There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models (...) and targets are picked out, how modeling inferences are justified, and the metaphysical status of models. (shrink)

In this 60th anniversary of Business & Society essay, we seek to make three main contributions at the intersection of governance and artificial intelligence. First, we aim to illuminate some of the deeper social, legal, organizational, and democratic challenges of rising AI adoption and resulting algorithmic power by reviewing AI research through a governance lens. Second, we propose an AI governance framework that aims to better assess AI challenges as well as how different governance modalities can support AI. At (...) the heart of our framework lies the governance forces that apply to institutions, organizations, and individuals, who ultimately provide, regulate, and use AI decision-making. We discuss how businesses may harness AI’s economic power through governance solutions without creating or amplifying societal biases and inequalities. Third, as part of our section on future research, we identify a set of governance trade-offs in AI adoption, suggest future research avenues to conceptually strengthen research on the governance of AI, and lay out key policy recommendations. (shrink)

Artificial insemination was the first conceptive technology to be widely used in agriculture. Whereas at the beginning of the twentieth century all cows in England and Wales were mated to bulls, by the end of the 1950s 60% conceived through artificial insemination. By then a national network of ‘cattle breeding centres’ brought AI within the reach of every farmer. In this paper I explore how artificial insemination, which had few supporters in the 1920s and 1930s, was transformed (...) into an ‘indispensable’ method for reproducing cattle. I discuss the factors that made organised AI possible , including changes in cultures of cattle breeding, novel State involvement in bovine reproduction, the rise of new ‘animal breeding research’ centres at Cambridge, Edinburgh and Reading universities, war preparations and central planning by the Milk Marketing Board . I go on to show that the unprecedented focus on bovine reproduction set in motion by the AI centres effectively generated new networks of reproductive research, through these the ‘biopower’ of the farm was incorporated into the clinic. The example of AI shows that by combining the history of reproductive technology in agriculture and medicine we can give a richer account of modern reproduction. (shrink)

Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for (...) computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent’s selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we will elucidate a process whereby an agent can work through an ethical problem to reach a solution that takes account of ethically relevant factors. (shrink)

Este artículo explora la integración de la IA en la comunicación académica para mejorar las capacidades cognitivas humanas. La concepción de la comunicación hombre-máquina (CMM), que considera las tecnologías basadas en la IA no como objetos interactivos, sino como sujetos comunicativos, plantea cuestiones más filosóficas en la comunicación académica. Es un hecho conocido que existe una mayor interacción entre los humanos y las máquinas, especialmente consolidada por la pandemia COVID-19, que intensificó el desarrollo del Sistema de Aprendizaje Adaptativo Individual, por (...) lo que necesariamente se requieren aportaciones de las IN para fortalecer la IA. Esto posicionó a la universidad en la yuxtaposición de asegurar la producción de individuos altamente talentosos que puedan continuar pensando más allá de lo pensable inteligentemente y permitir a los expertos en IA continuar construyendo algoritmos que puedan llevar el desarrollo de la tecnología al siguiente nivel. Para llevar a cabo tal tarea, la producción investigadora es primordial para conectar la universidad y la industria editorial. Este artículo examina de forma crítica componentes importantes e intenta hacer justicia a la emanación de preguntas críticas de los investigadores (NI), alimentando así el desarrollo de la tecnología (IA). (shrink)

The environmental costs and energy constraints have become emerging issues for the future development of Machine Learning (ML) and Artificial Intelligence (AI). So far, the discussion on environmental impacts of ML/AI lacks a perspective reaching beyond quantitative measurements of the energy-related research costs. Building on the foundations laid down by Schwartz et al., 2019 in the GreenAI initiative, our argument considers two interlinked phenomena, the gratuitous generalisation capability and the future where ML/AI performs the majority of quantifiable inductive inferences. (...) The gratuitous generalisation capability refers to a discrepancy between the cognitive demands of a task to be accomplished and the performance (accuracy) of a used ML/AI model. If the latter exceeds the former because the model was optimised to achieve the best possible accuracy, it becomes inefficient and its operation harmful to the environment. The future dominated by the non-anthropic induction describes a use of ML/AI so all-pervasive that most of the inductive inferences become furnished by ML/AI generalisations. The paper argues that the present debate deserves an expansion connecting the environmental costs of research and ineffective ML/AI uses (the issue of gratuitous generalisation capability) with the (near) future marked by the all-pervasive Human-Artificial Intelligence Nexus. (shrink)

