Results for 'Artificial Intelligence. '

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  1. Part II. A walk around the emerging new world. Russia in an emerging world / excerpt: from "Russia and the solecism of power" by David Holloway ; China in an emerging world.Constraints Excerpt: From "China'S. Demographic Prospects Toopportunities, Excerpt: From "China'S. Rise in Artificial Intelligence: Ingredientsand Economic Implications" by Kai-Fu Lee, Matt Sheehan, Latin America in an Emerging Worldsidebar: Governance Lessons From the Emerging New World: India, Excerpt: From "Latin America: Opportunities, Challenges for the Governance of A. Fragile Continent" by Ernesto Silva, Excerpt: From "Digital Transformation in Central America: Marginalization or Empowerment?" by Richard Aitkenhead, Benjamin Sywulka, the Middle East in an Emerging World Excerpt: From "the Islamic Republic of Iran in an Age of Global Transitions: Challenges for A. Theocratic Iran" by Abbas Milani, Roya Pakzad, Europe in an Emerging World Sidebar: Governance Lessons From the Emerging New World: Japan, Excerpt: From "Europe in the Global Race for Technological Leadership" by Jens Suedekum & Africa in an Emerging World Sidebar: Governance Lessons From the Emerging New Wo Bangladesh - 2020 - In George P. Shultz (ed.), A hinge of history: governance in an emerging new world. Stanford, California: Hoover Institution Press, Stanford University.
     
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  2. Evolutionary and religious perspectives on morality.Artificial Intelligence - forthcoming - Zygon.
  3. Otto Neumaier.Artificial Intelligence - 1987 - In Rainer P. Born (ed.), Artificial Intelligence: The Case Against. St Martin's Press. pp. 132.
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  4.  8
    Proceedings of the 1986 Conference on Theoretical Aspects of Reasoning about Knowledge: March 19-22, 1988, Monterey, California.Joseph Y. Halpern, International Business Machines Corporation, American Association of Artificial Intelligence, United States & Association for Computing Machinery - 1986
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  5. Jacques Ferber.Reactive Distributed Artificial - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 287.
     
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  6. Michael Wooldridge.Modeling Distributed Artificial - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 269.
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  7. Keith S. Decker.Intelligence Testbeds - 1996 - In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley. pp. 9--119.
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  8.  88
    Witness testimony evidence: argumentation, artificial intelligence, and law.Douglas Walton - 2007 - New York: Cambridge University Press.
    Recent work in artificial intelligence has increasingly turned to argumentation as a rich, interdisciplinary area of research that can provide new methods related to evidence and reasoning in the area of law. Douglas Walton provides an introduction to basic concepts, tools and methods in argumentation theory and artificial intelligence as applied to the analysis and evaluation of witness testimony. He shows how witness testimony is by its nature inherently fallible and sometimes subject to disastrous failures. At the same (...)
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  9. Artificial intelligence and the value of transparency.Joel Walmsley - 2021 - AI and Society 36 (2):585-595.
    Some recent developments in Artificial Intelligence—especially the use of machine learning systems, trained on big data sets and deployed in socially significant and ethically weighty contexts—have led to a number of calls for “transparency”. This paper explores the epistemological and ethical dimensions of that concept, as well as surveying and taxonomising the variety of ways in which it has been invoked in recent discussions. Whilst “outward” forms of transparency may be straightforwardly achieved, what I call “functional” transparency about the (...)
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  10.  5
    Reflective Artificial Intelligence.Peter R. Lewis & Ştefan Sarkadi - 2024 - Minds and Machines 34 (2):1-30.
    As artificial intelligence (AI) technology advances, we increasingly delegate mental tasks to machines. However, today’s AI systems usually do these tasks with an unusual imbalance of insight and understanding: new, deeper insights are present, yet many important qualities that a human mind would have previously brought to the activity are utterly absent. Therefore, it is crucial to ask which features of minds have we replicated, which are missing, and if that matters. One core feature that humans bring to tasks, (...)
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  11. Artificial Intelligence: Its Scope and Limits.James H. Fetzer - 1990 - Kluwer Academic Publishers.
    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 ..
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  12.  12
    Artificial Intelligence and the future of work.John-Stewart Gordon & David J. Gunkel - forthcoming - AI and Society:1-7.
