As is known, there has been a significant increase in the use of AI technologies in various fields related to the work of both public and private sectors. Despite its importance in economic, health, security, and educational fields, the use of AI technologies has led to several ethical and legal risks. For example, there are risks of bias or discrimination when building AI systems, challenges related to privacy and data protection, including issues that arise from errors in health protocol procedures (...) and their impact on patient health. This paper aims to highlight a number of practical applications of bias or discrimination associated with the use of AI technologies, concluding with the importance of having clear ethical governance to address the emerging risks of using AI applications. (shrink)

This is a draft of the written version of comments on a paper by David Cole, presented orally at the American Philosophical Association Central Division meeting in New Orleans, 27 April 1990. Following the written comments are 2 appendices: One contains a letter to Cole updating these comments. The other is the handout from the oral presentation.

This article deals with the links between the enaction paradigm and artificial intelligence. Enaction is considered a metaphor for artificial intelligence, as a number of the notions which it deals with are deemed incompatible with the phenomenal field of the virtual. After explaining this stance, we shall review previous works regarding this issue in terms of artificial life and robotics. We shall focus on the lack of recognition of co-evolution at the heart of these approaches. (...) We propose to explicitly integrate the evolution of the environment into our approach in order to refine the ontogenesis of the artificial system, and to compare it with the enaction paradigm. The growing complexity of the ontogenetic mechanisms to be activated can therefore be compensated by an interactive guidance system emanating from the environment. This proposition does not however, resolve that of the relevance of the meaning created by the machine (sense-making). Such reflections lead us to integrate human interaction into this environment in order to construct relevant meaning in terms of participative artificial intelligence. This raises a number of questions with regards to setting up an enactive interaction. The article concludes by exploring a number of issues, thereby enabling us to associate current approaches with the principles of morphogenesis, guidance, the phenomenology of interactions and the use of minimal enactive interfaces in setting up experiments which will deal with the problem of artificial intelligence in a variety of enaction-based ways. (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 Neural Networks have reached “grandmaster” and even “super-human” performance across a variety of games, from those involving perfect information, such as Go, to those involving imperfect information, such as “Starcraft”. Such technological developments from artificial intelligence (AI) labs have ushered concomitant applications across the world of business, where an “AI” brand-tag is quickly becoming ubiquitous. A corollary of such widespread commercial deployment is that when AI gets things wrong—an autonomous vehicle crashes, a chatbot exhibits “racist” behavior, (...) automated credit-scoring processes “discriminate” on gender, etc.—there are often significant financial, legal, and brand consequences, and the incident becomes major news. As Judea Pearl sees it, the underlying reason for such mistakes is that “... all the impressive achievements of deep learning amount to just curve fitting.” The key, as Pearl suggests, is to replace “reasoning by association” with “causal reasoning” —the ability to infer causes from observed phenomena. It is a point that was echoed by Gary Marcus and Ernest Davis in a recent piece for theNew York Times: “we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets—often using an approach known as ‘Deep Learning’—and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space, and causality.” In this paper, foregrounding what in 1949 Gilbert Ryle termed “a category mistake”, I will offer an alternative explanation for AI errors; it is not so much that AI machinery cannot “grasp” causality, but that AI machinery (qua computation) cannot understand anything at all. (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)

The tendency to idealise artificial intelligence as independent from human manipulators, combined with the growing ontological entanglement of humans and digital machines, has created an “anthrobotic” horizon, in which data analytics, statistics and probabilities throw our agential power into question. How can we avoid the consequences of a reified definition of intelligence as universal operation becoming imposed upon our destinies? It is here argued that the fantasised autonomy of automated intelligence presents a contradistinctive opportunity for philosophical (...) consciousness to understand itself anew as holistic and co-creative, beyond the recent “analytic” moment of the history of philosophy. Here we introduce the concept of “crealectic intelligence”, a meta-analytic and meta-dialectic aspect of consciousness. Intelligent behaviour may consist in distinguishing discrete familiar parts or reproducible functions in the midst of noise via an analytic process of segmentation; intelligence may also manifest itself in the constitution of larger wholes and dynamic unities through a dialectic process of association or assemblage. But, by contrast, crealectic intelligence co-creates realities in the image of an ideal or truth, taking into account the desiring agent imbued with a sense of possibility, in a relationship not only with the Real but also with the creative sublime or “Creal”. (shrink)

The article describes the possibilities of using and modifying existing machine learning technologies in the field of natural language processing for the purpose of designing a system for automatically generating control and test tasks (CTT). The reason for such studies was the limitations in generating theminimumrequired amount ofCTtomaintain student engagement in game-based learning formats, such as quizzes, and others. These limitations are associated with the lack of time resources among training professionals for manual generation of tests. The article discusses the (...) applied research of the Large Language Model (LLM) and Generative pre-trained transformer (GPT) technologies for the development of a system for automatic generation of tests for the purpose of its implementation in the BoxBattle gamified learning platform. The result of such applied research can be a system for automatic generation of tests, which will reduce the time for developing tests. As a result, this will allow teachers to free up time to implement a personalized approach to teaching and develop students’soft skills. (shrink)

