The application of Artificial Intelligence (AI) in healthcare and epidemiology undoubtedly has many benefits for the population. However, due to its environmental impact, the use of AI can produce social inequalities and long-term environmental damages that may not be thoroughly contemplated. In this paper, we propose to consider the impacts of AI applications in medical care from the One Health paradigm and long-term global health. From health and environmental justice, rather than settling for a short and fleeting green (...) honeymoon between health and sustainability caused by AI, it should aim for a lasting marriage. To this end, we conclude by proposing that, in the upcoming years, it could be valuable and necessary to promote more interconnected health, call for environmental cost transparency, and increase green responsibility. (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)

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

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)

Organizations such as the EU High-Level Expert Group on AI and the IEEE have recently formulated ethical principles and (moral) values that should be adhered to in the design and deployment of artificial intelligence (AI). These include respect for autonomy, non-maleficence, fairness, transparency, explainability, and accountability. But how can we ensure and verify that an AI system actually respects these values? To help answer this question, I propose an account for determining when an AI system can be said (...) to embody certain values. This account understands embodied values as the result of design activities intended to embed those values in such systems. AI systems are here understood as a special kind of sociotechnical system that, like traditional sociotechnical systems, are composed of technical artifacts, human agents, and institutions but—in addition—contain artificial agents and certain technical norms that regulate interactions between artificial agents and other elements of the system. The specific challenges and opportunities of embedding values in AI systems are discussed, and some lessons for better embedding values in AI systems are drawn. (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 ..

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)

What does it mean to consider the world of AI through a Christian lens? Rapid developments in AI continue to reshape society, raising new ethical questions and challenging our understanding of the human person. Encountering Artificial Intelligence draws on Pope Francis’ discussion of a culture of encounter and broader themes in Catholic social thought in order to examine how current AI applications affect human relationships in various social spheres and offers concrete recommendations for better implementation. The document also (...) explores questions regarding personhood, consciousness, and the kinds of relationships humans might have with even the most advanced AI. Through these discussions, this book investigates the theoretical and practical challenges to interpersonal encounter raised by the age of AI. (AI Research Group for the Centre for Digital Culture of the Dicastery of Culture and Education of the Holy See). (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)

Artificial intelligence is increasingly permeating many types of high-stake societal decision-making such as the work at the criminal courts. Various types of algorithmic tools have already been introduced into sentencing. This article concerns the use of algorithms designed to deliver sentence recommendations. More precisely, it is considered how one should determine whether one type of sentencing algorithm (e.g., a model based on machine learning) would be ethically preferable to another type of sentencing algorithm (e.g., a model based on (...) old-fashioned programming). Whether the implementation of sentencing algorithms is ethically desirable obviously depends upon various questions. For instance, some of the traditional issues that have received considerable attention are algorithmic biases and lack of transparency. However, the purpose of this article is to direct attention to a further challenge that has not yet been considered in the discussion of sentencing algorithms. That is, even if is assumed that the traditional challenges concerning biases, transparency, and cost-efficiency have all been solved or proven insubstantial, there will be a further serious challenge associated with the comparison of sentencing algorithms; namely, that we do not yet possess an ethically plausible and applicable criterion for assessing how well sentencing algorithms are performing. (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 article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to the collection of partial data, rare updates, and significant demands on resources. To address these issues, the article suggests that specific data management and Machine Learning (ML) techniques, such as natural language processing (...) and sentiment analysis, can improve the measurement (ML about) and practice (ML for) of IPD. The article concludes by considering some of the principal risks of ML for IPD, including concerns over data privacy, the potential for manipulation, and the dangers of overreliance on technology. (shrink)

Deep learning (DL) has become increasingly central to science, primarily due to its capacity to quickly, efficiently, and accurately predict and classify phenomena of scientific interest. This paper seeks to understand the principles that underwrite scientists’ epistemic entitlement to rely on DL in the first place and argues that these principles are philosophically novel. The question of this paper is not whether scientists can be justified in trusting in the reliability of DL. While today’s artificial intelligence exhibits characteristics (...) common to both scientific instruments and scientific experts, this paper argues that the familiar epistemic categories that justify belief in the reliability of instruments and experts are distinct, and that belief in the reliability of DL cannot be reduced to either. Understanding what can justify belief in AI reliability represents an occasion and opportunity for exciting, new philosophy of science. (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...

