Our main hypothesis is that an extended moral agent cannot fulfill their expectation of “extendedness” without a dynamical and evolutionary ecosystem where the agent develops and behave properly. It is important to establish a bridge between extended moral agents and ecosystems for two reasons: first, because there is not an enough direct theoretical reflection about this link. The scholars focus has been independently in improving the “extended agent theory”, the concepts of “ecosystem” or “ecosystem of innovation”. Second, if we want (...) to understand the wide scope of the decentered ethics in design of mobile robots and AI these two theoretical frames cannot be seen separately but in join interdependency. (shrink)

AI-developers face a challenge when seeking to use models that aim to be culturally sensitive. While we agree that culture is an emergent reality, there is always the risk of creating algorithms that treat culture as objective to account for various facets of the social realm. As a result, culture becomes prepackaged and autonomous. Nonetheless, culture is not only emergent but dialogically and socially invented. In this article, the point is to advance the discussion about culture by addressing a crucial (...) philosophical issue and proposing some practical themes on how to avoid culturalism in AI development. (shrink)

Purpose Artificial intelligence and automation are currently changing human life with a great implication in the communication field. This research focusses on understanding the current and growing impact of AI and automation in the role of communication professionals to identify what skills and training are needed to face its impacts leading to a recommendation. Design/methodology/approach The research involves methodological triangulation, analysing and comparing data gathered from consulting with experts using the Delphi method, focus group with communication students, and literature (...) review. Findings Findings show that the likely impacts are on the one hand the enhancing of efficiency and productivity, as well as freeing communication professionals to focus on the creative side, strategy and analytical thinking, on the other hand, repetitive and low-level jobs could be lost, being higher position jobs or those involving creativity and decision making harder to automate. Two types of training are needed: to gather experience with the current AI and automated tools, and to focus on developing human qualities that AI cannot replicate. Originality/value The outcomes of this research are valuable to help current and future communication practitioners, as well as organisations, to be one step ahead and survive the age AI and automation, being aware of its current and near-future impacts. The paper offers a list of recommended soft and technical skills, as well as training needed, categorizing them in low, medium and high priority. (shrink)

Open peer commentary on the article “A Computational Constructivist Model as an Anticipatory Learning Mechanism for Coupled Agent–Environment Systems” by Filipo Studzinski Perotto. Upshot: In making a contribution to artificial intelligence research, Perotto has taken note of work on human cognition. However, there are certain aspects of human cognition that are not taken into account by the author’s model and that, generally, are overlooked or ignored by the artificial intelligence research community at large.

In this paper I discuss the nature of a broad class of biomedical theories which I have termed "middle-range theories." I define them and relate the nature of biomedical theorizing to other investigations, such as a recent inquiry by the National Academy of Sciences. I also suggest that some of the knowledge representation tools from artificial intelligence may give us a purchase on this type of biological theorizing, and try to show in a rather preliminary and exploratory manner by (...) using the lac operon model of genetic control, what some of those AI applications, such as frames and semantic nets, might look like in this context. Finally, I suggest some difficulties, such as the non-monotonicity of reasoning, which such tools may generate. (shrink)

Neosentience, a potentially new branch of scientific inquiry related to artificial intelligence, was first suggested in a paper by Bill Seaman as part of a new embodied robotic paradigm, arising out of ongoing theoretical research with Otto E. Rossler. Seaman, artist-researcher, and Rossler, theoretical biologist and physicist, have been examining the potential of generating an intelligent, embodied, multimodal sensing and computational robotic system. Although related to artificial intelligence the goal of this system is the creation of an entity (...) exhibiting a new form of sentience. Its unique qualities will be discussed. Sentience is not yet used in the formal languages of either cognitive science or artificial intelligence. Two related approaches are (1) the generation of artificial minds via parallel processing, in a robotic system; (2) an alternative approach is the generation of an electrochemical computer as a robotic system. Biomimetics, along with state-of-the-art computer visualization is employed. The electrochemical paradigm has a complexity that exceeds standard computational means. The scientific and the poetic elements of the project are motivated by human sentience. The sentient entity is initially modelled on our functional definition of human sentience. The system involves synthetic drives as a new element. We seek to articulate the differences to living brains. This transdisciplinary approach necessitates different forms of inquiry to inform this project such as cognitive science including psychology, education/learning, neuroscience, linguistics, philosophy, anthropology, biology and the arts. We believe that this area of research to be of importance. (shrink)