It may seem strange to associate the name of Jan Patočka with artificial intelligence. Neither a mathematician nor a logician, the phenomenology he espoused, with its emphasis on lived experience, seems worlds apart from the formalism associated with the discipline. Yet, as I hope to show, the radicality and depth of Patočka’s thought is such that it casts a wide net. The reform of metaphysics that Patočka proposed in his asubjective phenomenology also affects artificial intelligence. It (...) shows that what philosophers take as its most difficult, yet primary problem may well be the result of a category mistake. (shrink)

This paper investigates the claim that artificial Intelligence Systems cannot be held morally responsible because they do not have an ability for agential self-awareness e.g. they cannot be aware that they are the agents of an action. The main suggestion is that if agential self-awareness and related first person representations presuppose an awareness of a self, the possibility of responsible artificial intelligence systems cannot be evaluated independently of research conducted on the nature of the self. Focusing (...) on a specific account of the self from the phenomenological tradition, this paper suggests that a minimal necessary condition that artificial intelligence systems must satisfy so that they have a capability for self-awareness, is having a minimal self defined as ‘a sense of ownership’. As this sense of ownership is usually associated with having a living body, one suggestion is that artificial intelligence systems must have similar living bodies so they can have a sense of self. Discussing cases of robotic animals as examples of the possibility of artificial intelligence systems having a sense of self, the paper concludes that the possibility of artificial intelligence systems having a ‘sense of ownership’ or a sense of self may be a necessary condition for having responsibility. (shrink)

The ever increasing use of generative artificial intelligence raises significant questions about authorship and related issues such as credit and accountability. In this paper, I consider whether works produced by means of users inputting natural language prompts into Generative Adversarial Networks are works of authorship. I argue that they are not. This is not due to concerns about randomness or machine-assistance compromising human labor or intellectual vision, but instead due to the syntactical and compositional limitations of existing AI (...) systems in handling natural language prompts. This, I argue, gives rise to ‘authorship gaps’. (shrink)

The purpose of this book, originally published in 1987, was to contribute to the advance of artificial intelligence by clarifying and removing the major sources of philosophical confusion at the time which continued to preoccupy scientists and thereby impede research. Unlike the vast majority of philosophical critiques of AI, however, each of the authors in this volume has made a serious attempt to come to terms with the scientific theories that have been developed, rather than attacking superficial 'straw (...) men' which bear scant resemblance to the complex theories that have been developed. For each is convinced that the philosopher's responsibility is to contribute from his own special intellectual point of view to the progress of such an important field, rather than sitting in lofty judgement dismissing the efforts of their scientific peers. The aim of this book is thus to correct some of the common misunderstandings of its subject. The technical term Artificial Intelligence has created considerable unnecessary confusion because of the ordinary meanings associated with it, and for that very reason, the term is endlessly misused and abused. The essays collected here all aim to expound the true nature of AI, and to remove the ill-conceived philosophical discussions which seek answers to the wrong questions in the wrong ways. Philosophical discussions and decisions about the proper use of AI need to be based on a proper understanding of the manner in which AI-scientists achieve their results; in particular, in their dependence on the initial planning input of human beings. The collection combines the Anglo-Saxon school of analytical philosophy with scientific and psychological methods of investigation. The distinguished authors in this volume represent a cross-section of philosophers, psychologists, and computer scientists from all over the world. The result is a fascinating study in the nature and future of AI, written in a style which is certain to appeal and inform laymen and specialists alike. has created considerable unnecessary confusion because of the ordinary meanings associated with it, and for that very reason, the term is endlessly misused and abused. The essays collected here all aim to expound the true nature of AI, and to remove the ill-conceived philosophical discussions which seek answers to the wrong questions in the wrong ways. Philosophical discussions and decisions about the proper use of AI need to be based on a proper understanding of the manner in which AI-scientists achieve their results; in particular, in their dependence on the initial planning input of human beings. The collection combines the Anglo-Saxon school of analytical philosophy with scientific and psychological methods of investigation. The distinguished authors in this volume represent a cross-section of philosophers, psychologists, and computer scientists from all over the world. The result is a fascinating study in the nature and future of AI, written in a style which is certain to appeal and inform laymen and specialists alike. inform laymen and specialists alike. (shrink)

