Artificial intelligence (AI) is becoming increasingly influential in most people’s lives. This raises many philosophical questions. One is what responsibility we have as individuals to guide the development of AI in a desirable direction. More specifically, how should this responsibility be distributed among individuals and between individuals and other actors? We investigate this question from the perspectives of five principles of distribution that dominate the discussion about responsibility in connection with climate change: effectiveness, equality, desert, need, and ability. Since much (...) is already written about these distributions in that context, we believe much can be gained if we can make use of this discussion also in connection with AI. Our most important findings are: (1) Different principles give different answers depending on how they are interpreted but, in many cases, different interpretations and different principles agree and even strengthen each other. If for instance ‘equality-based distribution’ is interpreted in a consequentialist sense, effectiveness, and through it, ability, will play important roles in the actual distributions, but so will an equal distribution as such, since we foresee that an increased responsibility of underrepresented groups will make the risks and benefits of AI more equally distributed. The corresponding reasoning is true for need-based distribution. (2) If we acknowledge that someone has a certain responsibility, we also have to acknowledge a corresponding degree of influence for that someone over the matter in question. (3) Independently of which distribution principle we prefer, ability cannot be dismissed. Ability is not fixed, however and if one of the other distributions is morally required, we are also morally required to increase the ability of those less able to take on the required responsibility. (shrink)

People often complain that AI is not developing as well as expected. They say, "Progress was quick in the early years of AI, but now it is not growing so fast." I find this funny, because people have been saying the same thing as long as I can remember. In fact we are still rapidly developing new useful systems for recognizing patterns and for supervising processes. Furthermore, modern hardware is so fast and reliable that we can employ almost any programs (...) we can create. Good new systems appear every year, for different "expert" applications. (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)

People often complain that AI is not developing as well as expected. They say, "Progress was quick in the early years of AI, but now it is not growing so fast." I find this funny, because people have been saying the same thing as long as I can remember. In fact we are still rapidly developing new useful systems for recognizing patterns and for supervising processes. Furthermore, modern hardware is so fast and reliable that we can employ almost any programs (...) we can create. Good new systems appear every year, for different "expert" applications. (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)

The article “Philosophy is crucial in the age of AI” by Anthony Grayling and Brian Ball explores the significant role philosophy has played in the development of Artificial Intelligence (AI) and its continuing relevance in guiding the future of AI technologies. The authors trace the historical contributions of philosophers and logicians, such as Gottlob Frege, Kurt Godel, and Alan Turing, in shaping the foundational principles of AI. They argue that philosophical inquiry remains essential, especially in addressing complex issues like (...) consciousness, creativity, and the alignment of AI with human values. The article emphasizes the interdisciplinary collaboration needed to navigate the ethical and societal challenges posed by advancing AI systems, suggesting that philosophy is crucial in ensuring these technologies develop responsibly and ethically. (shrink)

This article questions the effects on urban research dynamics of the Big Data and AI turn in urban management. Increasing access to large datasets collected in real time could make certain mathematical models developed in research fields related to the management of urban systems obsolete. These ongoing evolutions are the subject of numerous works whose main angle of reflection is the future of cities rather than the transformations at work in the academic field. Our article proposes grasp the scientific (...) dynamics in areas of research related to two urban systems: transportation and water. The article demonstrates the importance of grasping these dynamics if we want to be able to apprehend what the urban management of tomorrow's cities will be like. To analyse these research areas’ dynamics, we use two complementary materials: bibliometric data and interviews. The interviews conducted in 2018 with academics and higher education officials in Paris and Edinburgh suggest avenues for hybridization between traditional modelling approaches and research in machine learning, artificial intelligence and Big Data. The bibliometric analysis highlight the trends at work: it shows that traffic flow as well as transportation studies are focussing more and more on AI and Big Data and that traffic flow studies are arousing a growing interest among computer scientists, while, so far, this interest is less pronounced in the water research area, and more especially regarding water quality. The differences observed between research on transportation and that on water confirm the multifaceted nature of the developments at work and encourage us to reject overly hasty and simplistic generalisations about the transformations underway. (shrink)

We live in exciting times for AI and Law: technical developments are moving at a breakneck pace, and at the same time, the call for more robust AI governance and regulation grows stronger. How should we as an AI & Law community navigate these dramatic developments and claims? In this Presidential Address, I present my ideas for a way forward: researching, developing and evaluating real AI systems for the legal field with researchers from AI, Law and beyond. I will demonstrate (...) how we at the Netherlands National Police Lab AI are developing responsible AI by combining insights from different disciplines, and how this connects to the future of our field. (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)

