach of regulating AI constitutes a security apparatus as it produces an assessment of fears: weighting the fear of the failure to innovate with the fear of the ramifications of innovation. Finally, two lines of critical engagement based on this analysis are conducted. (shrink)

The US is promoting a new vision of a “Good AI Society” through its recent AI Bill of Rights. This offers a promising vision of community-oriented equity unique amongst peer countries. However, it leaves the door open for potential rights violations. Furthermore, it may have some federal impact, but it is non-binding, and without concrete legislation, the private sector is likely to ignore it.

Motivated by the issues raised by the merging of women and machines in science fiction, this article explores gender representations in Spike film Her that discusses the interaction between a male human and a disembodied female whose consciousness is held in an artificial intelligence (AI) operating system. One of the primary questions regarding the representation of the female AI is whether the film encourages a feminist perspective, that promotes female subjectivity in the era of the post-human, or it ends up (...) perpetuating visions of women’s oppression and objectification. Visual representations are important when discussing gender binaries, as they can be related to the image and the physical sexual differences. However, the role of sound is also crucial, as it contributes to different readings. In my analysis, I examine the merging and unmerging of audio and visual in the film. The female voice is the focal point of the analysis. (shrink)

Artificial intelligence (AI) technologies in medicine are gradually changing biomedical research and patient care. High expectations and promises from novel AI applications aiming to positively impact society raise new ethical considerations for patients and caregivers who use these technologies. Based on a qualitative content analysis of semi-structured interviews and focus groups with healthcare professionals (HCPs), patients, and family members of patients with Parkinson’s Disease (PD), the present study investigates participant views on the comparative benefits and problems of using human versus (...) AI predictive computer vision health monitoring, as well as participants’ ethical concerns regarding these technologies. Participants presumed that AI monitoring would enhance information sharing and treatment, but voiced concerns about data ownership, data protection, commercialization of patient data, and privacy at home. They highlighted that privacy issues at home and data security issues are often linked and should be investigated together. Findings may help technologists, HCPs, and policymakers determine how to incorporate stakeholders’ intersecting but divergent concerns into developing and implementing AI PD monitoring tools. (shrink)

Artificial intelligence (AI) and machine learning (ML) are becoming increasingly significant areas of research for scholars in science and technology studies (STS) and media studies. In March 2020, Waymo, Google/Alphabet’s autonomous vehicle project, introduced the ‘Open Dataset Virtual Challenge’, an annual competition leveraging their Waymo Open Dataset. This freely accessible dataset comprises annotated autonomous vehicle data from their own Waymo vehicles. Yearly, Waymo has continued to host iterations of this challenge, inviting teams of computer scientists to tackle evolving machine learning (...) and vision problems using Google's data and tools. This article analyses these challenges, situating them within the context of the ‘Grand Challenges’ of artificial intelligence (AI), which aimed to foster accountable and commercially viable advancements in the late 1980s. Through two exploratory workshops, we adopted a ‘technographic’ approach to examine the pivotal role of challenges in the development and political economy of AI. Serving as an organising principle for the AI innovation ecosystem, the challenge connects companies and external collaborators, driving advancements in specific machine vision domains. By exploring six key themes—interface methods, incrementalism, metrics, AI vernacular, applied domains, and competitive advantages—the article illustrates the role of these challenges in shaping AI research and development. By unpacking the dynamic interaction between data, computation, and labour, these challenges serve as catalysts propelling advancements towards self-driving technologies. The study reveals how challenges have historically and presently shaped the evolving landscape of self-driving and AI technologies. (shrink)