    In this paper, we delve into the significant impact of recent advancements in Artificial Intelligence (AI) on the future landscape of work. We discuss the looming possibility of mass unemployment triggered by AI and the societal repercussions of this transition. Despite the challenges this shift presents, we argue that it also unveils opportunities to mitigate social inequalities, combat global poverty, and empower individuals to follow their passions. Amidst this discussion, we also touch upon the existential question of the purpose (...)
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  13. Artificial intelligence and the ‘Good Society’: the US, EU, and UK approach.Corinne Cath, Sandra Wachter, Brent Mittelstadt, Mariarosaria Taddeo & Luciano Floridi - 2018 - Science and Engineering Ethics 24 (2):505-528.
    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 (...)
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  14. The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence.David Watson - 2019 - Minds and Machines 29 (3):417-440.
    Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised (...)
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  15. Artificial Intelligence and Artificial Sociality: Sociological Interpretation and Interdisciplinary Approach.Vladimir Menshikov, Vera Komarova, Ieva Bolakova & Andrejs Radionovs - 2024 - Filosofija. Sociologija 35 (2).
    The subject of this study is the participants in artificial sociality (humans and artificial intelligence (AI) tools) and communication between them. The first section analyses (using Luhmann’s methodology) communication as the basis of sociality. The second section shows how AI tools became social technologies in the framework of artificial sociality. The third section describes experimental communication between authors and AI tools (the case of ChatGPT). For the first time in the Baltic countries, the authors examined sociological, humanitarian, (...)
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  16. Artificial Intelligence and Robot Responsibilities: Innovating Beyond Rights.Hutan Ashrafian - 2015 - Science and Engineering Ethics 21 (2):317-326.
    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 (...)
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  17. Artificial intelligence and African conceptions of personhood.C. S. Wareham - 2021 - Ethics and Information Technology 23 (2):127-136.
    Under what circumstances if ever ought we to grant that Artificial Intelligences (AI) are persons? The question of whether AI could have the high degree of moral status that is attributed to human persons has received little attention. What little work there is employs western conceptions of personhood, while non-western approaches are neglected. In this article, I discuss African conceptions of personhood and their implications for the possibility of AI persons. I focus on an African account of personhood that (...)
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  18. Aligning artificial intelligence with moral intuitions: an intuitionist approach to the alignment problem.Dario Cecchini, Michael Pflanzer & Veljko Dubljevic - 2024 - AI and Ethics:1-11.
    As artificial intelligence (AI) continues to advance, one key challenge is ensuring that AI aligns with certain values. However, in the current diverse and democratic society, reaching a normative consensus is complex. This paper delves into the methodological aspect of how AI ethicists can effectively determine which values AI should uphold. After reviewing the most influential methodologies, we detail an intuitionist research agenda that offers guidelines for aligning AI applications with a limited set of reliable moral intuitions, each underlying (...)
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  19. Artificial Intelligence, Values, and Alignment.Iason Gabriel - 2020 - Minds and Machines 30 (3):411-437.
    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 (...)
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  20. May Artificial Intelligence take health and sustainability on a honeymoon? Towards green technologies for multidimensional health and environmental justice.Cristian Moyano-Fernández, Jon Rueda, Janet Delgado & Txetxu Ausín - 2024 - Global Bioethics 35 (1).
    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 (...)
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  21. Artificial Intelligence: The Very Idea.John Haugeland - 1985 - Cambridge: MIT Press.
    The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...
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  22. Artificial Intelligence and Scientific Method.Donald Gillies - 1996 - Oxford and New York: Oxford University Press.
    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 (...)
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  23.  35
    Artificial intelligence and the doctor–patient relationship expanding the paradigm of shared decision making.Giorgia Lorenzini, Laura Arbelaez Ossa, David Martin Shaw & Bernice Simone Elger - 2023 - Bioethics 37 (5):424-429.
    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 (...)
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  24.  66
    Might artificial intelligence become part of the person, and what are the key ethical and legal implications?Jan Christoph Bublitz - forthcoming - AI and Society:1-12.
    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 (...)
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  25. Trusting artificial intelligence in cybersecurity is a double-edged sword.Mariarosaria Taddeo, Tom McCutcheon & Luciano Floridi - 2019 - Philosophy and Technology 32 (1):1-15.
    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 (...)