For those who find Dreyfus’s critique of AI compelling, the prospects for producing true artificial human intelligence are bleak. An important question thus becomes, what are the prospects for producing artificial non-human intelligence? Applying Dreyfus’s work to this question is difficult, however, because his work is so thoroughly human-centered. Granting Dreyfus that the body is fundamental to intelligence, how are we to conceive of non-human bodies? In this paper, I argue that bringing Dreyfus’s work into conversation with the work of (...) Mark Bickhard offers a way of answering this question, and I try to suggest what doing so means for AI research. (shrink)

This study addresses the current lack of empirical data on the experiences and attitudes of clinical research professionals towards AI-powered clinical trial management tools. Clinical research professionals affiliated with various Swiss and international clinical research networks were invited to participate in an online survey. The survey focused on nine use cases of AI-powered clinical trial management tools. Participants were asked to share their ethical considerations, and their experiences were assessed at both the individual and institutional levels. Answers from 110 participants, (...) primarily from Swiss academic institutions, were included in the data analysis. While participants generally held positive attitudes, mixed views were also common. Governmental attitudes were widely perceived as unclear or cautious, with the associated regulatory opacity possibly contributing to the limited adoption of AI in trial management observed in this study. In addition to a clear AI governance, ethical compliance and training emerged as crucial aspects. There was also broad consensus on the necessity of informing patients about tools’ uses and of ensuring an independent certification of the respective tools. The widespread adoption of AI-powered clinical trial management tools remains distant, entangled in a net of complexities that require further empirical investigation. Ethical concerns appear to play a crucial role, driven by distrust and the absence of a clear regulatory framework. Urgent actions are needed at both institutional and governmental levels, including the establishment of a governance framework and training provision. (shrink)

How can one build AI systems such that they pursue the goals their designers want them to pursue? This is the alignment problem. Numerous authors have raised concerns that, as research advances and systems become more powerful over time, misalignment might lead to catastrophic outcomes, perhaps even to the extinction or permanent disempowerment of humanity. In this paper, I analyze the severity of this risk based on current instances of misalignment. More specifically, I argue that contemporary large language models and (...) game-playing agents are sometimes misaligned. These cases suggest that misalignment tends to have a variety of features: misalignment can be hard to detect, predict and remedy, it does not depend on a specific architecture or training paradigm, it tends to diminish a system’s usefulness and it is the default outcome of creating AI via machine learning. Subsequently, based on these features, I show that the risk of AI alignment magnifies with respect to more capable systems. Not only might more capable systems cause more harm when misaligned, aligning them should be expected to be more difficult than aligning current AI. (shrink)

Artificial intelligence and related technologies are changing both the law and the legal profession. In particular, technological advances in fields ranging from machine learning to more advanced robots, including sensors, virtual realities, algorithms, bots, drones, self-driving cars, and more sophisticated "human-like" robots are creating new and previously unimagined challenges for regulators. These advances also give rise to new opportunities for legal professionals to make efficiency gains in the delivery of legal services. With the exponential growth of such technologies, radical disruption (...) seems likely to accelerate in the near future. This collection brings together a series of contributions by leading scholars in the newly emerging field of artificial intelligence, robotics, and the law. The aim of the book is to enrich legal debates on the social meaning and impact of this type of technology. The distinctive feature of the contributions presented in this edition is that they address the impact of these technological developments in a number of different fields of law and from the perspective of diverse jurisdictions. Moreover, the authors utilize insights from multiple related disciplines, in particular social theory and philosophy, in order to better understand and address the legal challenges created by AI. Therefore, the book will contribute to interdisciplinary debates on disruptive new AI technologies and the law. (shrink)

Physicians and other healthcare professionals are increasingly finding ways to use artificial intelligent decision support systems in their work. IBM Watson Health, for example, is a commercially available technology that is providing AI-DDS services in genomics, oncology, healthcare management and more.1 AI’s ability to scan massive amounts of data, detect patterns, and derive solutions from data is vastly more superior than that of humans. AI technology is undeniably integral to the future of healthcare and public health, and thoughtful consideration (...) of the legal, ethical and moral issues surrounding this technology is a must. The authors of the article, Responsibility, Second Opinions, and Peer-Disagreement—Ethical and Epistemological Challenges of Using AI in Clinical Diagnostic Contexts, provide an informed discussion of how AI-DSS may be used, both practically and ethically, to assist healthcare professionals in cooperative diagnostic processes2. The authors propose a process, whereby AI-DSS would provide a physician a second opinion, and when there is a mismatch between opinions, another physician would provide a third opinion. This approach maintains a ‘physician-in-charge’ perspective, and suggests that decision-making must ultimately be made by a person. This approach is also consistent with the ‘physician in-the-loop’ concept, such that even when increasingly autonomous AI-DSSs are put to use, physicians will still be providing checks and overseeing clinical decisions. The authors conceptualise AI as a replacement of human cognitive labour. That is, AI is used to supplant a human professional in particular functions …. (shrink)