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)

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 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)

인공지능에 인격의 지위를 부여할 수 있는지에 대한 찬반 논쟁에서, 인격에 대한 칸트의 관점이 종종 인용된다. 인공지능에 인격을 부여할 수 있는지에 대한 찬성 입장과 반대 입장 사이에 여러 상이한 주장들이 발견되는 한편, 양측은 종종 인격에 대한 칸트의 관점에 따르면 인공지능에는 인격이 부여될 수 없다는 해석을 공통적으로 받아들인다. 인공지능에 인격의 지위를 부여하는 것에 반대하는 입장에서는 칸트 철학에 대한 그러한 해석을 인공지능 일반에 인격의 지위를 부여해서는 안 된다는 주장을 뒷받침하는 철학적 논거 중 하나로 활용하는 반면, 인공지능에 인격의 지위를 부여하는 것에 찬성하는 입장에서는 칸트 (...) 철학에 대한 그러한 해석을 극복해야 할 인간 중심주의적 편견을 보여주는 한 사례로 활용한다. 본 논문은 찬반 양측이 종종 공유하는 해당 해석의 한계를 지적하고, 인격에 대한 칸트의 관점이 인공지능에 인격을 부여할 수 있는지의 문제에 어떠한 시사점을 줄 수 있는지에 대해 논의한다. 해당 해석은 특정 분야의 문제 해결을 위해서만 활용될 수 있는 약 인공지능에 적용되는 경우 어느 정도 설득력이 있으나, 이성적 사유와 도덕적 행위를 수행할 수 있을 것으로 상상되는 강 인공지능까지 논의의 범위에 포함되는 경우 문제적이다. 해당 해석은 칸트가 인격을 이성적 사유와 도덕적 행위의 가능성을 뒷받침하는 표상으로 제시할 뿐, 인격의 표상이 적용될 수 있는 실제 존재자의 범위에 대한 객관적 지식을 주장하지 않는다는 점을 종종 간과한다. 칸트는 인격에 대한 객관적 지식이 성립될 수 없다고 주장하므로, 인격에 대한 칸트의 관점은 인격적 존재자를 인간종의 범위 안으로 국한시키는 인간 중심주의와는 거리가 멀며, 이성적 사유와 도덕적 행위를 수행할 수 있을 것으로 상상되는 강인공지능의 출현 가능성을 부정할 논거로 활용되기 어렵다. (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)

Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should be (...) interpreted. The problem of symbolic grounding (Harnad, 1990) is then addressed to show the problematic relationship between ChatGPT and the natural environment, and thus the impossibility for it to understand the symbols it manipulates. To explain the reasons why ChatGPT does not succeed in this task, an investigation is carried out and a possible solution to the problem in the artificial domain is proposed by making a comparison with the natural ability of living beings to ground their own meanings from some basic cognitive-sensory aspects, which, it is explained, are directly related to the emergence of self-awareness in humans. Thus, the question is raised whether a possible and concrete solution to the Symbol Grounding Problem would involve in the artificial domain the development of cognitive abilities fully comparable to those of humans. Finally, I explain the difficulties that would have to be overcome before such a level could be reached, since human cognitive capacities are intimately linked to intersubjectivity and intercorporeality. (shrink)

This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects of the AI alignment problem are interrelated, creating space for productive engagement between people working in both domains. Second, it is important to be clear about the goal of alignment. There are significant differences between AI that aligns with instructions, intentions, revealed preferences, ideal preferences, interests and values. A principle-based approach to AI alignment, which combines these elements (...) in a systematic way, has considerable advantages in this context. Third, the central challenge for theorists is not to identify ‘true’ moral principles for AI; rather, it is to identify fair principles for alignment that receive reflective endorsement despite widespread variation in people’s moral beliefs. The final part of the paper explores three ways in which fair principles for AI alignment could potentially be identified. (shrink)