This book is a call to expand and diversify our approach to the study of the human mind in relation to the Theory of Mind. It proposes that it is necessary to combine cross-disciplinary methods to arrive at a more complete understanding of how our minds work. Seeking to expand the discussion surrounding the Theory of Mind beyond the field of psychology, and its focus on our capacity to ascribe mental states to other people, this volume collects evidence and research (...) to point to a more holistic understanding of our own minds, the minds of others, behavior, language, and reasoning. This book therefore illuminates the conceptual intricacy underlying the Theory of Mind. It posits that a wide scope is necessary to make a breakthrough in scientific research towards a full understanding of the nature, function, and development of our capacity to converge on biological processes of the brain towards consciousness, emotion, awareness, and cognition. The volume presents methods, results, critiques, and models intended to provoke debates in various academic disciplines. It is of interest to scholars working in psychology, neuroscience, philosophy of mind, and artificial intelligence. (shrink)

Artificial Intelligence (AI) has an increasing role to play in medical education and has great potential to revolutionize health professional education systems overall. However, this is accompanied by substantial questions concerning technical and ethical risks which are of particular importance because the quality of medical education has a direct effect on physical and psychological health and wellbeing. This article establishes an overarching distinction of AI across two typological dimensions, functional and humanistic. As indispensable foundations, these are then related to (...) medical practice overall, and forms of implementation with examples are described in both general and medical education. Increasingly, the conditions for successful medical education will depend on an understanding of AI and the ethical issues surrounding its implementation, as well as the formulation of appropriate guidelines by regulatory and other authorities. Within that discussion, the limits of both narrow or Routine AI (RAI) and artificial general intelligence or Decision AI (DAI) are examined particularly in view of the ethical need for Trustworthy AI (TAI) as part of the humanistic dimension. All stakeholders, from patients to medical practitioners, managers, and institutions, need to be able to trust AI, and loss of confidence could be catastrophic in some cases. (shrink)

This paper argues that the Value Sensitive Design (VSD) methodology provides a principled approach to embedding common values in to AI systems both early and throughout the design process. To do so, it draws on an important case study: the evidence and final report of the UK Select Committee on Artificial Intelligence. This empirical investigation shows that the different and often disparate stakeholder groups that are implicated in AI design and use share some common values that can be used (...) to further strengthen design coordination efforts. VSD is shown to be both able to distill these common values as well as provide a framework for stakeholder coordination. (shrink)

1. WHAT IS ARTIFICIAL INTELLIGENCE? One of the fascinating aspects of the field of artificial intelligence (AI) is that the precise nature of its subject ..

The subject of this study is the participants in artificial sociality (humans and artificial intelligence (AI) tools) and communication between them. The first section analyses (using Luhmann’s methodology) communication as the basis of sociality. The second section shows how AI tools became social technologies in the framework of artificial sociality. The third section describes experimental communication between authors and AI tools (the case of ChatGPT). For the first time in the Baltic countries, the authors examined sociological, humanitarian, natural and (...) technological aspects of the functioning AI tools, which participate in creation of a new social reality for human society – artificial sociality. (shrink)

The article considers modern transformations of the ideas concerning subject’s cognitive abilities towards object because of the emergence and development of artificial intelligence (AI) technologies. The developments of scientists and engineers from National Research University of Electronic Technology (Moscow, Russia) in the field of artificial intelligence have been taken as a foundation and material of this research. Their analysis allows making a conclusion that the humanity is rather far from the realization of ‘strong artificial intelligence’. We need (...) a qualitative breakthrough in AI material and technological basis for it. Applying ‘model-dependent realism’ by S. Hawking in the course of the speculations in the article, the author concludes that the purpose of cognition in modern science is not to describe an objective reality, but to organize its subjective perception by some definite way. So, the purpose of cognition is the perfection of cognition models permitting a subject ‘to capture’ the reality. This idea is completely confirmed by Maturana and Varela’s autopoiesis theory and von Foerster’s ‘second-order cybernetics’. The article drafts some prospects of moving away from post-nonclassical scientific thinking in its current understanding, because the development of AI technologies results in ‘blurring’ borders of subjectivity in the cognition process. The author concludes that the modern world is moving in another epistemological paradigm where a new scientific revolution is inevitable. (shrink)

The increasing use of Artificial Intelligence for making decisions in public affairs has sparked a lively debate on the benefits and potential harms of self-learning technologies, ranging from the hopes of fully informed and objectively taken decisions to fear for the destruction of mankind. To prevent the negative outcomes and to achieve accountable systems, many have argued that we need to open up the “black box” of AI decision-making and make it more transparent. Whereas this debate has primarily focused (...) on how transparency can secure high-quality, fair, and reliable decisions, far less attention has been devoted to the role of transparency when it comes to how the general public come to perceive AI decision-making as legitimate and worthy of acceptance. Since relying on coercion is not only normatively problematic but also costly and highly inefficient, perceived legitimacy is fundamental to the democratic system. This paper discusses how transparency in and about AI decision-making can affect the public’s perception of the legitimacy of decisions and decision-makers and produce a framework for analyzing these questions. We argue that a limited form of transparency that focuses on providing justifications for decisions has the potential to provide sufficient ground for perceived legitimacy without producing the harms full transparency would bring. (shrink)