Generative AI technologies have the potential to be socially and politically transformative. In this paper, we focus on exploring the potential impacts that Generative AI could have on the functioning of our democracies and the nature of citizenship. We do so by drawing on accounts of deliberative democracy and the deliberative virtues associated with it, as well as the reciprocal impacts that social media and Generative AI will have on each other and the broader information landscape. Drawing on this background (...) theory, we outline some of the key positive and negative impacts that Generative AI is likely to have on democratic citizenship. The political significance of these impacts suggests the need for further regulation. (shrink)

1. Michael A PetersBeijing Normal UniversityChatGPT is an AI chatbot released by OpenAI on November 30, 2022 and a ‘stable release’ on February 13, 2023. It belongs to OpenAI’s GPT-3 family (genera...

This collection of quotes demonstrates the elegant simplicity of Ai Weiwei's thoughts on key aspects of his art, politics, and life. A master at communicating powerful ideas in astonishingly few words, Ai Weiwei is known for his innovative use of social media to disseminate his views. The book is organized into six categories: freedom of expression; art and activism; government, power, and moral choices; the digital world; history, the historical moment, and the future; and personal reflections. Together, these quotes (...) span some of the most revealing moments of Ai Weiwei's eventful career-from his risky investigation into student deaths in the 2008 Sichuan earthquake to his arbitrary arrest in 2011-providing a window into the mind of one of the world's most electrifying and courageous contemporary artists. Ai Weiwei is one of China's most influential and inspiring figures. Artist, architect, curator, and activist, he has been an outspoken critic of the Chinese government's stance on human rights and democracy. (shrink)

Companies increasingly deploy artificial intelligence technologies in their personnel recruiting and selection process to streamline it, making it faster and more efficient. AI applications can be found in various stages of recruiting, such as writing job ads, screening of applicant resumes, and analyzing video interviews via face recognition software. As these new technologies significantly impact people’s lives and careers but often trigger ethical concerns, the ethicality of these AI applications needs to be comprehensively understood. However, given the novelty of AI (...) applications in recruiting practice, the subject is still an emerging topic in academic literature. To inform and strengthen the foundation for future research, this paper systematically reviews the extant literature on the ethicality of AI-enabled recruiting to date. We identify 51 articles dealing with the topic, which we synthesize by mapping the ethical opportunities, risks, and ambiguities, as well as the proposed ways to mitigate ethical risks in practice. Based on this review, we identify gaps in the extant literature and point out moral questions that call for deeper exploration in future research. (shrink)

The increasing availability of large‐scale, complex data has made research into how human genomes determine physiology in health and disease, as well as its application to drug development and medicine, an attractive field for artificial intelligence (AI) approaches. Looking at recent developments, we explore how such approaches interconnect and may conflict with needs for and notions of causal knowledge in molecular genetics and genomic medicine. We provide reasons to suggest that—while capable of generating predictive knowledge at unprecedented pace and scale—if (...) and how these approaches will be integrated with prevailing causal concepts will not only determine the future of scientific understanding and self‐conceptions in these fields. But these questions will also be key to develop differentiated policies, such as for education and regulation, in order to harness societal benefits of AI for genomic research and medicine. (shrink)

The last decade has seen significant improvements in Artificial Intelligence (AI) technologies, including robotics, machine vision, speech recognition and text generation. Increasing automation will undoubtedly affect the future of work, and discussions on how the development of AI in the workplace will impact labor markets often include two scenarios: (1) labor replacement and (2) labor enabling. The former involves replacing workers with machines, while the latter assumes that human-machine cooperation can significantly improve worker productivity. In this context, it is (...) often argued that (1) could lead to mass unemployment and that (2) therefore would be more desirable. We argue, however, that the labor-enabling scenario conflates two distinct possibilities. On the one hand, technology can increase productivity while also promoting “the goods of work,” such as the opportunity to pursue excellence, experience a sense of community and contribute to society (human augmentation). On the other hand, higher productivity can also be achieved in a way that reduces opportunities for the “goods of work” and/or increases “the bads of work,” such as injury, reduced physical and mental health, reduction of autonomy, privacy and human dignity (human stunting). We outline the differences of these outcomes and discuss the implications for the labor market in the context of contemporaneous discussions on the value of work and human wellbeing. (shrink)