본 논문의 목적은 현재의 인공지능(artificial intelligence, 이하 AI) 윤리 논의에서 결여되어 있는 AI 개발자 윤리의 중요성과 필요성을 부각하고, AI 개발자 윤리로 덕성(virtue)기반의 모델이 적합함을 보여 이를 제안하는 것이다. AI는 고정된 과학기술이 아니라 발전노정에 있는 동적이라는 특성과 인간과의 상호작용에서 AI를 만든 인간의 삶에 지대한 영향을 끼치는 재귀적 특성이 있는 과학기술이다. 이러한 AI의 특성으로 인해, AI가 초래할 리스크에 대응하려는 AI 윤리는 발전 과정에 따라 제시되어야 한다는 점에서 체계적이고, 실천을 도모하는 동기부여의 구조를 가져야 한다는 점에서 기존 도덕의 형식적 특징인 1인칭, 2인칭, (...) 3인칭 관점이 통합될 필요가 있다. 그런데 최근에 활발하게 제시된 많은 AI윤리 지침에 대한 메타 분석에 따르면, 현재의 지침으로서의 AI 윤리 논의들은 1인칭 관점의 동기부여가 없는 3인칭 관점에만 한정되어 실질적인 ‘윤리 실현’(ethics realizing)을 도모하기에 취약하다. AI 윤리 지침 자체가 추상적이고 모호할 뿐만 아니라, AI를 개발하는 사람들에게 아무런 영향력을 행사하지 못하는 ‘윤리 세탁’(ethics washing)에 불과하기 때문이다. 이러한 한계를 보완하기 위해서는 AI 개발자들이 AI 윤리를 내면화하여 규범적으로 실천하게 할 수 있게 하는 AI 개발자 윤리가 필요한데, 본 논문은 덕성 기반의 AI 개발자 윤리가 이러한 목적을 위해 효과적이라고 주장한다. 덕성 기반의 AI 개발자 모델은, 과학적 덕성 모델(scientific virtue model)이 그랬던 것처럼 AI 개발의 목적이 무엇인지, AI개발자들의 전문직 덕성(vocational virtue)이 무엇인지, 그리고 이러한 덕성을 함양하기 위한 효과적인 교육 방법은 무엇인지 등의 이론 연구와 AI 개발자들과의 소통을 토대로 하는 경험 연구의 결합을 통해 실천적 차원의 모델로 구체화될 수 있다. 본 논문에서 이론적으로 제안하는 덕성 기반의 AI 개발자 윤리가 추후 한국 사회의 경험 연구를 통해 실천적 차원의 모델로 구체화되어 AI가 초래하는 윤리적 문제들에 효과적으로 대응하면서 AI의 혜택이 풍성히 향유되는데 기여하기를 기대한다. (shrink)

Artificial Intelligence and Music Ecosystem highlights the opportunities and rewards associated with the application of AI in the creative arts. Featuring an array of voices, including interviews with Jacques Attali, Holly Herndon and Scott Cohen, this book offers interdisciplinary approaches to pressing ethical and technical questions associated with AI. Considering the perspectives of developers, students and artists, as well as the wider themes of law, ethics and philosophy, Artificial Intelligence and Music Ecosystem is an essential introduction (...) for anyone interested in the impact of AI on music, including those studying and working in the creative arts. (shrink)

Several technological developments, such as self-service technologies and artificial intelligence, are disrupting the retailing industry by changing consumption and purchase habits and the overall retail experience. Although AI represents extraordinary opportunities for businesses, companies must avoid the dangers and risks associated with the adoption of such systems. Integrating perspectives from emerging research on AI, morality of machines, and norm activation, we examine how individuals morally behave toward AI agents and self-service machines. Across three studies, we demonstrate that consumers’ (...) moral concerns and behaviors differ when interacting with technologies versus humans. We show that moral intention is less likely to emerge for AI checkout and self-checkout machines compared with human checkout. In addition, moral intention decreases as people consider the machine less humanlike. We further document that the decline in morality is caused by less guilt displayed toward new technologies. The non-human nature of the interaction evokes a decreased feeling of guilt and ultimately reduces moral behavior. These findings offer insights into how technological developments influence consumer behaviors and provide guidance for businesses and retailers in understanding moral intentions related to the different types of interactions in a shopping environment. (shrink)

This article examines the transformative role of Generative Artificial Intelligence (GAI) in education, exploring diverse disciplines such as engineering, medicine, programming, and information systems. GAI emerges as a revolutionary force, promising to fundamentally change educational practices. The PRISMA 2020 methodology (Page et al., 2021) was used to evaluate the relevant scientific literature. The systematic review identified research that applied specific criteria in the analysis of IAG in education. The selected papers covered a variety of disciplines, providing a comprehensive (...) view of the impact of IAG in education. The results show a diversity of approaches and institutional responses to IAG in education. From significant changes in teaching practices to the identification of specific opportunities in disciplines such as computer science and engineering, GAI stands out as a catalyst for transformation. The adaptation of tertiary education, the need for specific skills to work with GAI, and ethical responses emerge as key themes. It focuses on the need for a deeper and more consensual understanding of the role of GAI in education. Concrete research-supported opportunities are highlighted, but ethical limitations and concerns are also underscored. Collaboration, reflection, and adaptation to open educational practices are proposed as approaches to address the challenges and fully exploit the benefits of IAG in education. This comprehensive analysis contributes to understanding the current and future landscape of GAI in education, providing valuable guidelines for educators, institutions, and educational technology developers. (shrink)

