In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with (...) 97.50 % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

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

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)

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)

And why is there a subjective component to experience?). It is easy to see that the separation between Weak and Strong Artificial Consciousness mirrors the separation between the easy problems and the hard problems of consciousness.

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)

In the field of machine consciousness, it has been argued that in order to build human-like conscious machines, we must first have a computational model of qualia. To this end, some have proposed a framework that supports qualia in machines by implementing a model with three computational areas (i.e., the subconceptual, conceptual, and linguistic areas). These abstract mechanisms purportedly enable the assessment of artificial qualia. However, several critics of the machine consciousness project dispute this possibility. For instance, Searle, in (...) his Chinese room objection, argues that however sophisticated a computational system is, it can never exhibit intentionality; thus, would also fail to exhibit consciousness or any of its varieties. This paper argues that the proposed architecture mentioned above answers the problem posed by Searle, at least in part. Specifically, it argues that we could reformulate Searle’s worries in the Chinese room in terms of the three-stage artificial qualia model. And by doing so, we could see that the person doing all the translations in the room could realize the three areas in the proposed framework. Consequently, this demonstrates the actualization of self-consciousness in machines. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method (...) is suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (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)

Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims to: (...) (i) defend the need for a novel conceptual model for understanding the systemic legal disruption caused by new technologies such as AI; (ii) to situate this model in relation to preceding debates about the interaction of regulation with new technologies (particularly the ‘cyberlaw’ and ‘robolaw’ debates); and (iii) to set out a detailed model for understanding the legal disruption precipitated by AI, examining both pathways stemming from new affordances that can give rise to a regulatory ‘disruptive moment’, as well as the Legal Development, Displacement or Destruction that can ensue. The article proposes that this model of legal disruption can be broadly generalisable to understanding the legal effects and challenges of other emerging technologies. (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 ..

While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...) robot blame, namely the folk's willingness to ascribe inculpating mental states or "mens rea" to robots. In a vignette-based experiment (N=513), we presented participants with a situation in which an agent knowingly runs the risk of bringing about substantial harm. We manipulated agent type (human v. group agent v. AI-driven robot) and outcome (neutral v. bad), and measured both moral judgment (wrongness of the action and blameworthiness of the agent) and mental states attributed to the agent (recklessness and the desire to inflict harm). We found that (i) judgments of wrongness and blame were relatively similar across agent types, possibly because (ii) attributions of mental states were, as suspected, similar across agent types. This raised the question - also explored in the experiment - whether people attribute knowledge and desire to robots in a merely metaphorical way (e.g., the robot "knew" rather than really knew). However, (iii), according to our data people were unwilling to downgrade to mens rea in a merely metaphorical sense when given the chance. Finally, (iv), we report a surprising and novel finding, which we call the inverse outcome effect on robot blame: People were less willing to blame artificial agents for bad outcomes than for neutral outcomes. This suggests that they are implicitly aware of the dangers of overattributing blame to robots when harm comes to pass, such as inappropriately letting the responsible human agent off the moral hook. (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)

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)

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)

Cyberfeminism and Artificial Life examines construction, manipulation and re-definition of life in contemporary technoscientific culture. It takes a critical political view of the concept of life as information, tracing this through the new biology and the changing discipline of artificial life and its manifestation in art, language, literature, commerce and entertainment. From cloning to computer games, and incorporating an analysis of hardware, software and 'wetware', Sarah Kember demonstrates how this relatively marginal field connects with, and connects up global (...) networks of information systems. As well as offering suggestions for the evolution of [cyber]feminism in Alife environments, the author identifies the emergence of posthumanism; an ethics of the posthuman subject mobilized in the tension between cold war and post-cold war politics, psychological and biological machines, centralized and de-centralized control, top-down and bottom-up processing, autonomous and autopoietic organisms, cloning and transgenesis, species-self and other species. Ultimately, this book aims to re-focus concern on the ethics rather than on the 'nature' of life-as-it-could-be. (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)