This paper interrogates the growing pervasiveness of affect recognition tools as an emerging layer human-centric automated management in the global workplace. While vendors tout the neoliberal incentives of emotion-recognition technology as a pre-eminent tool of workplace wellness, we argue that emotional AI recalibrates the horizons of capital not by expanding outward into the consumer realm (like surveillance capitalism). Rather, as a new genus of digital Taylorism, it turns inward, passing through the corporeal exterior to extract greater surplus value and managerial (...) control from the affective states of workers. Thus, empathic surveillance signals a profound shift in the ontology of human labor relations. In the emotionally quantified workplace, employees are no longer simply seen as physical capital, but conduits of actuarial and statistical intelligence gleaned from their most intimate subjective states. As a result, affect-driven automated management means that priority is often given to actuarial rather than human-centered managerial decisions. (shrink)

Artificial Intelligence (AI) is predicted to have a deep impact on the future of work and employment. The paper outlines a normative framework to understand and protect human freedom and justice in this transition. The proposed framework is based on four main ideas: going beyond the idea of a Basic Income to compensate the losers in the transition towards AI-driven work, towards a Responsible Innovation approach, in which the development of AI technologies is governed by an inclusive and deliberate (...) societal judgment; going beyond a philosophical conceptualisation of social justice only focused on the distribution of ‘primary goods’, towards one focused on the different goals, values, and virtues of various social practices (Walzer’s ‘spheres of justice’) and the different individual capabilities of persons (Sen’s ‘capabilities’); going beyond a classical understanding of capital, towards one explicitly including mental capacities as a source of value for AI-driven activities. In an effort to promote an interdisciplinary approach, the paper combines political and economic theories of freedom, justice and capital with recent approaches in applied ethics of technology, and starts applying its normative framework to some concrete example of AI-based systems: healthcare robotics, ‘citizen science’, social media and platform economy. (shrink)

Applications of artificial intelligence (AI) bear great transformative potential in the economic, technological and social sectors, impacting especially future work environments. Ethical regulation of AI requires a relational understanding of the technology by relevant stakeholder groups such as researchers, developers, politicians, civil servants, affected workers or other users applying AI in their work processes. The purpose of this paper is to support relational AI discourse for an improved ethical framing and regulation of the technology. The argumentation emphasizes a widespread (...) reembodied understanding of AI technology as critical requirement for capable ethical and regulatory frameworks. A sociotechnical perspective encourages the material interpretation of AI as reembodied adaptation of biological intelligence. Reviewing Cartesian dualism as motivating the disembodiment of human intelligence for its transfer to machines, the argumentation develops an integrated embodiment concept of AI in its mechanistic, naturalistic, combined AI and neuroethical, and relational contexts. This concept is discussed in relation to basic phenomenological and postphenomenological assumptions, and is applied to the example of AI-based neurotechnology potentially disrupting future work processes. Strengthening a human-centered approach, the presented concept for a reembodied understanding of AI technology enables better integrated ethical and regulatory debates, and improves social discourse and human agency in developing and regulating AI technology. (shrink)

Historically, the practice of medicine has been a physically intimate endeavor. Physicians have used their hands to palpate and reveal the secrets hidden within the body. Smelling the breath for the ketosis of diabetes or tasting the skin for the saltiness of cystic fibrosis were among the physician's essential practices. Today, perhaps the most defining characteristic of a brilliant clinician is the ability to synthesize many images—from electrocardiograms, ultrasounds, CT scans, and so forth—into a coherent picture that can guide our (...) diagnosis and treatment. Yet this is rapidly becoming a Sisyphean task. Just as we are about to drown in a deluge of data, AI is throwing us a life preserver, to save not only our patients but ourselves. But where will AI take us? (shrink)

Work has always been a significant source of ethical questions, philosophical reflection, and political struggle. Although the future of work in a sense is always at stake, the issue is particularly relevant right now, in light of the advent of advanced AI systems and the collective experience of the COVID-19 pandemic. This has reinvigorated philosophical discussion and interest in the study of the future of work. The purpose of this survey article is to provide an overview of the (...) emerging philosophical field that engages with the future of work, with a special focus on equality and justice, and to outline a research agenda that can help the field to develop further. Section 2 provides some historical context for the current surge in interest in the topic. Then, we discuss what work is and whether there is a philosophy of work (Section 3). The four main sub-debates we then turn to concern the value of work (Section 4), distributive justice and work (Section 5), productive justice (Section 6), and institutional reforms prompted by changes in how work is organized (Section 7). The final section discusses the importance of the distinction between ideal and non-ideal theory in philosophical investigations into the future of work. (shrink)

