Results for 'AI and Ethics'

967 found
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  1.  57
    Generative AI and Ethical Analysis.John McMillan - 2023 - American Journal of Bioethics 23 (10):42-44.
    Cohen (2023), Rahimzadeh and colleagues (2023), and Porsdam Mann and colleagues (2023) have written thorough and well-canvassed pieces about the ethical and conceptual challenges of large language...
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  2.  61
    AI and Ethics: Shedding Light on the Black Box.Katrina Ingram - 2020 - International Review of Information Ethics 28.
    Artificial Intelligence is playing an increasingly prevalent role in our lives. Whether its landing a job interview, getting a bank loan or accessing a government program, organizations are using automated systems informed by AI enabled technologies in ways that have significant consequences for people. At the same time, there is a lack of transparency around how AI technologies work and whether they are ethical, fair or accurate. This paper examines a body of literature related to the ethical considerations surrounding the (...)
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  3. AI and Ethics.Hannah H. Kim - 2020 - In David Weitzner, Issues in business ethics and corporate social responsibility: selections from SAGE business researcher. Los Angeles: SAGE reference.
     
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  4.  79
    AI and Ethics When Human Beings Collaborate With AI Agents.José J. Cañas - 2022 - Frontiers in Psychology 13.
    The relationship between a human being and an AI system has to be considered as a collaborative process between two agents during the performance of an activity. When there is a collaboration between two people, a fundamental characteristic of that collaboration is that there is co-supervision, with each agent supervising the actions of the other. Such supervision ensures that the activity achieves its objectives, but it also means that responsibility for the consequences of the activity is shared. If there is (...)
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  5.  50
    Possibilities and ethical issues of entrusting nursing tasks to robots and artificial intelligence.Tomohide Ibuki, Ai Ibuki & Eisuke Nakazawa - 2024 - Nursing Ethics 31 (6):1010-1020.
    In recent years, research in robotics and artificial intelligence (AI) has made rapid progress. It is expected that robots and AI will play a part in the field of nursing and their role might broaden in the future. However, there are areas of nursing practice that cannot or should not be entrusted to robots and AI, because nursing is a highly humane practice, and therefore, there would, perhaps, be some practices that should not be replicated by robots or AI. Therefore, (...)
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  6. AI and the expert; a blueprint for the ethical use of opaque AI.Amber Ross - 2022 - AI and Society (2022):Online.
    The increasing demand for transparency in AI has recently come under scrutiny. The question is often posted in terms of “epistemic double standards”, and whether the standards for transparency in AI ought to be higher than, or equivalent to, our standards for ordinary human reasoners. I agree that the push for increased transparency in AI deserves closer examination, and that comparing these standards to our standards of transparency for other opaque systems is an appropriate starting point. I suggest that a (...)
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  7. AI and society: a virtue ethics approach.Mirko Farina, Petr Zhdanov, Artur Karimov & Andrea Lavazza - 2024 - AI and Society 39 (3):1127-1140.
    Advances in artificial intelligence and robotics stand to change many aspects of our lives, including our values. If trends continue as expected, many industries will undergo automation in the near future, calling into question whether we can still value the sense of identity and security our occupations once provided us with. Likewise, the advent of social robots driven by AI, appears to be shifting the meaning of numerous, long-standing values associated with interpersonal relationships, like friendship. Furthermore, powerful actors’ and institutions’ (...)
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  8.  87
    Trust and ethics in AI.Hyesun Choung, Prabu David & Arun Ross - 2023 - AI and Society 38 (2):733-745.
    With the growing influence of artificial intelligence (AI) in our lives, the ethical implications of AI have received attention from various communities. Building on previous work on trust in people and technology, we advance a multidimensional, multilevel conceptualization of trust in AI and examine the relationship between trust and ethics using the data from a survey of a national sample in the U.S. This paper offers two key dimensions of trust in AI—human-like trust and functionality trust—and presents a multilevel (...)