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  26. Artificial Intelligence and Neuroscience Research: Theologico-Philosophical Implications for the Christian Notion of the Human Person.Justin Nnaemeka Onyeukaziri - 2023 - Maritain Studies/Etudes Maritainiennes 39:85-103.
    This paper explores the theological and philosophical implications of artificial intelligence (AI) and Neuroscience research on the Christian’s notion of the human person. The paschal mystery of Christ is the intuitive foundation of Christian anthropology. In the intellectual history of the Christianity, Platonism and Aristotelianism have been employed to articulate the Christian philosophical anthropology. The Aristotelian systematization has endured to this era. Since the modern period of the Western intellectual history, Aristotelianism has been supplanted by the positive sciences as (...)
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  27. Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions.Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith & Simone Stumpf - 2024 - Information Fusion 106 (June 2024).
    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 (...)
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  28. Beneficial Artificial Intelligence Coordination by means of a Value Sensitive Design Approach.Steven Umbrello - 2019 - Big Data and Cognitive Computing 3 (1):5.
    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 (...)
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  29.  54
    Conversational Artificial Intelligence in Psychotherapy: A New Therapeutic Tool or Agent?Jana Sedlakova & Manuel Trachsel - 2022 - American Journal of Bioethics 23 (5):4-13.
    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 (...)
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  30.  21
    Might artificial intelligence become part of the person, and what are the key ethical and legal implications?Jan Christoph Bublitz - forthcoming - AI and Society:1-12.
    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 (...)
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  31. African Reasons Why Artificial Intelligence Should Not Maximize Utility.Thaddeus Metz - 2021 - In Beatrice Dedaa Okyere-Manu (ed.), African Values, Ethics, and Technology: Questions, Issues, and Approaches. Palgrave-Macmillan. pp. 55-72.
    Insofar as artificial intelligence is to be used to guide automated systems in their interactions with humans, the dominant view is probably that it would be appropriate to programme them to maximize (expected) utility. According to utilitarianism, which is a characteristically western conception of moral reason, machines should be programmed to do whatever they could in a given circumstance to produce in the long run the highest net balance of what is good for human beings minus what is bad (...)
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  32. Artificial Intelligence: A Philosophical Introduction.Jack Copeland - 1993 - Wiley-Blackwell.
    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. (...)
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  33. Artificial Intelligence as a Means to Moral Enhancement.Michał Klincewicz - 2016 - Studies in Logic, Grammar and Rhetoric 48 (1):171-187.
    This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015). The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artifi-cial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative theories, such as Kantianism or (...)
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  34. Artificial intelligence, transparency, and public decision-making.Karl de Fine Licht & Jenny de Fine Licht - 2020 - AI and Society 35 (4):917-926.
    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 (...)
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  35. Artificial Intelligence: A Philosophical Introduction.B. Jack Copeland - 1993 - Cambridge: Blackwell.
    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 (...)
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  36.  28
    Artificial intelligence in local governments: perceptions of city managers on prospects, constraints and choices.Tan Yigitcanlar, Duzgun Agdas & Kenan Degirmenci - 2023 - AI and Society 38 (3):1135-1150.
    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 (...)
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  37. Artificial Intelligence, Jobs and the Future of Work: Racing with the Machines.Alban Duka & Edvard P. G. Bruun - 2018 - Basic Income Studies 13 (2).
    Artificial intelligence is rapidly entering our daily lives in the form of driverless cars, automated online assistants and virtual reality experiences. In so doing, AI has already substituted human employment in areas that were previously thought to be uncomputerizable. Based on current trends, the technological displacement of labor is predicted to be significant in the future – if left unchecked this will lead to catastrophic societal unemployment levels. This paper presents a means to mitigate future technological unemployment through the (...)
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  38. Artificial Intelligence and Legal Disruption: A New Model for Analysis.John Danaher, Hin-Yan Liu, Matthijs Maas, Luisa Scarcella, Michaela Lexer & Leonard Van Rompaey - forthcoming - Law, Innovation and Technology.
    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: (...)
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  39.  69
    Artificial intelligence in support of the circular economy: ethical considerations and a path forward.Huw Roberts, Joyce Zhang, Ben Bariach, Josh Cowls, Ben Gilburt, Prathm Juneja, Andreas Tsamados, Marta Ziosi, Mariarosaria Taddeo & Luciano Floridi - forthcoming - AI and Society:1-14.