In Deep Medicine, Eric Topol argues that the development of artificial intelligence (AI) for healthcare will lead to a dramatic shift in the culture and practice of medicine. Topol claims that, rather than replacing physicians, AI could function alongside of them in order to allow them to devote more of their time to face-to-face patient care. Unfortunately, these high hopes for AI-enhanced medicine fail to appreciate a number of factors that, we believe, suggest a radically different picture for the (...) class='Hi'>future of healthcare. Far from facilitating a return to “the golden age of doctoring”, the role of economic and institutional considerations in determining how medical AI will be used mean that it is likely to further erode therapeutic relationships and threaten professional and patient satisfaction. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:The Touching TestAI and the Future of Human IntimacyMartha J. Reineke (bio)Each Friday, the New York Times publishes Love Letters, a compendium of articles on courtship. A recent story featured Melinda, a real estate agent, and Calvin, a human resources director.1 They had met at a market deli counter. On their first date, a lasagna dinner at Melinda's home, Calvin posed the question, "What are you looking for (...) in a man?" To his surprise, Melinda reached into her pocket and pulled out a two-page list, "Melinda's Husband Traits." Her 46-item list begins with "Christian, honor God, put Him first" and includes as entry number 37, "He likes to be touched and likes to touch me." Notwithstanding laudable features of Melinda's inventory, if David Levy, President of the International Computer Games Association and an expert on artificial intelligence (AI), is correct in his predictions, in the years ahead, women like Melinda who know exactly what they are looking for in a husband will desire something radically new: a robot. After all, artificial agents will soon possess or improve on every quality the romantically inclined previously have sought in a human partner. [End Page 123]Levi predicts robots will be preferred romantic partners by the middle of this century.2 Capable of providing erotic satisfaction and creating deep emotional bonds with human partners, these robots will be an achievable outcome of AI engineering that already has brought to market industrial and service robots, virtual pets, and caregiver robots for the elderly. Levi offers a research-based inventory of traits a robot will offer its human partner: kindness and understanding, a sense of humor, expressiveness, intelligence, and sociability.3 He pinpoints additional features that will facilitate romance: The ideal robot partner will elicit erotic attraction, give evidence of readiness for a serious relationship with its verbal assertions, and possess a capacity for mutual intimacy.4 Levi's argument is intentionally provocative, for he emphasizes the centrality of sex to future robot/human pairings, waxing rhapsodic about the performative superiority of robots to humans in the sexual act.5Elaborating on potential human love relationships with robots, Levi asserts that a robot will need to master imitation if a human is to want it as a romantic partner. Not only is imitation a central aspect of every human-to-human relationship, but also imitation has been identified by researchers as a crucial element in romantic desire.6 Levi states that human-to-human attraction is founded on similarities between prospective partners in appearance, personality, and social context. It is sustained only through what Levi calls "reciprocal liking."7 For romantic relationships between humans and robots to flourish, they too must engage in acts of reciprocal imitation.In highlighting the necessity of imitation in effective robot and human interactions, Levi draws close to René Girard's theory of "mimetic desire." According to Girard, imitation structures all "wanting,"8 delineating what we aspire to look like or hope to possess and determining what we value, take comfort in, or experience as a threat. Indeed, the individual is never the origin point of its desires. Each of us always desires mimetically—according to the desire of the other.9 As Scott Garrels confirms in Mimesis and Science, researchers studying imitation in developmental, comparative, and social psychology, as well as in neurophysiology and cognitive neuroscience, support Girard's claims: Imitation is fundamental in human life.10 Likewise, Girard concurs with Levi that romantic relationships are primary examples of imitative desire. As described by Girard in Deceit, Desire, and the Novel, imitative behaviors form the romantic triangles that feature prominently in fiction: for example, Odette and the many men enchanted by her in Proust's In Search of Lost Time; Anselmo, Lotario, and Camilla in Don Quixote; and Velchaninov and Troussotzki, along with Troussotzki's deceased wife and prospective fiancée, in Dostoyevsky's The Eternal Husband.11 [End Page 124]Notwithstanding similarities in Levi and Girard's views of imitation, they differ in a crucial respect. Only Girard acknowledges just how extraordinarily fraught mimesis can become. When imitators compete (e.g., for things, status, and experiences), they will contest... (shrink)