Different people have different perceptions about artificial intelligence (AI). It is extremely important to bring together all the alternative frames of thinking—from the various communities of developers, researchers, business leaders, policymakers, and citizens—to properly start acknowledging AI. This article highlights the ‘fruitful collaboration’ that sociology and AI could develop in both social and technical terms. We discuss how biases and unfairness are among the major challenges to be addressed in such a sociotechnical perspective. First, as intelligent machines reveal their nature (...) of ‘magnifying glasses’ in the automation of existing inequalities, we show how the AI technical community is calling for transparency and explainability, accountability and contestability. Not to be considered as panaceas, they all contribute to ensuring human control in novel practices that include requirement, design and development methodologies for a fairer AI. Second, we elaborate on the mounting attention for technological narratives as technology is recognized as a social practice within a specific institutional context. Not only do narratives reflect organizing visions for society, but they also are a tangible sign of the traditional lines of social, economic, and political inequalities. We conclude with a call for a diverse approach within the AI community and a richer knowledge about narratives as they help in better addressing future technical developments, public debate, and policy. AI practice is interdisciplinary by nature and it will benefit from a socio-technical perspective. (shrink)

This paper deals with various aspects of the development of data systems for engineering materials. The problem considered here is the difference between the end-users' mental model of materials, which focuses on performance, and the concepts of properties of materials held by materials specialists. Previous treatises on this problem have elaborated on systems aspects in general, emphasising incompatibilities in the relationship mentioned and the means of overcoming these incompatibilities by service management. Another perspective applied has been the historical one, combined (...) with experience of traditional views on science and technology. The present paper pursues this general path by discussing the problem in terms of visions, illusions and myths. These phenomena are thought to be both inevitable in this context and necessary in any attempt to understand the dilemma of data systems for engineering materials. It is believed that the views of the different parties involved are to a great extent steered by visions, illusions and myths, examples of which are discussed. Furthermore, it is suggested that these phenomena have roots in, or are expressions of, paradigms and values related to world pictures. Admittedly eclectic, this discussion leads to the conclusion that a solution to the dilemma in question cannot be found within computer science, materials technology and design theory only. Guidance has to be sought in philosophy and theory of science as well as in literature and the arts. In order to make it possible to implement ideas arrived at by such means, practitioners of psychology will probably have to be consulted. (shrink)

Il lavoro consiste in una particolare rilettura del testo cusaniano, nella quale si cerca di evidenziare, tra le altre fonti, soprattutto la presenza di Meister Eckhart. La “discesa” nel fondo dell'anima è presentata come il culmine teoretico di quel cammino di visione a cui e-duca l'aegnima dell'icona. Per queste ragioni l'articolo punta sull'influsso della mistica speculativa in campo teoretico e di quella dottrina che M. Eckhart chiama “Generazione del Logos nell'anima”. Tale trattazione apre poi il senso dell'ampia sezione dedicata alla (...) filosofia negativa e ai “nomi divini” del Deus Trinitas, stavolta sulla scia di Dionigi: Infinito, Non-Aliud e Padre. Centrale è la figura del Cristo, unica vera condizione di possibilità della visione “di” Dio in quanto unico mediatore tra il finito e l'infinito; in Cristo si realizza quella paradossale unione delle due nature ed offre così all'umanità la chiave tanto desiderata per avvicinare l'Infinito. (shrink)

The advent of AI calls for an existential self-redefinition of humanity. It necessitates the establishment of a pluralistic global humanist culture that enables us to coexist in the new world of active media and autopoietic technology. In this paper, related philosophical questions give rise to the proposal of a novel metaculture that elevates human heritages and cultural memories to the plane of a digital AI- based infrastructure. I argue for a balanced and holistic approach to human-to-human and human–AI interactions and (...) metaculture that can be developed in the form of combinatorial “metagames” that reflect the potential of human consciousness, transcend the boundaries between technology, human embodiment and biology, the arts, sciences and humanities, and philosophy, and, finally, include the element of meaningful coincidence and spontaneity “in the second potency.” Hermann Hesse’s final novel, The Glass Bead Game, offers a key to understanding this basic idea. His vision is extremely relevant today. Based on this, the concept of cultivating global cultural memories through innovative aesthetic-epistemic “Glass Bead Games 2.0” is discussed further from a systematic angle. To complement this, reference is also made to Hesse’s own source of inspiration: Novalis’s “encyclopedist” approach interlinks aesthetic and epistemic productivity in a way that could become a major starting point to create a new holistic metaculture in the Age of AI. (shrink)