    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 (...)
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  40.  55
    Aligning artificial intelligence with human values: reflections from a phenomenological perspective.Shengnan Han, Eugene Kelly, Shahrokh Nikou & Eric-Oluf Svee - 2022 - AI and Society 37 (4):1383-1395.
    Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values (...)
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  41. Artificial intelligence meets natural stupidity.Drew McDermott - 1981 - In J. Haugel (ed.), Mind Design. MIT Press. pp. 5-18.
  42. Artificial Intelligence, Social Media and Depression. A New Concept of Health-Related Digital Autonomy.Sebastian Laacke, Regina Mueller, Georg Schomerus & Sabine Salloch - 2021 - American Journal of Bioethics 21 (7):4-20.
    The development of artificial intelligence (AI) in medicine raises fundamental ethical issues. As one example, AI systems in the field of mental health successfully detect signs of mental disorders, such as depression, by using data from social media. These AI depression detectors (AIDDs) identify users who are at risk of depression prior to any contact with the healthcare system. The article focuses on the ethical implications of AIDDs regarding affected users’ health-related autonomy. Firstly, it presents the (ethical) discussion of (...)
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  43.  53
    Artificial intelligence is an oxymoron.Jakob Svensson - 2023 - AI and Society 38 (1):363-372.
    Departing from popular imaginations around artificial intelligence (AI), this article engages in the I in the AI acronym but from perspectives outside of mathematics, computer science and machine learning. When intelligence is attended to here, it most often refers to narrow calculating tasks. This connotation to calculation provides AI an image of scientificity and objectivity, particularly attractive in societies with a pervasive desire for numbers. However, as is increasingly apparent today, when employed in more general areas of our messy (...)
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  44.  49
    Some Artificial Intelligence Tools for Argument Evaluation: An Introduction.Douglas Walton - 2016 - Argumentation 30 (3):317-340.
    Even though tools for identifying and analyzing arguments are now in wide use in the field of argumentation studies, so far there is a paucity of resources for evaluating real arguments, aside from using deductive logic or Bayesian rules that apply to inductive arguments. In this paper it is shown that recent developments in artificial intelligence in the area of computational systems for modeling defeasible argumentation reveal a different approach that is currently making interesting progress. It is shown how (...)
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  45. Artificial Intelligence Systems, Responsibility and Agential Self-Awareness.Lydia Farina - 2022 - In Vincent C. Müller (ed.), Philosophy and Theory of Artificial Intelligence 2021. Berlin, Germany: pp. 15-25.
    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 (...)
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  46. Artificial Intelligence: The Basics.Kevin Warwick - 2011 - Routledge.
    'if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in (...)
     
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  47. Artificial intelligence, deepfakes and a future of ectypes.Luciano Floridi - 2018 - Philosophy and Technology 31 (3):317-321.
    AI, especially in the case of Deepfakes, has the capacity to undermine our confidence in the original, genuine, authentic nature of what we see and hear. And yet digital technologies, in the form of databases and other detection tools also make it easier to spot forgeries and to establish the authenticity of a work. Using the notion of ectypes, this paper discusses current conceptions of authenticity and reproduction and examines how, in the future, these might be adapted for use in (...)
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  48. Artificial intelligence crime: an interdisciplinary analysis of foreseeable threats and solutions.Thomas C. King, Nikita Aggarwal, Mariarosaria Taddeo & Luciano Floridi - 2019 - Science and Engineering Ethics 26 (1):89-120.
    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 (...)
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  49. Can Artificial Intelligence Make Art?Elzė Sigutė Mikalonytė & Markus Kneer - 2022 - ACM Transactions on Human-Robot Interactions.
    In two experiments (total N=693) we explored whether people are willing to consider paintings made by AI-driven robots as art, and robots as artists. Across the two experiments, we manipulated three factors: (i) agent type (AI-driven robot v. human agent), (ii) behavior type (intentional creation of a painting v. accidental creation), and (iii) object type (abstract v. representational painting). We found that people judge robot paintings and human painting as art to roughly the same extent. However, people are much less (...)
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  50. Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care?Alex John London - 2022 - Cell Reports Medicine 100622 (3):1-8.
    There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to overcome structural problems in the culture and practice of medicine and the organization of health systems that impact the data from which AI models are built, the environments into which they will be deployed, and the practices and incentives that structure their (...)
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