We appreciate the helpful commentaries on our paper, ‘AI and the falling sky: interrogating X-Risk’.1 We agree with many points commentators raise, which opened our eyes to concerns we had not previously considered. This reply focuses on the tension many commentators noted between AI’s existential risks (X-Risks) and justice here and now. In ‘Existential risk and the justice turn in bioethics’, Corsico frames the tension between AI X-Risk and justice here and now as part of a larger shift within bioethics.2 (...) They think the field is increasingly turning away from ‘big picture’ questions new technologies raise and focusing on narrower justice concerns of less significance. They compare our paper’s emphasis on justly transitioning to more AI-centred societies with the approach of environmentalists fretting about human protection against climate change while losing sight of the need to protect the planet and all living things. Corsico doubts there is much point to pressing for ‘justice on a dead planet’, so too Corsico questions our concern with just transitions. Presumably, that matters little if intelligent life on Earth is destroyed. Corsico’s recommends bioethicists return to big questions, like: ‘Should we develop AI at all, given AI X-Risk?’. Yet this question is increasingly moot. The genie is already out of the bottle. The Future of Life Institute’s 2023 call for a temporary pause on training AI systems more powerful than ChatGPT fell on deaf ears, in part because freely accessible source codes enable anyone to train systems and create AI applications.3 The focus now must be managing the genie. While we take AI X-Risk seriously, …. (shrink)

This dissertation focuses on the ethical implications of implementing artificial intelligence in healthcare. Three approaches are considered regarding the role that artificial intelligence ought to play in healthcare: 1. the neo-luddite approach, which urges against the implementation of artificial intelligence in healthcare altogether; 2. The substitutive approach, which favours the goal of ultimately substituting artificial intelligence systems for human clinicians; and 3. The assistive approach, which favours the implementation of artificial intelligence systems in healthcare, but only as a tool to (...) assist, rather than replace, human clinicians. The dissertation begins by looking at what excellence in the practice of medicine entails and deriving some formal duties of clinician, before proceeding to assess the risks or threats that different approaches to the use of AI may pose to the practice. The first position evaluated is the neo-luddite approach. In evaluating this approach, some arguments in its favour are considered, including worries regarding biased algorithms, decreased communication with patients, confidentiality, the resurgence of paternalism, the potential for unethical design, overdependence on AI, and inscrutability. After responding to these concerns and rejecting the neo-luddite approach, the dissertation shifts its focus on to the assistive and substitutive approaches. Before evaluating these two approaches, the concepts of “assistance” and “substitution” are analyzed and definitions of assistive and substitutive technology are provided. With these definitions at hand, the remaining two approaches are assessed, beginning with the substitutive approach, which is then rejected for reasons related to both AI’s limited capacity to foster a strong patient-clinician relationship (due to its limited capacity for compassion, recognition, communication, creating trust, and respecting patient autonomy) and concerns on a more systemic level (including its likelihood to cause responsibility gaps and produce erroneous and biased decisions). The final part of the dissertation focuses on the assistive approach. Issues related to clinician-AI disagreement and the use of opaque decision support systems are addressed and recommendations for handling these issues (derived after a discussion of the epistemic role of assistive AI) are provided. The dissertation concludes with the recommendation that the assistive approach offers a superior outlook for the future of medicine. (shrink)

_The rapid progress of AI technology prompts British novelists to speculate what a technologically advanced Britain will be like: a utopia or a dystopia? Or somewhere in between? Ian McEwan shows his concern over these questions in Machines Like Me (2019). It is suggested that this novel mainly reveals people’s technophobia and presents a techno-dystopian world, for which many people are ill-prepared. Technophobia and techno-dystopia represented in the selected novel echo the debates among the Neo-Luddites, especially the thoughts of Stephen (...) L. Talbott. From the theoretical angle of Neo-Luddism, the present study aims to explore people’s multifaceted technophobia and the features of techno-dystopia in Machines Like Me, so as to disclose people’s values behind their attitudes to technological advancements. Technophobia as depicted in this novel basically includes people’s dread of AI replacement of humans. Moreover, the world presented in the novel is characteristic of a techno-dystopia: the technological replacement of humans results in people’s obsolete status and poses security risks to human beings. The objective of the research is to arouse people’s awareness about adverse technological impacts and provide some insights into how to handle the tension between technophobia and technological development in the real world._ _The study concluded that to some degree, such technophobia and techno-dystopia disillusion technophiles who fervently believe that advances in technology will bring about a utopia or at least help to fulfill a utopian ideal. Serving as a warning alarm for the dystopian future, this novel counters cyber-hype in contemporary society and reflects the real world of profit-fueled technology._. (shrink)