As China and the United States strive to be the primary global leader in AI, their visions are coming into conflict. This is frequently painted as a fundamental clash of civilisations, with evidence based primarily around each country’s current political system and present geopolitical tensions. However, such a narrow view claims to extrapolate into the future from an analysis of a momentary situation, ignoring a wealth of historical factors that influence each country’s prevailing philosophy of technology and thus their overarching (...) AI strategies. In this article, we build a philosophy-of-technology-grounded framework to analyse what differences in Chinese and American AI policies exist and, on a fundamental level, why they exist. We support this with Natural Language Processing methods to provide an evidentiary basis for our analysis of policy differences. By looking at documents from three different American presidential administrations––Barack Obama, Donald Trump, and Joe Biden––as well as both national and local policy documents (many available only in Chinese) from China, we provide a thorough comparative analysis of policy differences. This article fills a gap in US–China AI policy comparison and constructs a framework for understanding the origin and trajectory of policy differences. By investigating what factors are informing each country’s philosophy of technology and thus their overall approach to AI policy, we argue that while significant obstacles to cooperation remain, there is room for dialogue and mutual growth. (shrink)

In the past few years, several democratic governments have published their National AI Strategies (NASs). These documents outline how AI technology should be implemented in the public sector and explain the policies that will ensure the ethical use of personal data. In this article, I examine these documents as political texts and reconstruct the political imaginary that underlies them. I argue that these documents intervene in contemporary democratic politics by suggesting that AI can help democracies overcome some of the challenges (...) they are facing. To achieve this, NASs use different kinds of imaginaries—democratic, sociotechnical and data—that help citizens envision how a future AI democracy might look like. As part of this collective effort, a new kind of relationship between citizens and governments is formed. Citizens are seen as autonomous data subjects, but at the same time, they are expected to share their personal data for the common good. As a result, I argue, a new kind of political imaginary is developed in these documents. One that maintains a human-centric approach while championing a vision of collective sovereignty over data. This kind of political imaginary can become useful in understanding the roles of citizens and governments in this technological age. (shrink)

AI and robotic technologies attract much hype, including utopian and dystopian future visions of technologically driven provision in the health and care sectors. Based on 30 interviews with scientists, clinicians and other stakeholders in the UK, Europe, USA, Australia, and New Zealand, this paper interrogates how those engaged in developing and using AI and robotic applications in health and care characterize their future promise, potential and challenges. We explore the ways in which these professionals articulate and navigate a range of (...) high and low expectations, and promissory and cautionary future visions, around AI and robotic technologies. We argue that, through these articulations and navigations, they construct their own perceptions of socially and ethically ‘acceptable futures’ framed by an ‘ethics of expectations.’ This imbues the envisioned futures with a normative character, articulated in relation to the present context. We build on existing work in the sociology of expectations, aiming to contribute towards better understanding of how technoscientific expectations are navigated and managed by professionals. This is particularly timely since the COVID-19 pandemic gave further momentum to these technologies. (shrink)

This article attempts to demystify computer vision for novice programmers through a survey of new applications in the arts, system design considerations, and contemporary tools. It introduces the concept and gives a brief history of computer vision within interactive art from Myron Kruger to the present. Basic techniques of computer vision such as detecting motion and object tracking are discussed in addition to various software applications created for exploring the topic. As an example, the results of a (...) one-week machine vision workshop are presented to show how designers are able to apply their skills toward creating novel uses of these technologies. The article concludes with a listing of code for basic computer vision techniques. (shrink)

Thirty years ago, I elaborated on a position that could be seen as a compromise between an "extreme," symbol-based AI, and a "neurochemical reductionism" in AI. The present article recalls aspects of the espoused framework of schema theory that, it suggested, could provide a better bridge from human psychology to brain theory than that offered by the symbol systems of A. Newell and H. A. Simon.

The present comment concerns a recent AI & Ethics article which purports to report evidence of speciesist bias in various popular computer vision (CV) and natural language processing (NLP) machine learning models described in the literature. I examine the authors' analysis and show it, ironically, to be prejudicial, often being founded on poorly conceived assumptions and suffering from fallacious and insufficiently rigorous reasoning, its superficial appeal in large part relying on the sequacity of the article's target readership.