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  9.  84
    AI led ethical digital transformation: framework, research and managerial implications.Kumar Saurabh, Ridhi Arora, Neelam Rani, Debasisha Mishra & M. Ramkumar - 2022 - Journal of Information, Communication and Ethics in Society 20 (2):229-256.
    Purpose Digital transformation leverages digital technologies to change current processes and introduce new processes in any organisation’s business model, customer/user experience and operational processes. Artificial intelligence plays a significant role in achieving DT. As DT is touching each sphere of humanity, AI led DT is raising many fundamental questions. These questions raise concerns for the systems deployed, how they should behave, what risks they carry, the monitoring and evaluation control we have in hand, etc. These issues call for the need (...)
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  10.  53
    Robots, AI, and Assisted Dying: Ethical and Philosophical Considerations.Ryan Tonkens - 2015 - In Jukka Varelius & Michael Cholbi, New Directions in the Ethics of Assisted Suicide and Euthanasia. Cham: Springer Verlag. pp. 279-298.
    The focus of this chapter is on some of the ethical and philosophical issues at the intersection of robotics and artificial intelligence (AI) applications in the health care sector and medical assistance in dying (e.g. physician-assisted suicide and euthanasia), including: (1) Is there a role for robotic systems/AI to play in the orchestration or delivery of assisted dying?; (2) Can the use of robotic systems/AI make the orchestration of assisted dying more ethical?; and (3) What insights can be generated in (...)
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  11. AI and robot ethics.John Tasioulas - 2019 - In David Edmonds, Ethics and the Contemporary World. New York: Routledge.
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  12.  91
    Generative AI and human–robot interaction: implications and future agenda for business, society and ethics.Bojan Obrenovic, Xiao Gu, Guoyu Wang, Danijela Godinic & Ilimdorjon Jakhongirov - forthcoming - AI and Society:1-14.
    The revolution of artificial intelligence (AI), particularly generative AI, and its implications for human–robot interaction (HRI) opened up the debate on crucial regulatory, business, societal, and ethical considerations. This paper explores essential issues from the anthropomorphic perspective, examining the complex interplay between humans and AI models in societal and corporate contexts. We provided a comprehensive review of existing literature on HRI, with a special emphasis on the impact of generative models such as ChatGPT. The scientometric study posits that due to (...)
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  13.  46
    The social and ethical impacts of artificial intelligence in agriculture: mapping the agricultural AI literature.Mark Ryan - 2023 - AI and Society 38 (6):2473-2485.
    This paper will examine the social and ethical impacts of using artificial intelligence (AI) in the agricultural sector. It will identify what are some of the most prevalent challenges and impacts identified in the literature, how this correlates with those discussed in the domain of AI ethics, and are being implemented into AI ethics guidelines. This will be achieved by examining published articles and conference proceedings that focus on societal or ethical impacts of AI in the agri-food sector, (...)
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  14.  74
    Generative AI and medical ethics: the state of play.Hazem Zohny, Sebastian Porsdam Mann, Brian D. Earp & John McMillan - 2024 - Journal of Medical Ethics 50 (2):75-76.
    Since their public launch, a little over a year ago, large language models (LLMs) have inspired a flurry of analysis about what their implications might be for medical ethics, and for society more broadly. 1 Much of the recent debate has moved beyond categorical evaluations of the permissibility or impermissibility of LLM use in different general contexts (eg, at work or school), to more fine-grained discussions of the criteria that should govern their appropriate use in specific domains or towards (...)
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  15.  28
    Moral distance, AI, and the ethics of care.Carolina Villegas-Galaviz & Kirsten Martin - forthcoming - AI and Society:1-12.
    This paper investigates how the introduction of AI to decision making increases moral distance and recommends the ethics of care to augment the ethical examination of AI decision making. With AI decision making, face-to-face interactions are minimized, and decisions are part of a more opaque process that humans do not always understand. Within decision-making research, the concept of moral distance is used to explain why individuals behave unethically towards those who are not seen. Moral distance abstracts those who are (...)