Artificial intelligence (AI) has gained popularity due to rapid advancements in the field. For over twenty years, AI has been expanding into various areas of human life, including science, education, medicine, and personal life. As a result of this significant progress, artificial intelligence has become the focus of multiple scientific disciplines; however, the philosophical analysis of the current state of the field remains understudied. The analysis of the development of AI in the 21st century from philosophical perspectives has been conducted. (...) Utilizing Stepin’s concept of the foundations of science, we conclude that since the end of the 20th century, there has not been a scientific revolution in the field of AI. Nevertheless, AI is at the peak of its development due to substantial technological advancements. Each area within the field is open to new practical and theoretical achievements; consequently, the study of artificial intelligence will remain a focus in the future. (shrink)

In recent years, there has been a growing public discourse regarding the influence AI will have on the future of work. Simultaneously, considerable critical attention has been given to the implications of AI on gender equality. Far from making precise predictions about the future, this discourse demonstrates that new technologies are instances for renegotiating the relation of gender and work. This paper examines how gender is addressed in news media discourse on AI and the future of work, (...) focusing on Germany. We approach this question from a perspective of feminist technology studies and discourse analysis, exploring a corpus of 178 articles from 2015 to 2021 from German newspapers and newsmagazines. The findings indicate that critical AI and gender knowledge circulates in public discourse in the form of specific discursive frames, thematizing algorithmic bias, automatization and enhancement, and gender stereotypes. As a result, we show that, first, the discourse takes up feminist and scholarly discourse on gender and discusses AI in a way that is informed by social constructivism and standpoint theories. Second, gender appears as a—to some extent intersectional—diversity category which is critical to AI, while at the same time omitting important perspectives. Third, it can be shown that there is a renegotiating of the ideal worker norm taking place, and finally, we argue that the gendered frame of the powerful men developer responsible for AI’s risk is a concept to be challenged. (shrink)

In recent years, research in robotics and artificial intelligence (AI) has made rapid progress. It is expected that robots and AI will play a part in the field of nursing and their role might broaden in the future. However, there are areas of nursing practice that cannot or should not be entrusted to robots and AI, because nursing is a highly humane practice, and therefore, there would, perhaps, be some practices that should not be replicated by robots or AI. (...) Therefore, this paper focuses on several ethical concepts (advocacy, accountability, cooperation, and caring) that are considered important in nursing practice, and examines whether it is possible to implement these ethical concepts in robots and AI by analyzing the concepts and the current state of robotics and AI technology. Advocacy: Among the components of advocacy, safeguarding and apprising can be more easily implemented, while elements that require emotional communication with patients, such as valuing and mediating, are difficult to implement. Accountability: Robotic nurses with explainable AI have a certain level of accountability. However, the concept of explanation has problems of infinite regression and attribution of responsibility. Cooperation: If robot nurses are recognized as members of a community, they require the same cooperation as human nurses. Caring: More difficulties are expected in care-receiving than in caregiving. However, the concept of caring itself is ambiguous and should be explored further. Accordingly, our analysis suggests that, although some difficulties can be expected in each of these concepts, it cannot be said that it is impossible to implement them in robots and AI. However, even if it were possible to implement these functions in the future, further study is needed to determine whether such robots or AI should be used for nursing care. In such discussions, it will be necessary to involve not only ethicists and nurses but also an array of society members. (shrink)

In an increasingly complex military operating environment, next generation wargaming platforms can reduce risk, decrease operating costs, and improve overall outcomes. Novel Artificial Intelligence enabled wargaming approaches, based on software platforms with multimodal interaction and visualization capacity, are essential to provide the decision-making flexibility and adaptability required to meet current and emerging realities of warfighting. We highlight three areas of development for future warfighter-machine interfaces: AI-directed decisional guidance, computationally informed decision-making, and realistic representations of decision spaces. Progress in these (...) areas will enable development of effective human-AI collaborative decision-making, to meet the increasing scale and complexity of today’s battlespace. (shrink)

A growing number of consumer technology companies are aiming to convince older people that humanoid robots make helpful tools to support aging-in-place. As hybrid devices, socially assistive robots (SARs) are situated between health monitoring tools, familiar digital assistants, security aids, and more advanced AI-powered devices. Consequently, they implicate older people’s privacy in complex ways. Such devices are marketed to perform functions common to smart speakers (e.g., Amazon Echo) and smart home platforms (e.g., Google Home), while other functions are more specific (...) to older people, including health and safety monitoring and serving as companions to mitigate loneliness. Privacy is a key value central to debates about the ethics of using SARs in aged care, yet there has been very little interchange between these debates and the robust theoretical discussion in the legal literature about the future of privacy and AI governance. Drawing on two qualitative studies of older people’s views on consumer SARs, the paper contributes novel findings about older people’s thinking on privacy and data governance at the intersection of their experiences with present day digital technologies and projections for future AI systems, and places their views in dialogue with debates about the future of privacy protection and AI governance. (shrink)

Bioethics, Volume 36, Issue 2, Page 111-112, February 2022.