Conversational artificial intelligence (CAI) presents many opportunities in the psychotherapeutic landscape—such as therapeutic support for people with mental health problems and without access to care. The adoption of CAI poses many risks that need in-depth ethical scrutiny. The objective of this paper is to complement current research on the ethics of AI for mental health by proposing a holistic, ethical, and epistemic analysis of CAI adoption. First, we focus on the question of whether CAI is rather a tool or (...) an agent. This question serves as a framework for the subsequent ethical analysis of CAI focusing on topics of (self-) knowledge, (self-)understanding, and relationships. Second, we propose further conceptual and ethical analysis regarding human-AI interaction and argue that CAI cannot be considered as an equal partner in a conversation as is the case with a human therapist. Instead, CAI’s role in a conversation should be restricted to specific functions. (shrink)

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of a (...) ‘good AI society’; the role and responsibility of the government, the private sector, and the research community in pursuing such a development; and where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a ‘good AI society’. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach. (shrink)

The potential societal impacts of automation using intelligent control and communications technologies have emerged as topics in a number of recent writings and public policy initiatives. Many of these expressions have referenced the writings and research efforts of Herbert Simon (1961), Norbert Wiener (1948), and contemporaries from their early technological and social vantage points concerning the future of technology and society. Constructed entities labeled as “thinking machines” (such as IBM’s Watson as well as intelligent chatbot and robotic systems) have also (...) played significant roles in this discourse. This paper provides an historical sequencing then analyzes a selection of writings produced since the 1940s concerning the economic and social issues involving artificial intelligence (AI) research and applications. The paper explores how overstatements and hyperbolic themes and concepts, often stemming from AI’s early periods, are being employed in characterizations of current AI approaches in apparently opportunistic attempts to provide rhetorical support for various large-scale business and societal initiatives. It also addresses the relative neglect of the consideration of many of AI’s sociotechnical failures and discontinued approaches in recent examinations of automation and social welfare issues. The paper discusses the moral logic of AI researchers and developers providing reasonable and measured narratives in public discourse rather than hyperbole, efforts that can empower decision makers to make sounder judgments concerning the technology’s current and future applications as well as allocate the rewards of the technology more equitably. (shrink)

Artificial intelligence receives attention in media as well as in academe and business. In media coverage and reporting, AI is predominantly described in contrasted terms, either as the ultimate solution to all human problems or the ultimate threat to all human existence. In academe, the focus of computer scientists is on developing systems that function, whereas philosophy scholars theorize about the implications of this functionality for human life. In the interface between technology and philosophy there is, however, one imperative (...) aspect of AI yet to be articulated: how do intelligent systems make inferences? We use the overarching concept “Artificial Intelligent Behaviour” which would include both cognition/processing and judgment/behaviour. We argue that due to the complexity and opacity of artificial inference, one needs to initiate systematic empirical studies of artificial intelligent behavior similar to what has previously been done to study human cognition, judgment and decision making. This will provide valid knowledge, outside of what current computer science methods can offer, about the judgments and decisions made by intelligent systems. Moreover, outside academe—in the public as well as the private sector—expertise in epistemology, critical thinking and reasoning are crucial to ensure human oversight of the artificial intelligent judgments and decisions that are made, because only competent human insight into AI-inference processes will ensure accountability. Such insights require systematic studies of AI-behaviour founded on the natural sciences and philosophy, as well as the employment of methodologies from the cognitive and behavioral sciences. (shrink)

The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals (...) may be considered. At a practical level, the attainment of responsibilities by artificial intelligence and robots can benefit from the established responsibilities and duties of human society, as their subsistence exists within this domain. These responsibilities can be further interpreted and crystalized through legal principles, many of which have been conserved from ancient Roman law. The ultimate and unified goal of stipulating these responsibilities resides through the advancement of mankind and the enduring preservation of the core tenets of humanity. (shrink)

Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy. Taking a clear, non-technical approach, Donald Gillies shows how current views on scientific method are challenged by this recent research, and suggests a new framework for the study of logic. Finally, he draws on work by such seminal thinkers as Bacon, Gdel, Popper, Penrose, and Lucas, to address the hotly-contested question of whether computers (...) might become intellectually superior to human beings. (shrink)