This paper discusses two opposing views about the relation between artificial intelligence (AI) and human intelligence: on the one hand, a worry that heavy reliance on AI technologies might make people less intelligent and, on the other, a hope that AI technologies might serve as a form of cognitive enhancement. The worry relates to the notion that if we hand over too many intelligence-requiring tasks to AI technologies, we might end up with fewer opportunities to train (...) our own intelligence. Concerning AI as a potential form of cognitive enhancement, the paper explores two possibilities: (1) AI as extending—and thereby enhancing—people’s minds, and (2) AI as enabling people to behave in artificially intelligent ways. That is, using AI technologies might enable people to behave as if they have been cognitively enhanced. The paper considers such enhancements both on the level of individuals and on the level of groups. (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)

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)

인공 감정에 관한 철학적 탐구가 필요한 시점이다. 인간의 고유한 영역으로 간주되던 인지적 과제에서 기계의 추월을 염려하는 처지가 되자, 사람들은 이제 이성이 아니라 감정에서 인간의 고유성을 찾으려한다. 하지만 최근 인공지능 로봇에 감성을 불어넣는 작업이 새로운 화두로 떠오르고 있다. 이 글은 인공 감정의 실현가능성과 잠재적인 위험을 논의한다. 먼저, 감성 로봇의 개발 현황과 주요한 동기들을 개괄하고, 왜 로봇의 감정이 문제가 되는지 살펴본다. 진정한 감정-소유 로봇이 가능한지 검토하기 위해 감정을 선험적으로 정의하기보다는 감정이 수행하는 몇 가지 핵심 역할을 소개하고 이로부터 어떤 대상에 감정을 부여할 수 (...) 있는 기준들을 제안한다. 나는 이런 기준에 비추어 진정한 감정 로봇이 근미래에 실현될 가능성이 낮다고 주장한다. 그러나 감정-소유 로봇이 등장하기 이전이라도, 어느 정도의 자율성을 가진 로봇과 맺는 일방적 감정 소통은 잠재적으로 위험할 수 있으며, 이에 대비하는 것이 시급하다고 주장한다. (shrink)

This book provides an overview of the various biometric technologies, decision-making algorithms and the subsequent market expansion opportunity. Further, this book proposes a Throughput Model, which draws from computer science, economic and psychology literatures to model perceptual, informational sources, judgmental processes and decision choice algorithms. This approach describes how biometrics might be implemented to reduce risks to individuals and organizations, especially when dealing with digital based mediums.

In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and (...) legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens. (shrink)

The world’s current model for economic development is unsustainable. It encourages high levels of resource extraction, consumption, and waste that undermine positive environmental outcomes. Transitioning to a circular economy (CE) model of development has been proposed as a sustainable alternative. Artificial intelligence (AI) is a crucial enabler for CE. It can aid in designing robust and sustainable products, facilitate new circular business models, and support the broader infrastructures needed to scale circularity. However, to date, considerations of the ethical (...) implications of using AI to achieve a transition to CE have been limited. This article addresses this gap. It outlines how AI is and can be used to transition towards CE, analyzes the ethical risks associated with using AI for this purpose, and supports some recommendations to policymakers and industry on how to minimise these risks. (shrink)

As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts (...) from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders. (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)

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)

This is the first professional academic work in China to discuss artificial intelligence and blockchain together. Artificial intelligence is a productivity revolution, and its development has a significant and profound impact on global changes. However, at the same time, its development also brings a series of challenges to human society, such as privacy, security, and fairness issues. Therefore, the significance of blockchain is even more prominent. Blockchain is a revolution in production relations, which will propose important (...) solutions to the challenges of privacy, security, and fairness that arise after the development of artificial intelligence. The book not only discusses the problems currently faced by the development of artificial intelligence, as well as the new opportunities and challenges that artificial intelligence brings to future global governance, but also explains the further development direction of the intelligent revolution from the perspective of blockchain. (shrink)