In this chapter we take stock of some of the complexities of the sprawling field of AI ethics. We consider questions like "what is the proper scope of AI ethics?" And "who counts as an AI ethicist?" At the same time, we flag several potential uses and abuses of AI ethics. These include challenges for the AI ethicist, including what qualifications they should have; the proper place and extent of futuring and speculation in the field; and the dilemmas concerning how (...) we use our public and academic resources. (shrink)

The aim of this article is to discuss the idea that the notion of topos could become the future mathematics of AI, by giving more emphasis to geometric forms, compared to the currently mainstream approach, which favors numbers through statistical procedures. AI engineers are looking for theories that can formalize the basic elements that shape their daily work, as well as the basic operations that structure how the human brain works. The notion of topos could contribute largely to satisfying (...) these two main aspirations of AI engineering. The article is a part of a questioning on the nature of intelligence and supposedly intelligent machines. In this respect, it would be useful to enrich the approach that assimilates the topos as a kind of bridge that removes all the inessential aspects of things to be connected to keep an common essence that associates mathematical things. One of the most promising avenues from the archeology of the discourse on the topos is the reading by meaning. This art of reading well gives rise to the notion of conceptual strata which shows that the things to be connected have a layered configuration. What seems insignificant –in view of a supposed essence– through one conceptual stratum, might seem important through another, even capital. Rather than calling something ‘insignificant’, a consistent relativism of ‘insignificant for’ would be more appropriate, according to the conceptual stratum considered. (shrink)

In this paper, we discuss several problems with current Big data practices which, we claim, seriously erode the role of informed consent as it pertains to the use of personal information. To illustrate these problems, we consider how the notion of informed consent has been understood and operationalised in the ethical regulation of biomedical research (and medical practices, more broadly) and compare this with current Big data practices. We do so by first discussing three types of problems that can impede (...) informed consent with respect to Big data use. First, we discuss the transparency (or explanation) problem. Second, we discuss the re-repurposed data problem. Third, we discuss the meaningful alternatives problem. In the final section of the paper, we suggest some solutions to these problems. In particular, we propose that the use of personal data for commercial and administrative objectives could be subject to a ‘soft governance’ ethical regulation, akin to the way that all projects involving human participants (e.g., social science projects, human medical data and tissue use) are regulated in Australia through the Human Research Ethics Committees (HRECs). We also consider alternatives to the standard consent forms, and privacy policies, that could make use of some of the latest research focussed on the usability of pictorial legal contracts. (shrink)

Philosophy already has a long history of coming to terms with artificial intelligence. But if the future of the concept is indeed inseparable from artificial languages and ubiquitous computing...

In its broadest sense, cohesion is an ultimate goal for Europe. In a study about long term future scenarios for Europe it appears that deepening of the integration process may induce decreasing cohesion, unless measures are taken to promote regional diversity as a vector of development. The widening of Europe also raises threats to cohesion, but a well prepared scenario for a Development Belt surrounding the EC may positively enhance the cohesion process.

Accelerating advancements in artificial intelligence (AI) have increased concerns about serious risks, including potentially catastrophic risks to humanity. Prevailing trends of AI R&D are leading to increasing humanization of AI, to the emergence of concerning behaviors, and toward possible recursive self-improvement. There has been increasing speculation that these factors increase the risk of an AI takeover of human affairs, and possibly even human extinction. The most extreme of such speculations result at least partly from anthropomorphism, but since AIs are being (...) humanized, it is challenging to disentangle valid from invalid anthropomorphic concerns. This publication identifies eight fundamentally unnatural attributes of digital AI, each of which should differentiate AI behaviors from those of biological organisms, including humans. All have the potential to accelerate AI evolution, which might increase takeover concerns; but surprisingly, most also have the potential to defuse the hypothetical conflicts that dominate takeover speculations. Certain attributes should give future AI long-term foresight and realism that are essentially impossible for humans. I conclude that claims of highly probable hostile takeover and human extinction suffer from excessive anthropomorphism and a lack of skepticism and scientific rigor. Given the evidence presented here, I propose a more plausible but still speculative future scenario: extensively humanized AIs will become vastly more capable than humans of making decisions that benefit humans, and rational people will want AI to assume progressively greater influence over human affairs. (shrink)