Wittgenstein’s Private Language Argument holds that language requires rule-following, rule following requires the possibility of error, error is precluded in pure introspection, and inner mental life is known only by pure introspection, thus language cannot exist entirely within inner mental life. Fodor defends his Language of Thought program against the Private Language Argument with a dilemma: either privacy is so narrow that internal mental life can be known outside of introspection, or so broad that computer language serves as a counter-example. (...) I suggest that the developing field of artificial intelligence (deep learning neural networks) tends to vitiate Fodor’s defense and hence vindicate the Private Language Argument. The first horn of Fodor’s dilemma requires language to encompass genuinely internal mental life, i.e. non-projected intentional states, which are not exhibited in classical machine learning but only by deep learning neural networks (artificial intelligence). Such networks act as black boxes, however, whose state cannot be understood by tracking the changes in their supervenience bases without shared context, and that shared context introduces the possibility of error. The language of artificial intelligence is not private. (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)

Ectogenesis (artificial wombs) might soon become a reality. This paper will analyse how the development of such technologies will affect Judith Jarvis Thomson’s defence of abortion, and what the potential consequences of this will be for society. Thomson attempts to justify abortion by appealing to the mother’s right to bodily autonomy. We will argue that once these technologies have been developed, the right to abortion can no longer be justified by such appeals. As a result, when justifying abortion, Thomson-style (...) arguments will no longer work, and a very different strategy will have to be adopted by those wishing to justify its permissibility. Anticipating a consequent weaker position of the pro-choice view, we briefly consider some of the practical implications of ectogenesis for society: effects on parental dynamics, governmental expenditure, research, and gender equality. (shrink)

In most domains of human life, we are willing to accept that there are experts with greater knowledge and competencies that distinguish them from non-experts or laypeople. Despite this fact, the very recognition of expertise curiously becomes more controversial in the case of “moral experts”. Do moral experts exist? And, if they indeed do, are there ethical reasons for us to follow their advice? Likewise, can emerging technological developments broaden our very concept of moral expertise? In this article, we begin (...) by arguing that the objections that have tried to deny the existence (and convenience) of moral expertise are unsatisfactory. After that, we show that people have ethical reasons to ask for a piece of moral advice in daily life situations. Then, we argue that some Artificial Intelligence (AI) systems can play an increasing role in human morality by becoming moral experts. Some AI-based moral assistants can qualify as artificial moral experts and we would have good ethical reasons to use them. (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)

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 book explores the role of artificial intelligence in the development of a claim that morality is person-made and rational. Professor Danielson builds moral robots that do better than amoral competitors in a tournament of games like the Prisoners Dilemma and Chicken. The book thus engages in current controversies over the adequacy of the received theory of rational choice. It sides with Gauthier and McClennan, who extend the devices of rational choice to include moral constraint. Artificial Morality goes (...) further, by promoting communication, testing and copying of principles and by stressing empirical tests. (shrink)

Artificial Knowing challenges the masculine slant in the Artificial Intelligence (AI) view of the world. Alison Adam admirably fills the large gap in science and technology studies by showing us that gender bias is inscribed in AI-based computer systems. Her treatment of feminist epistemology, focusing on the ideas of the knowing subject, the nature of knowledge, rationality and language, are bound to make a significant and powerful contribution to AI studies. Drawing from theories by Donna Haraway and Sherry (...) Turkle, and using tools of feminist epistemology, Adam provides a sustained critique of AI which interestingly re-enforces many of the traditional criticisms of the AI project. Artificial Knowing is an esential read for those interested in gender studies, science and technology studies, and philosophical debates in AI. (shrink)

Thinking about how the law might decide whether to extend legal personhood to artificial agents provides a valuable testbed for philosophical theories of mind. Further, philosophical and legal theorising about personhood for artificial agents can be mutually informing. We investigate two case studies, drawing on legal discussions of the status of artificial agents. The first looks at the doctrinal difficulties presented by the contracts entered into by artificial agents. We conclude that it is not necessary or (...) desirable to postulate artificial agents as legal persons in order to account for such contracts. The second looks at the potential for according sophisticated artificial agents with legal personality with attendant constitutional protections similar to those accorded to humans. We investigate the validity of attributes that have been suggested as pointers of personhood, and conclude that they will take their place within a broader matrix of pragmatic, philosophical and extra-legal concepts. (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)