Highly sophisticated capabilities of artificial intelligence (AI) have skyrocketed its popularity across many industry sectors globally. The public sector is one of these. Many cities around the world are trying to position themselves as leaders of urban innovation through the development and deployment of AI systems. Likewise, increasing numbers of local government agencies are attempting to utilise AI technologies in their operations to deliver policy and generate efficiencies in highly uncertain and complex urban environments. While the popularity of (...) AI is on the rise in urban policy circles, there is limited understanding and lack of empirical studies on the city manager perceptions concerning urban AI systems. Bridging this gap is the rationale of this study. The methodological approach adopted in this study is twofold. First, the study collects data through semi-structured interviews with city managers from Australia and the US. Then, the study analyses the data using the summative content analysis technique with two data analysis software. The analysis identifies the following themes and generates insights into local government services: AI adoption areas, cautionary areas, challenges, effects, impacts, knowledge basis, plans, preparedness, roadblocks, technologies, deployment timeframes, and usefulness. The study findings inform city managers in their efforts to deploy AI in their local government operations, and offer directions for prospective research. (shrink)

‘도덕 행위자(moral agent)’의 개념은 전통적으로 자신의 행동에 대해 책임을 질 수 있는 자유의지를 가진 인격적 존재에 한정되어 적용되었다. 그런데 도덕적 함축을 갖는 다양한 행동을 수행할 수 있는 자율적 AI의 등장은 이러한 행위자 개념의 수정을 요구하는 것처럼 보인다. 필자는 이 논문에서 일정한 요건을 만족시키는 AI에 대해서 인격성을 전제하지 않는 기능적인 의미의 도덕 행위자 자격이 부여될 수 있다고 주장한다. 그리고 그런 한에 있어서, AI에게도 그 행위자성에 걸맞은 책임 혹은 책무성의 귀속이 가능해진다. 이러한 주장을 뒷받침하기 위하여, 본 논문은 예상되는 여러 가능한 반론들을 살펴보고 (...) 거기에 응답함으로써, AI를 자율적 행위자로 여길 수 있는 여러 근거들을 제시하는 동시에, AI에게 귀속 가능한 책임 혹은 책무성의 개념을 발전시키고자 시도한다. (shrink)

인공지능이 자율성을 가진 존재일 수 있는가? 자율성은 책임과 권리같은 관념의 선결 조건으로 오늘의 사회에서 ‘인공지능이 해내는 일’에 연관된 책임과 공헌을 배분하는 데 적용할 규범의 이론적 기반이 된다는 점에서 이 물음은 현실적으로 중요하다. 공학의 ‘자율적 에이전트’ 개념은 현행의 철학적 논의에도 영향을 미치며, 공학과 철학의 자율성 개념 간의 관계가 명료하게 인식되지 못한 까닭에 야기될 혼란의 개연성이 실재한다. 이런 현실의 문제 상황을 의식하면서, 이 논문은 앞의 물음을 가능성에 관한 물음과 정당성에 관한 물음으로 분석하고, 인공지능의 자율성에 관한 전망을 검토한다. 논의의 과정에서 ‘X가 자율성을 가진다’는 (...) 의미를 규명해야 할 필요가 확인되고, 논문은 루소와 칸트와 크리스만의 논의를 활용하여 자율성의 개념을 고찰한다. 그렇게 분석한 자율성의 개념을 인공지능의 속성에 적용해 볼 때, 칸트가 정립한 자율성 개념에 비추어 인공지능은 자율적 존재일 수 없으며, 크리스만의 서술에서 부각된 자율적 존재의 핵심 속성을 고려할 때 인공지능이나 그것으로 작동하는 로보틱 시스템이 자율성을 지니도록 하는 것은 부적절한 위험을 허용한다는 점에서 옳지 않음이 드러난다. (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)

Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young (...) and inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