Artificial intelligence, ethics, law: a view on the Italian and American debate (and on their differences) In the past ten years the scientific discourse on artificial intelligence (AI) has thrived. What are the challenges that AI poses to the law? If something goes wrong, who should be blamed? In the pursuit of answers to these questions, legal scholars – as the authors of the reviewed books – jumped on the AI bandwagon, joining philosophers, ethicists, computer (...) scientists.The essay highlights recurring traits of this discussion on AI and law. Its purpose is to present two paramount examples of the common versus civil law approach to solving conflicts, such as the one represented by the impact of AI technologies on our society. (shrink)

The increasing diffusion of novel digital and online sociotechnical systems for arational behavioral influence based on Artificial Intelligence (AI), such as social media, microtargeting advertising, and personalized search algorithms, has brought about new ways of engaging with users, collecting their data and potentially influencing their behavior. However, these technologies and techniques have also raised concerns about the potential for manipulation, as they offer unprecedented capabilities for targeting and influencing individuals on a large scale and in a more subtle, (...) automated and pervasive manner than ever before. This paper, provides a narrative review of the existing literature on manipulation, with a particular focus on the role of AI and associated digital technologies. Furthermore, it outlines an account of manipulation based of four key requirements: intentionality, asymmetry of outcome, non-transparency and violation of autonomy. I argue that while manipulation is not a new phenomenon, the pervasiveness, automaticity, and opacity of certain digital technologies may raise a new type of manipulation, called “digital manipulation”. I call “digital manipulation” any influence exerted through the use of digital technology that is intentionally designed to bypass reason and to produce an asymmetry of outcome between the data processor (or a third party that benefits thereof) and the data subject. Drawing on insights from psychology, sociology, and computer science, I identify key factors that can make manipulation more or less effective, and highlight the potential risks and benefits of these technologies for individuals and society. I conclude that manipulation through AI and associated digital technologies is not qualitatively different from manipulation through human–human interaction in the physical world. However, some functional characteristics make it potentially more likely of evading the subject’s cognitive defenses. This could increase the probability and severity of manipulation. Furthermore, it could violate some fundamental principles of freedom or entitlement related to a person’s brain and mind domain, hence called neurorights. To this end, an account of digital manipulation as a violation of the neuroright to cognitive liberty is presented. (shrink)

In their paper, “Conversational Artificial Intelligence in Psychotherapy: A New Therapeutic Tool or Agent?” Sedlakova and Trachsel (2023) claim that therapeutic insights and therapeutic changes are...

This paper reflects on the problem of endowing Artificial Intelligence with legal subjectivity, especially with regard to civil law. It is necessary to reject the myth that the criteria of legal subjectivity are sentience and reason. Arguing that AI may have potential legal subjectivity based on an analogy to animals or juristic persons suggests the existence of a single hierarchy or sequence of entities, organized according to their degree of similarity to human beings; also, that the place of (...) an entity in this hierarchy determines the scope of subjectivity attributed to it. Rather, it is participation or presence in social life, whatever the role, that is the true criterion of subjectivity. In addition, it is clear that even if AI is not currently a significant participant in social life, it will be in the nearest future. Despite the potential dangers associated with endowing AI with some kind of subjectivity, such a course is inescapable, and should be considered sooner rather than later. (shrink)

Trust and trustworthiness are central concepts in contemporary discussions about the ethics of and qualities associated with artificial intelligence (AI) and the relationships between people, organisations and AI. In this article we develop an interdisciplinary approach, using socio-technical software engineering and design anthropological approaches, to investigate how trust and trustworthiness concepts are articulated and performed by AI software practitioners. We examine how trust and trustworthiness are defined in relation to AI across these disciplines, and investigate how AI, trust (...) and trustworthiness are conceptualised and experienced through an ethnographic study of the work practices of nine practitioners in the software industry. We present key implications of our findings for the generation of trust and trustworthiness and for the training and education of future software practitioners. (shrink)

The article critically examines the capabilities and limitations of artificial intelligence (AI) technologies within the context of ongoing debates surrounding potential threats stemming from their advancement. The study scrutinizes and challenges key arguments positing the possibility of human subjugation by AI systems. The author undertakes a comparative analysis of natural and artificial intelligence, employing the psychological experiences of C.G. Jung as a case study. It is demonstrated that despite the remarkable achievements of contemporary neural networks in (...) information processing, they are fundamentally limited in their capacity for genuine comprehension and creative thought. The paper identifies three key innovations associated with AI development: the enhancement of users’ cognitive capabilities, the formation of a novel psychic reality of “digital consciousness,” and the emergence of hybrid life forms at the nexus of human activity and technological processes. The author highlights the fundamental limitations of AI in the realms of emotional intelligence and creative capabilities. Attention is drawn to the challenges associated with the development of AI systems, including the influence of impersonal social structures on decision-making, the disconnect between developers and users, and the psychological effects of interacting with AI. The conclusion reached is that the issue of human subjugation by AI requires a re-evaluation within the broader context of the impact of contemporary technologies on society. It is proposed that the forthcoming era be viewed as a period of coexistence and interaction between two types of intelligence: natural and artificial. Apprehension is expressed that humanity will not adjust its worldview and behavior until after experiencing a series of impending catastrophes. In closing, the author advocates for proactive engagement in mitigating the risks associated with AI development, while simultaneously underscoring the impracticality of complete abstention from these technologies. (shrink)