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)

Artificial life (also known as “ALife”) is a broad, interdisciplinary endeavor that studies life and life-like processes through simulation and synthesis. The goals of this activity include modelling and even creating life and life-like systems, as well as developing practical applications using intuitions and methods taken from living systems. Artificial life both illuminates traditional philosophical questions and raises new philosophical questions. Since both artificial life and philosophy investigate the essential nature of certain fundamental aspects of reality like (...) life and adaptation, artificial life offers philosophy a new perspective on these phenomena. This chapter provides an introduction to current research in artificial life and explains its philosophical implications. (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)

Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, (...) we critically explore the possibilities and challenges for virtue ethics from a computational perspective. Drawing on previous conceptual and technical work, we outline a version of artificial virtue based on moral functionalism, connectionist bottom–up learning, and eudaimonic reward. We then describe how core features of the outlined theory can be interpreted in terms of functionality, which in turn informs the design of components necessary for virtuous cognition. Finally, we present a comprehensive framework for the technical development of artificial virtuous agents and discuss how they can be implemented in moral environments. (shrink)

This paper discusses the problem of responsibility attribution raised by the use of artificial intelligence technologies. It is assumed that only humans can be responsible agents; yet this alone already raises many issues, which are discussed starting from two Aristotelian conditions for responsibility. Next to the well-known problem of many hands, the issue of “many things” is identified and the temporal dimension is emphasized when it comes to the control condition. Special attention is given to the epistemic condition, which (...) draws attention to the issues of transparency and explainability. In contrast to standard discussions, however, it is then argued that this knowledge problem regarding agents of responsibility is linked to the other side of the responsibility relation: the addressees or “patients” of responsibility, who may demand reasons for actions and decisions made by using AI. Inspired by a relational approach, responsibility as answerability thus offers an important additional, if not primary, justification for explainability based, not on agency, but on patiency. (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)

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)

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)

This new volume in the acclaimed Oxford Readings in Philosophy sereis offers a selection of the most important philosophical work being done in the new and fast-growing interdisciplinary area of artificial life. Artificial life research seeks to synthesize the characteristics of life by artificial means, particularly employing computer technology. The essays here explore such fascinating themes as the nature of life, the relation between life and mind, and the limits of technology.

Our ability to locate moral responsibility is often thought to be a necessary condition for conducting morally permissible medical practice, engaging in a just war, and other high-stakes endeavors. Yet, with increasing reliance upon artificially intelligent systems, we may be facing a wideningresponsibility gap, which, some argue, cannot be bridged by traditional concepts of responsibility. How then, if at all, can we make use of crucial emerging technologies? According to Colin Allen and Wendell Wallach, the advent of so-called ‘artificial (...) moral agents’ (AMAs) is inevitable. Still, this notion may seem to push back the problem, leaving those who have an interest in developing autonomous technology with a dilemma. We may need to scale-back our efforts at deploying AMAs (or at least maintain human oversight); otherwise, we must rapidly and drastically update our moral and legal norms in a way that ensures responsibility for potentially avoidable harms. This paper invokes contemporary accounts of responsibility in order to show how artificially intelligent systems might be held responsible. Although many theorists are concerned enough to develop artificial conceptions ofagencyor to exploit our present inability to regulate valuable innovations, the proposal here highlights the importance of—and outlines a plausible foundation for—a workable notion ofartificial moral responsibility. (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)

This book explores the role of artificial intelligence in the development of a claim that morality is person-made and rational. Professor Danielson builds moral robots that do better than amoral competitors in a tournament of games like the Prisoners Dilemma and Chicken. The book thus engages in current controversies over the adequacy of the received theory of rational choice. It sides with Gauthier and McClennan, who extend the devices of rational choice to include moral constraint. _Artificial Morality_ goes further, (...) by promoting communication, testing and copying of principles and by stressing empirical tests. (shrink)