In this paper I provide an exposition and critique of Johnson and Noorman’s (2014) three conceptualizations of the agential roles artificial systems can play. I argue that two of these conceptions are unproblematic: that of causally efficacious agency and “acting for” or surrogate agency. Their third conception, that of “autonomous agency,” however, is one I have reservations about. The authors point out that there are two ways in which the term “autonomy” can be used: there is, firstly, the engineering (...) sense of the term, which simply refers to the ability of some system to act independently of substantive human control. Secondly, there is the moral sense of the term, which has traditionally grounded many notions of human mor-al responsibility. I argue that the continued usage of “autonomy” in discussions of artificial agency complicates matters unnecessarily. This occurs in two ways: firstly, the condition of autonomy, even in its engineering sense, fails to accurately describe the way “autonomous” systems are developed in practice. Secondly, the continued usage of autonomy in the moral sense introduces unnecessary meta-physical baggage form the free will debate into discussions about moral agency. In order to understand the debate surrounding autonomy, we would therefore first need to settle many seemingly intractable metaphysical questions regarding the existence of free will in human beings. (shrink)

The growing field of machine morality has becoming increasingly concerned with how to develop artificial moral agents. However, there is little consensus on what constitutes an ideal moral agent let alone an artificial one. Leveraging a recent account of heroism in humans, the aim of this paper is to provide a prospective framework for conceptualizing, and in turn designing ideal artificial moral agents, namely those that would be considered heroic robots. First, an overview of what it means (...) to be an artificial moral agent is provided. Then, an overview of a recent account of heroism that seeks to define the construct as the dynamic and interactive integration of character strengths and situational constraints that afford the opportunity for moral behavior . With this as a foundation, a discussion is provided for what it might mean for a robot to be an ideal moral agent by proposing a dynamic and interactive connectionist model of robotic heroism. Given the limited accounts of robots engaging in moral behavior, a case for extending robotic moral capacities beyond just being a moral agent to the level of heroism is supported by drawing from exemplar situations where robots demonstrate heroism in popular film and fiction. (shrink)

Computer Science and Artificial Intelligence will be the twenty-first century logic development of the main power source, and in the twenty-first century will largely determine the face of logic. At least in the early twenty-first century, logic will focus on the following topics: how to deal with common sense reasoning in the logic of Eph coordination, non-monotonic and fault tolerance factors? how to make robots with human intelligence and creativity, as established from the empirical evidence used to guide future (...) action in the induction of judgments can be wrong? how the knowledge representation and knowledge reasoning, in particular, is based on the existing knowledge base and between the cognitive subject knowledge and the reasoning? how contextual factors, combined with a variety of natural language understanding and reasoning, so that intelligent robots to employing natural language for successful communication with people? . . . . And so on. (shrink)

The paper proposes a synthesis between human scientists and artificial representation learning models as a way of augmenting epistemic warrants of realist theories against various anti-realist attempts. Towards this end, the paper fleshes out unconceived alternatives not as a critique of scientific realism but rather a reinforcement, as it rejects the retrospective interpretations of scientific progress, which brought about the problem of alternatives in the first place. By utilising adversarial machine learning, the synthesis explores possibility spaces of available evidence (...) for unconceived alternatives providing modal knowledge of what is possible therein. As a result, the epistemic warrant of synthesised realist theories should emerge bolstered as the underdetermination by available evidence gets reduced. While shifting the realist commitment away from theoretical artefacts towards modalities of the possibility spaces, the synthesis comes out as a kind of perspectival modelling. (shrink)

Standard notions in philosophy of mind have a tendency to characterize socio-cognitive abilities as if they were unique to sophisticated human beings. However, assuming that it is likely that we are soon going to share a large part of our social lives with various kinds of artificial agents, it is important to develop a conceptual framework providing notions that are able to account for various types of social agents. Recent minimal approaches to socio-cognitive abilities such as mindreading and commitment (...) present a promising starting point from which one can expand the field of application not only to infants and non-human animals but also to artificial agents. Developing a minimal approach to the sociocognitive ability of acting jointly, I present a foundation for future discussions about the question of how our conception of sociality can be expanded to artificial agents. (shrink)

This essay introduces this special issue on virtue ethics in relation to military AI. It describes the current situation of military AI ethics as following that of AI ethics in general, caught between consequentialism and deontology. Virtue ethics serves as an alternative that can address some of the weaknesses of these dominant forms of ethics. The essay describes how the articles in the issue exemplify the value of virtue-related approaches for these questions, before ending with thoughts for further research.

У статті досліджується специфіка взаємозв’язку релігії, культури та штучного інтелекту (ШІ) у постмодерністському контексті сучасності. У цьому розумінні віртуалізація та штучний інтелект стають не просто інструментами, але й новим способом осмислення світу – вони кидають виклик традиційним уявленням про релігію, культуру, знання, істину й ідентичність. Автори закликають до осягнення можливих шляхів розвитку релігії та культури в постмодерному контексті та до пошуку гармонії між реальним і віртуальним, між традиційним та новаторським, між людським і штучним.