This paper provides a philosophically informed and robust account of the global justice implications of Artificial Intelligence (AI). We first discuss some of the key theories of global justice, before justifying our focus on the Capabilities Approach as a useful framework for understanding the context-specific impacts of AI on low- to middle-income countries. We then highlight some of the harms and burdens facing low- to middle-income countries within the context of both AI use and the AI supply chain, (...) by analyzing the extraction of _materials_, which includes mineral extraction and the environmental harms associated with it, and the extraction of _labor_, which includes unethical labor practices, low wages, and the trauma experienced by some AI workers. We then outline some of the potential harms and benefits that AI poses, how these are distributed, and what global justice implications this has for low- to middle-income countries. Finally, we articulate the global justice significance of AI by utilizing the Capabilities Approach. We argue that AI must be considered from a global justice perspective given that, globally, AI puts significant downward pressure on several elements of well-being thereby making it harder for people to achieve threshold levels of the central human capabilities needed for a life of dignity. (shrink)

In their article, Sedlakova and Trachsel (2023) propose a holistic, ethical, and epistemic analysis of conversational artificial intelligence (CAI) in psychotherapeutic settings. They mainly descri...

The article presents a socio-philosophical analysis of artificial intelligence (AI) integration into public administration systems. The research focuses on identifying an optimal balance between enhancing administrative efficiency and preserving humanistic values. The author examines diverse perspectives on AI’s role in contemporary society, ranging from techno-optimistic concepts that view AI as a tool for qualitative improvement of human life, to critical theories warning of dehumanization risks and increased social control. The paper conducts a comparative analysis of national AI development (...) strategies among leading global powers, identifying their common features and significant differences shaped by cultural, political, and economic factors. Potential risks and threats associated with the implementation of AI systems in public administration are explored, including issues of personal data protection, information security, and the ethical dimensions of algorithmic decision-making. The concept of a human-centered approach to AI is examined as a potential guiding principle for the development and deployment of these technologies. Various levels of control over AI systems are characterized, encompassing legal regulation, professional and public evaluation. Particular attention is given to the prospects of artificial general intelligence (AGI) development and its potential impact on the transformation of state institutions and social relations. The study argues that AGI architecture, enabling genuine system agency, must incorporate a level responsible for actualization functions (strategic goal-setting, ethics, knowledge, and self-identification). Special emphasis is placed on the system’s awareness of its finite existence as a necessary condition for developing meaningful operational strategies and ethical principles. The article concludes that as AI technologies advance, the importance of ethical norms, value systems, and responsibility principles increases since these core societal factors cannot be fully replaced even by the most sophisticated regulation. The author highlights the growing significance of mutual trust between state and society in an environment where AI systems provide unprecedented opportunities for social control. (shrink)

This article links three rarely considered dimensions related to the implementation of artificial intelligence (AI)-based technologies in the form of predictive policing and discusses them in relation to liberal democratic societies. The three dimensions are the theoretical embedding and the workings of AI within anomic conditions (1), potential normative disorders emerging from them in the form of thinking errors and discriminatory practices (2) as well as the consequences of these disorders on the psychosocial, and emotional level (3). Against (...) this background, AI-induced anomie is conceptualized as a field of tension that refers to a systematic deterioration of democratic norms that are supposed to create ‘normative orders’, but which, when implemented through AI-supported measures, can reproduce existing discriminations, and establish new kinds of discriminatory relations. In future, these AI-based measures have the potential to lead to opposing normative disorders by emerging in the form of false social norms to an equally false Second Nature. They deprive persons involved of the possibility of individual appropriation of social norms and the specific emotional development associated with it. (shrink)

Applications of artificial intelligence/machine learning in health care are dynamic and rapidly growing. One strategy for anticipating and addressing ethical challenges related to AI/ml for health care is patient and public involvement in the design of those technologies – often referred to as ‘co-design’. Co-design has a diverse intellectual and practical history, however, and has been conceptualized in many different ways. Moreover, AI/ml introduces challenges to co-design that are often underappreciated. Informed by perspectives from critical data studies and (...) critical digital health studies, we review the research literature on involvement in health care, and involvement in design, and examine the extent to which co-design as commonly conceptualized is capable of addressing the range of normative issues raised by AI/ml for health care. We suggest that AI/ml technologies have amplified and modified existing challenges related to patient and public involvement, and created entirely new challenges. We outline three pitfalls associated with co-design for ethical AI/ml for health care and conclude with suggestions for addressing these practical and conceptual challenges. (shrink)