It has become a truism that the ethics of artificial intelligence (AI) is necessary and must help guide technological developments. Numerous ethical guidelines have emerged from academia, industry, government and civil society in recent years. While they provide a basis for discussion on appropriate regulation of AI, it is not always clear how these ethical guidelines were developed, and by whom. Using content analysis, we surveyed a sample of the major documents (_n_ = 47) and analyzed the accessible (...) information regarding their methodology and stakeholder engagement. Surprisingly, only 38% report some form of stakeholder engagement (with 9% involving citizens) and most do not report their methodology for developing normative insights (15%). Our results show that documents with stakeholder engagement develop more comprehensive ethical guidance with greater applicability, and that the private sector is least likely to engage stakeholders. We argue that the current trend for enunciating AI ethical guidance not only poses widely discussed challenges of applicability in practice, but also of transparent development (as it rather behaves as a black box) and of active engagement of diversified, independent and trustworthy stakeholders. While most of these documents consider people and the common good as central to their telos, engagement with the general public is significantly lacking. As AI ethics moves from the initial race for enunciating general principles to more sustainable, inclusive and practical guidance, stakeholder engagement and citizen involvement will need to be embedded into the framing of ethical and societal expectations towards this technology. (shrink)

: Artificial intelligences and robots increasingly mimic human mental powers and intelligent behaviour. However, many authors claim that ascribing human mental powers to them is both conceptually mistaken and morally dangerous. This article defends the view that artificial intelligences can have human-like mental powers, by claiming that both human and artificial minds can be seen as extended minds – along the lines of Chalmers and Clark’s view of mind and cognition. The main idea of this article is (...) that the Extended Mind Model is independently plausible and can easily be extended to artificial intelligences, providing a solid base for concluding that artificial intelligences possess minds. This may warrant viewing them as morally responsible agents. Keywords: Artificial Intelligence; Mind; Moral Responsibility; Extended Cognition Intelligenze artificiali come menti estese. Perché no? Riassunto: Intelligenze artificiali e robot simulano in misura sempre crescente le capacità mentali e i comportamenti intelligenti umani. Molti autori, tuttavia, sostengono che attribuire loro capacità mentali umane sia concettualmente errato e moralmente pericoloso. In questo lavoro si difende l’idea per cui le intelligenze artificiali possano avere capacità mentali simili a quelle umane, sostenendo che menti umane e artificiali possano essere considerate come menti estese – sulla scorta della prospettiva di Chalmers e Clark circa la mente e la cognizione. L’idea principale alla base di questo lavoro è che il Modello della Mente Estesa abbia plausibilità a prescindere e che possa essere facilmente esteso alle intelligenze artificiali, fornendo una base solida per concludere che le intelligenze artificiali possiedano delle menti e si possano considerare come agenti moralmente responsabili. Parole chiave: Intelligenza artificiale; Mente; Responsabilità morale; Conoscenza estesa. (shrink)

Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, (...) and procedures cannot be meaningfully understood by human practitioners. When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, black-box medicine is not conducive for supporting informed decision-making based on shared information, shared deliberation, and shared mind between practitioner and patient. (shrink)

Recent decades have witnessed tremendous progress in artificial intelligence and in the development of autonomous systems that rely on artificial intelligence. Critics, however, have pointed to the difficulty of allocating responsibility for the actions of an autonomous system, especially when the autonomous system causes harm or damage. The highly autonomous behavior of such systems, for which neither the programmer, the manufacturer, nor the operator seems to be responsible, has been suspected to generate responsibility gaps. This has (...) been the cause of much concern. In this article, I propose a more optimistic view on artificial intelligence, raising two challenges for responsibility gap pessimists. First, proponents of responsibility gaps must say more about when responsibility gaps occur. Once we accept a difficult-to-reject plausibility constraint on the emergence of such gaps, it becomes apparent that the situations in which responsibility gaps occur are unclear. Second, assuming that responsibility gaps occur, more must be said about why we should be concerned about such gaps in the first place. I proceed by defusing what I take to be the two most important concerns about responsibility gaps, one relating to the consequences of responsibility gaps and the other relating to violations of jus in bello. (shrink)