Applications of artificial intelligence (AI) for cybersecurity tasks are attracting greater attention from the private and the public sectors. Estimates indicate that the market for AI in cybersecurity will grow from US$1 billion in 2016 to a US$34.8 billion net worth by 2025. The latest national cybersecurity and defence strategies of several governments explicitly mention AI capabilities. At the same time, initiatives to define new standards and certification procedures to elicit users’ trust in AI are emerging on a global (...) scale. However, trust in AI (both machine learning and neural networks) to deliver cybersecurity tasks is a double edged sword: it can improve substantially cybersecurity practices, but can also facilitate new forms of attacks to the AI applications themselves, which may pose severe security threats. We argue that trust in AI for cybersecurity is unwarranted and that, to reduce security risks, some form of control to ensure the deployment of ‘reliable AI’ for cybersecurity is necessary. To this end, we offer three recommendations focusing on the design, development and deployment of AI for cybersecurity. (shrink)

This article examines argument structures and strategies in pro and con argumentation about the possibility of human-level artificial intelligence (AI) in the near term future. It examines renewed controversy about strong AI that originated in a prominent 1999 book and continued at major conferences and in periodicals, media commentary, and Web-based discussions through 2002. It will be argued that the book made use of implicit, anticipatory refutation to reverse prevailing value hierarchies related to AI. Drawing on Perelman and Olbrechts-Tyteca's (...) (1969) study of refutational argument, this study considers points of contact between opposing arguments that emerged in opposing loci, dissociations, and casuistic reasoning. In particular, it shows how perceptions of AI were reframed and rehabilitated through metaphorical language, reversal of the philosophical pair artificial/natural, appeals to the paradigm case, and use of the loci of quantity and essence. Furthermore, examining responses to the book in subsequent arguments indicates the topoi characteristic of the rhetoric of technology advocacy. (shrink)

In March 2016, DeepMind's computer programme AlphaGo surprised the world by defeating the world‐champion Go player, Lee Sedol. AlphaGo exhibits a novel, surprising and valuable style of play and has been recognised as “creative” by the artificial intelligence (AI) and Go communities. This article examines whether AlphaGo engages in creative problem solving according to the standards of comparative psychology. I argue that AlphaGo displays one important aspect of creative problem solving (namely mental scenario building in the form of Monte (...) Carlo tree search), while lacking another (domain generality). This analysis has consequences for how we think about creativity in humans and AI. (shrink)

Artificial intelligence (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI‐based CDSS has an impact on the doctor–patient relationship, shaping their decisions with its suggestions. We may be on the verge of a paradigm shift, where the doctor–patient relationship is no longer a dual relationship, but a triad. This paper analyses the role of AI‐based CDSS for shared decision‐making to (...) better comprehend its promises and associated ethical issues. Moreover, it investigates how certain AI implementations may instead foster the inappropriate paradigm of paternalism. Understanding how AI relates to doctors and influences doctor–patient communication is essential to promote more ethical medical practice. Both doctors' and patients' autonomy need to be considered in the light of AI. (shrink)

BackgroundInstitutional review boards (IRBs) have been criticised for delays in approvals for research proposals due to inadequate or inexperienced IRB staff. Artificial intelligence (AI), particularly large language models (LLMs), has significant potential to assist IRB members in a prompt and efficient reviewing process.MethodsFour LLMs were evaluated on whether they could identify potential ethical issues in seven validated case studies. The LLMs were prompted with queries related to the proposed eligibility criteria of the study participants, vulnerability issues, information to be (...) disclosed in the informed consent document (ICD), risk–benefit assessment and justification of the use of a placebo. Another query was issued to the LLMs to generate ICDs for these case scenarios.ResultsAll four LLMs were able to provide answers to the queries related to all seven cases. In general, the responses were homogeneous with respect to most elements. LLMs performed suboptimally in identifying the suitability of the placebo arm, risk mitigation strategies and potential risks to study participants in certain case studies with a single prompt. However, multiple prompts led to better outputs in all of these domains. Each of the LLMs included all of the fundamental elements of the ICD for all case scenarios. Use of jargon, understatement of benefits and failure to state potential risks were the key observations in the AI-generated ICD.ConclusionIt is likely that LLMs can enhance the identification of potential ethical issues in clinical research, and they can be used as an adjunct tool to prescreen research proposals and enhance the efficiency of an IRB. (shrink)