> Future people count. There could be a lot of them. We can make their lives better. > > -- William MacAskill, What We Owe The Future > > [Longtermism is] quite possibly the most dangerous secular belief system in the world today. > > -- Émile P. Torres, Against Longtermism Philosophers,1 2 psychologists,3 4 politicians5 and even some tech billionaires6 have sounded the alarm about artificial intelligence (AI) and the dangers it may pose to the long-term future (...) of humanity. Some believe it poses an existential risk (X-Risk)7 to our species, potentially causing our extinction or bringing about the collapse of human civilisation as we know it. The above quote from philosopher Will MacAskill captures the key tenets of ‘longtermism’, an ethical standpoint that places the onus on current generations to prevent AI-related—and other—X-Risks for the sake of people living in the future.1 2 Developing from an adjacent social movement commonly associated with utilitarian philosophy, ‘effective altruism’, longtermism has amassed following of its own. Its supporters argue that preventing X-Risks is at least as morally significant as addressing current challenges like global poverty. However, critics are concerned that such a distant-future focus will sideline efforts to tackle the many pressing moral issues facing humanity now.8 9 Indeed, according to ‘strong’ longtermism,10 future needs arguably should take precedence over present ones. In essence, the claim is that there is greater expected utility to allocating available resources to prevent human extinction in the future than there is to focusing on present lives, since doing so stands to benefit the incalculably large number of people in later generations who will far outweigh existing populations.1 Taken to the extreme, this view suggests it would be morally permissible, or even required, to actively neglect, harm or destroy large swathes of humanity as …. (shrink)

인공지능의 개발 경쟁이 본격화됨에 따라 막대한 자본이 투입되고 AI관련 시장 점유율 이 획기적으로 증가하고 있다. 이런 추세는 인공지능이 우리의 일상적 생활에 광범위한 영 향을 미칠 뿐만 아니라 정치영역에도 커다란 파장을 몰고 올 것으로 예상하게 한다. 이를 배경으로 본 연구는 인공지능이 민주주의에 어떤 함의를 가질 것인지 탐색하고자 한다. 2022년 11월 Open ChatGPT 출시 이후 이 주제에 대한 연구들이 쏟아져 나왔지만 아직 상당히 추상적이고 피상적인 모습을 넘어서지 못하고 있는 상황을 진단하고, 본 연구는 다 음 세 단계를 통해 이 주제에 대한 구체적이고 실질적인 (...) 연구를 꾀한다. 먼저, 인공지능이 우리에게 어떤 영향을 줄 것인지 ‘개발-유통-사용’의 현실적 맥락에서 구체적으로 파악 한다. 둘째, 민주주의를 일반적 개념으로 추상화하지 않고 세 개의 구체적 모델(시장모델, 합의모델, 공동체모델)로 제시한다. 셋째, 인공지능의 현실적 효과를 각 민주주의 모델에 적용하여 실질적 관계를 분석한다. 그 결과, 현실적 맥락에서 인공지능의 영향력 확산과 침투는 세 민주주의 모델에 각기 다른 이유로 부정적으로 작용할 개연성을 조심스럽게 진 단한다. 이는 인공지능 자체가 가지는 문제라기보다 ‘생산-유통=소비’되는 현실적 맥락 에 기인하는 것으로 볼 수 있다. (shrink)

The societal and ethical implications of artificial intelligence (AI) have sparked discussions among academics, policymakers and the public around the world. What has gone unnoticed so far are the likewise vibrant discussions in China. We analyzed a large sample of discussions about AI ethics on two Chinese social media platforms. Findings suggest that participants were diverse, and included scholars, IT industry actors, journalists, and members of the general public. They addressed a broad range of concerns associated with the (...) application of AI in various fields. Some even gave recommendations on how to tackle these issues. We argue that these discussions are a valuable source for understanding the future trajectory of AI development in China as well as implications for global dialogue on AI governance. (shrink)

Psychotherapy is provided by professionals, trained, supervised and certified by other professionals, all the way back to Freud and similar founding fathers. Even though methods and styles vary, pa...