ABSTRACT The science of artificial intelligence (AI) is not as unemotional as it might first appear. Not only are researchers in the field now taking an interest in how to program affective capacities into artificial agents; there is also plenty of historical evidence that concerns about affect have been present in AI from the earliest years. Examination of archival materials from the 1940s and 1950s shows that affects (particularly as they circulate between men) have been a significant part (...) of innovation in AI from the beginning. This essay looks at one fragment of that history: the currents of affective and sexual interests in and around Walter Pitts, one of the important, eccentric, and little‐written‐about founders of AI. (shrink)

This article offers a critical perspective on efforts to build computational models of human emotional processes. I argue that current computational scientists are missing an opportunity to bring simplicity and clarity to emotion research by adopting an overly literal interpretation of psychological theory. Rather, hearkening back to arguments from the early days of cognitive science, I suggest an approach of reinterpreting psychological phenomena through the lens of computation. I illustrate this approach through models of emotional dynamics and cultural differences.

This article will focus on issues concerning the provision of artificial nutrition and hydration to patients who are extremely old, completely bedridden, and totally dependent on others. These patients have no advance directives, no malignancy, suffer from persistent but unstable disturbance of consciousness as well as severe cognitive impairment, and cannot eat sufficient amounts of food to maintain their lives. Should ANH be provided? Some would agree while others would maintain otherwise. The underlying values and normative theory behind each (...) argument are quite different. In this paper, I will present opinions, comments, and arguments concerning the provision of PANH to such patients and examine each using the Takahashi‘s three levels structure analysis. Utilitarianism is a fitting ethical theory for the third level in arguments against the provision of PANH to patients in question, and the non-religious sanctity of life doctrine covers the opposite position. (shrink)

In service marketing, AI assistants and self-service technology have become popular. As a result, it is critical to enrich the understanding of whether consumers react differently in the artificial intelligence service context in comparison with the human service context. This study examines the effect of assistant type on consumers’ decision-making. Through three experiments, this research finds that variety seeking will be higher when consumers are making decision in AI service environment. Furthermore, we tested uncertainty as the underlying mechanism. Moreover, (...) we demonstrated that this pattern is moderated by situational involvement. Specifically, in consumption contexts of high involvement, the consumers are less likely to seek variety, and in consumption contexts of low involvement, they prefer more variety. This research offers service providers new insights by revealing how, why, and when the interaction of AI technology influences consumers’ decision-making in service marketing. (shrink)

이 논문은 인공지능의 존재론적 지위를 평가하기 위한 두 개의 물음을 던진다. 하나는 인공지능이 개념을 가질 수 있는가 하는 물음이고, 다른 하나는 인공지능이 행위의 능력을 가졌는가 하는 물음이다. 개념 능력은 인공지능이 통상적인 언어의 형태로 주어지는 명령이나 정보를 능동적으로 이해하고 그것의 작동에 반영할 수 있기 위한 필요조건이다. 최근 인공지능 기술은 영상자료에서 비지도 학습의 방식으로 특정 범주의 사물을 식별해내는 성과를 거뒀지만, 이런 식별의 능력은 개념 능력의 필요조건도 충분조건도 아니다. 인공지능이 우리와 같은 개념을 가지도록 하는 것은 인간 사회의 언어 관행을 고스란히 학습시키는 방식으로 가능할 (...) 것인데, 이것은 불가능하지는 않지만 사실상 완결되기 어려운 목표다. 한편, 행위 능력에 대한 평가는 인공지능 프로그램이나 지능형 로봇 같은 인공물을 모종의 책임과 권리를 지닌 행위 주체로 간주할 수 있는가 하는 물음을 다루기 위한 열쇠다. 행위는 행위 주체와 환경 간의 상호작용으로, 행위의 실현에는 환경 속 대상에 대한 지각과 그것에 관한 동작의 협응, 달리 말하자면 감수자 체계와 행위자 체계의 통합이 필수적이다. 그리고 이러한 협응이나 통합의 배후에는 행위를 낳는 의도를 가지고 협응을 조율하는 존재, 즉 자아가 있다. 행위는 감수자 체계와 행위자 체계의 협응을 통해 자아의 의도를 실현하는 과정이다. 인공물의 작동이 이런 조건을 충족한다고 볼 이유는 아직 없다. 결국, 두 물음에 대한 이 논문의 대답은 부정적이거나 기껏해야 유보적이다. (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)