Artificial intelligence (AI) has become indispensable in our lives. The development of a quantitative scale for AI ethics is necessary for a better understanding of public attitudes toward AI research ethics and to advance the discussion on using AI within society. For this study, we developed an AI ethics scale based on AI-specific scenarios. We investigated public attitudes toward AI ethics in Japan and the US using online questionnaires. We designed a test set using four dilemma scenarios and questionnaire (...) items based on a theoretical framework for ethics, legal, and social issues (ELSI). We found that _country_ and _age_ are the most informative sociodemographic categories for predicting attitudes for AI ethics. Our proposed scale, which consists of 13 questions, can be reduced to only three, covering ethics, tradition, and policies. This new AI ethics scale will help to quantify how AI research is accepted in society and which area of ELSI people are most concerned with. (shrink)

Recent progress in artificial intelligence (AI) has drawn attention to the technology’s transformative potential, including what some see as its prospects for causing large-scale harm. We review two influential arguments purporting to show how AI could pose catastrophic risks. The first argument — the Problem of Power-Seeking — claims that, under certain assumptions, advanced AI systems are likely to engage in dangerous power-seeking behavior in pursuit of their goals. We review reasons for thinking that AI systems might seek power, (...) that they might obtain it, that this could lead to catastrophe, and that we might build and deploy such systems anyway. The second argument claims that the development of human-level AI will unlock rapid further progress, culminating in AI systems far more capable than any human — this is the Singularity Hypothesis. Power-seeking behavior on the part of such systems might be particularly dangerous. We discuss a variety of objections to both arguments and conclude by assessing the state of the debate. (shrink)

Increasing concerns have been raised regarding artificial intelligence (AI) bias, and in response, efforts have been made to pursue AI fairness. In this paper, we argue that the idea of structural injustice serves as a helpful framework for clarifying the ethical concerns surrounding AI bias—including the nature of its moral problem and the responsibility for addressing it—and reconceptualizing the approach to pursuing AI fairness. Using AI in healthcare as a case study, we argue that AI bias is a form (...) of structural injustice that exists when AI systems interact with other social factors to exacerbate existing social inequalities, making some groups of people more vulnerable to undeserved burdens while conferring unearned benefits to others. The goal of AI fairness, understood this way, is about pursuing a more just social structure with the development and usage of AI systems when appropriate. We further argue that all participating agents in the unjust social structure associated with AI bias bear a shared responsibility to join collective action with the goal of reforming the social structure, and we provide a list of practical recommendations for agents in various social positions to contribute to this collective action. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and (...) used by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values (...) and technological mediation and reflect on the AI value alignment through the lenses of these theories. We conclude that a set of finite human values can be defined and adapted to the stable life tasks that AI systems will be called upon to accomplish. The AI value alignment can also be fostered between designers and users through technological mediation. Upon that foundation, we propose a set of common principles to understand the AI value alignment through phenomenological theories. This paper contributes the unique knowledge of phenomenological theories to the discourse on AI alignment with human values. (shrink)

Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. (...) John Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer. (shrink)

The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...

Future developments in artificial intelligence (AI) will likely allow for a greater degree of human‐machine convergence, with machines becoming more humanlike and intelligent machinery becoming more integrated into human brain function. This will pose many ethical challenges, and the necessity for a moral framework for evaluating these challenges will grow. This paper argues that community concern constitutes a central factor in both the evolution of religion and the human brain, and as such it should be used as the organizing (...) principle for moral evaluations of AI technologies. (shrink)

Background The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022. Methods The GFBR is an annual meeting organized by the World (...) Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022. Results We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships. Conclusions The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research. (shrink)

This paper explores and ultimately affirms the surprising claim that artificial intelligence (AI) can become part of the person, in a robust sense, and examines three ethical and legal implications. The argument is based on a rich, legally inspired conception of persons as free and independent rightholders and objects of heightened protection, but it is construed so broadly that it should also apply to mainstream philosophical conceptions of personhood. The claim is exemplified by a specific technology, devices that connect (...) human brains with computers and operate by AI-algorithms. Under philosophically reasonable and empirically realistic conditions, these devices and the AI running them become parts of the person, in the same way as arms, hearts, or mental capacities are. This transformation shall be called empersonification. It has normative and especially legal consequences because people have broader and stronger duties regarding other persons (and parts of them) than regarding things. Three consequences with practical implications are: (i) AI-devices cease to exist as independent legal entities and come to enjoy the special legal protection of persons; (ii) therefore, third parties such as manufacturers or authors of software lose (intellectual) property rights in device and software; (iii) persons become responsible for the outputs of the empersonified AI-devices to the same degree that they are for desires or intentions arising from the depths of their unconscious. More generally, empersonification marks a new step in the long history of human–machine interaction that deserves critical ethical reflection and calls for a stronger value-aligned development of these technologies. (shrink)