The association of Wittgenstein’s name with the notion of artificial intelligence is bound to cause some surprise both to Wittgensteinians and to people interested in artificial intelligence. After all, Wittgenstein died in 1951 and the term artificial intelligence didn’t come into use until 1956 so that it seems unlikely that one could have anything to do with the other. However, establishing a connection between Wittgenstein and artificial intelligence is not as insuperable (...) a problem as it might appear at first glance. While it is true that artificial intelligence as a quasi-distinct discipline is of recent vintage, some of its concerns, especially those of a philosophical nature, have been around for quite some time. At the birth of modern philosophy we find Descartes wondering whether it would be possible to create a machine that would be phenomenologically indistinguishable from.. (shrink)

Our society is in the middle of the AI revolution. We discuss several applications of AI, in particular medical causality, where deep-learning neural networks screen through big data bases, extracting associations between a patient’s condition and possible causes. While beneficial in medicine, several questionable AI trading strategies have emerged in finance. Though advantages in many aspects of our lives, serious threats of AI exist. We suggest several regulatory measures to reduce these threats. We further discuss whether ‘full AI robots’ should (...) be programmed with a virtual consciousness and conscience. While this would reduce AI threats via motivational control, other threats such as the desire for AI—human socioeconomic equality could prove detrimental. (shrink)

In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with (...) AI, and the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment. (shrink)

I thank Jane Sedlakova and Manuel Trachsel for their work on situating conversational artificial intelligence’s (CAI) potential role in psychotherapy. In their article, Sedlakova and Trachsel argue...

Most jurisdictions require a patient to consent to any medical intervention. Clinicians ask a patient, ‘Given the pain and distress associated with our intervention and the predicted likelihood of this best-case outcome, do you want to accept the treatment?’ When a patient is incapable of deciding, clinicians may ask people who know the patient to say what the patient would decide; this is substituted judgement. In contrast, asking the same people to say how the person would make the decision is (...) substituted interests.1 The UK Mental Capacity Act 2005 uses the latter approach, and my comments appertain to that approach. When a patient lacks capacity, the question facing clinicians is, ‘Given the likely outcome of this treatment plan for the patient’s life in the long term, would the patient decide to accept the plan?’ This answer depends on the patient’s wishes, values and other factors they would use when deciding. The proposed development of an algorithm involves the following:2. (shrink)

In their target article, “A Personalized Patient Preference Predictor for Substituted Judgments in Healthcare: Technically Feasible and Ethically Desirable,” Earp et al. (2024) discuss ways in whic...

McCarthy and Howard (2023) present a “Non-Domination” approach to supported decision-making, specially to help intellectually and developmentally disabled (IDD) patients rather than “Mental Prosthe...

Artificial Intelligence (AI) is set to bring changes to legal systems. These technologies may have positive practical implications when it comes to access, efficiency, and accuracy in Justice. However, there are still many uncertainties and challenges associated with the implementation of AI in the legal space. In this research, we surveyed Judges on critical challenges related to the Judging Profession in the AI paradigm; Automated Adjudication; and Legal Principles. Our results suggest that (i) Judges are hesitant about changes (...) in their profession. They signal the need for adequate training that fosters legal literacy in AI, but are less open to changes in legal writing or their social and institutional role; (ii) Judges believe higher levels of automation only lead to fair outcomes if used in earlier phases of adjudication; (iii) Judges believe and are concerned about AI leading to Techno-Legal Positivism; and (iv) Judges consider that Legal AI technologies may have a positive impact in some legal principles, as long as everyone has equal access to those technologies and cybersecurity and judge on the loop safeguards are in place; and (v) Judges are strongly concerned about the de-humanization of Justice. They consider that assessing evidence, analyzing arguments, and deciding on a legal case should be inherently human. By surveying these practitioners, we aim to foster a responsible, inclusive, and transparent innovation in Justice. (shrink)

For over a decade John Searle's ingenious argument against the possibility of artificial intelligence has held a prominent place in contemporary philosophy. This is not just because of its striking central example and the apparent simplicity of its argument. As its appearance in Scientific American testifies, it is also due to its importance to the wider scientific community. If Searle is right, artificial intelligence in the strict sense, the sense that would claim that mind can (...) be instantiated through a formal program of symbol manipulation, is basically wrong. No set of formal conditions can provide us with the characteristic feature of mind which is the intentionally of its mental contents. Formally regarded, such intentionally is an irreducible primitive. It cannot be analyzed into non-intentional (purely syntactic, symbolic) components. This paper will argue that this objection is based on a misunderstanding. Intentionality is not simply something given which is incapable of further analysis. It only appears so when we mistakenly abstract it from time. When we regard its temporal structure, it shows itself as a rule-governed, synthetic process, one capable of being instantiated both by machines and men. (shrink)

The argument presented in this paper is not a direct attack or defence of the Chinese Room Argument (CRA), but relates to the premise at its heart, that syntax is not sufficient for semantics, via the closely associated propositions that semantics is not intrinsic to syntax and that syntax is not intrinsic to physics. However, in contrast to the CRA’s critique of the link between syntax and semantics, this paper will explore the associated link between syntax and physics. The main (...) argument presented here is not significantly original – it is a simple reflection upon that originally given by Hilary Putnam (Putnam 1988) and criticised by David Chalmers and others: instead of seeking to justify Putnam’s claim that, “every open system implements every Finite State Automaton (FSA)”, and hence that psychological states of the brain cannot be functional states of a computer, I will seek to establish the weaker result that, over a finite time window every open system implements the trace of a particular FSA Q, as it executes program (p) on input (x). That this result leads to panpsychism is clear as, equating Q (p, x) to a specific Strong AI program that is claimed to instantiate phenomenal states as it executes, and following Putnam’s procedure, identical computational (and ex hypothesi phenomenal) states (ubiquitous little ‘pixies’) can be found in every open physical system. (shrink)

This article identifies and examines a tension in mental health researchers’ growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research specifically, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data (...) points. The imperatives of the “participatory turn” in mental health research may be at odds with the (often unquestioned) assumptions and data collection methods of AI/ML approaches. This article aims to show why this is a problem and how it might be addressed. (shrink)

The use of artificial intelligence (AI) to make high-stakes decisions is sometimes thought to create a troubling responsibility gap – that is, a situation where nobody can be held morally responsible for the outcomes that are brought about. However, philosophers and practitioners have recently claimed that, even though no individual can be held morally responsible, groups of individuals might be. Consequently, they think, we have less to fear from the use of AI than might appear to be the (...) case. This paper assesses this claim. Drawing on existing philosophical models of collective responsibility, I consider whether changing focus from the individual to the collective level can help us identify a locus of responsibility in a greater range of cases of AI deployment. I find that appeal to collective responsibility will be of limited use in filling the responsibility gap: the models considered either do not apply to the case at hand or else the relevant sort of collective responsibility, even if present, will not be sufficient to remove the costs that are often associated with an absence of responsibility. (shrink)

Hubert and Stuart Dreyfus have tried to place connectionism and artificial intelligence in a broader historical and intellectual context. This history associates connectionism with neuroscience, conceptual holism, and nonrationalism, and artificial intelligence with conceptual atomism, rationalism, and formal logic. The present paper argues that the Dreyfus account of connectionism and artificial intelligence is both historically and philosophically misleading.

Transparency is now a fundamental principle for data processing under the General Data Protection Regulation. We explore what this requirement entails for artificial intelligence and automated decision-making systems. We address the topic of transparency in artificial intelligence by integrating legal, social, and ethical aspects. We first investigate the ratio legis of the transparency requirement in the General Data Protection Regulation and its ethical underpinnings, showing its focus on the provision of information and explanation. We then discuss (...) the pitfalls with respect to this requirement by focusing on the significance of contextual and performative factors in the implementation of transparency. We show that human–computer interaction and human-robot interaction literature do not provide clear results with respect to the benefits of transparency for users of artificial intelligence technologies due to the impact of a wide range of contextual factors, including performative aspects. We conclude by integrating the information- and explanation-based approach to transparency with the critical contextual approach, proposing that transparency as required by the General Data Protection Regulation in itself may be insufficient to achieve the positive goals associated with transparency. Instead, we propose to understand transparency relationally, where information provision is conceptualized as communication between technology providers and users, and where assessments of trustworthiness based on contextual factors mediate the value of transparency communications. This relational concept of transparency points to future research directions for the study of transparency in artificial intelligence systems and should be taken into account in policymaking. (shrink)

This article addresses the issue of attributing phenomenal consciousness to Artificial Intelligence (AI), a mistake that can lead to ethically dangerous consequences and that is becoming widespread due to the advances of Large Language Models such as ChatGPT. We juxtapose advancements in AI with the notion of inner experience as it is present in humans. The study draws from various disciplines, including philosophy of mind, artificial intelligence, and theological texts such as "The Inner Castle" by Saint (...) Theresa of Ávila and "Confessions" by Saint Augustine. Firstly, it reviews the current state of the relationship between phenomenal consciousness and AI, followed by a critique of the idea that advanced language models, like ChatGPT, can achieve an inner experience in the same sense we use the term to describe the human inner experience. A common objection is raised, suggesting that AI can become conscious by increasing its complexity. This is countered by presenting theoretical and empirical evidence on the independence of computational intelligence and phenomenal consciousness. The study concludes that, despite AI's notable cognitive abilities, it lacks the inner experience that characterizes human experience. Then, our second main contribution is an analogy of the dwellings of the Inner Castle to the range of different subjective experiences that are available to human beings, together with actions associated to them, which can be useful to understand where the machine can perform tasks that are similar to the human and where subjective experience is key. We are now in a pivotal moment where it is essential to understand the limitations of AI for deploying it ethically. (shrink)

The aim of this article is, on the one hand, to take up and discuss some key categories and concepts in semiotics, in an attempt to analyze the mechanisms underlying current artificial intelligence (AI) models, with a focus on ChatGPT. Although many of these concepts are already being debated, they remain crucial in relation to semiotic and sociosemiotic categories. Concepts such as generativity, perception, textuality, and the effects of meaning, as well as the notion of language itself, require (...) a new semiotic evaluation, including in relation to a cultural history of AI, and the metaphors associated with it. In addition, this article aims to propose more of a general observation and review of some theoretical problems and sociosemiotic issues related to the advent of AIs with some correlated examples, such as in the field of political communication and conflict. (shrink)