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  16.  92
    AI and law: ethical, legal, and socio-political implications.John-Stewart Gordon - 2021 - AI and Society 36 (2):403-404.
  17. Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision Making.Suzanne Https://Orcidorg Tolmeijer, Markus Https://Orcidorg Christen, Serhiy Kandul, Markus Https://Orcidorg Kneer & Abraham Https://Orcidorg Bernstein - 2022 - Proceedings of the 2022 Chi Conference on Human Factors in Computing Systems 160:160:1–17.
    While artificial intelligence (AI) is increasingly applied for decision-making processes, ethical decisions pose challenges for AI applications. Given that humans cannot always agree on the right thing to do, how would ethical decision-making by AI systems be perceived and how would responsibility be ascribed in human-AI collaboration? In this study, we investigate how the expert type (human vs. AI) and level of expert autonomy (adviser vs. decider) influence trust, perceived responsibility, and reliance. We find that participants consider humans to be (...)
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  18. Ethics of generative AI and manipulation: a design-oriented research agenda.Michael Klenk - 2024 - Ethics and Information Technology 26 (1):1-15.
    Generative AI enables automated, effective manipulation at scale. Despite the growing general ethical discussion around generative AI, the specific manipulation risks remain inadequately investigated. This article outlines essential inquiries encompassing conceptual, empirical, and design dimensions of manipulation, pivotal for comprehending and curbing manipulation risks. By highlighting these questions, the article underscores the necessity of an appropriate conceptualisation of manipulation to ensure the responsible development of Generative AI technologies.
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  19.  57
    Exploring the phenomenon and ethical issues of AI paternalism in health apps.Michael Kühler - 2021 - Bioethics 36 (2):194-200.
    Bioethics, Volume 36, Issue 2, Page 194-200, February 2022.
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  20.  20
    Emotionalized AI and the meaningfulness gap: an AI ethics perspective.Masoud Toossi Saeidi - forthcoming - AI and Society:1-11.
    This paper demonstrates that with increased philosophical scrutiny regarding the absurdity of life and meaningful living, the development of “Emotionalized AI” falls under ethical considerations. In this context, contemporary philosophical discussions on the meaning of life—as articulated by thinkers like Thomas Nagel, Joshua Seachris, Thaddeus Metz, and Susan Wolf—intersect with recent years’ reviews of AI ethics, particularly those related to meaningful relationships. The main analysis is conducted by explaining a philosophical perspective on meaningful life and revisiting AI ethics (...)
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  21.  81
    Artificial Intelligence and Robotics in Nursing: Ethics of Caring as a Guide to Dividing Tasks Between AI and Humans.Felicia Stokes & Amitabha Palmer - 2020 - Nursing Philosophy 21 (4):e12306.
    Nurses have traditionally been regarded as clinicians that deliver compassionate, safe, and empathetic health care (Nurses again outpace other professions for honesty & ethics, 2018). Caring is a fundamental characteristic, expectation, and moral obligation of the nursing and caregiving professions (Nursing: Scope and standards of practice, American Nurses Association, Silver Spring, MD, 2015). Along with caring, nurses are expected to undertake ever‐expanding duties and complex tasks. In part because of the growing physical, intellectual and emotional demandingness, of nursing as (...)
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  22. The Ethics of Medical AI and the Physician-Patient Relationship.Sally Dalton-Brown - 2020 - Cambridge Quarterly of Healthcare Ethics 29 (1):115-121.
    :This article considers recent ethical topics relating to medical AI. After a general discussion of recent medical AI innovations, and a more analytic look at related ethical issues such as data privacy, physician dependency on poorly understood AI helpware, bias in data used to create algorithms post-GDPR, and changes to the patient–physician relationship, the article examines the issue of so-called robot doctors. Whereas the so-called democratization of healthcare due to health wearables and increased access to medical information might suggest a (...)
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  23.  34
    Trustworthy artificial intelligence and ethical design: public perceptions of trustworthiness of an AI-based decision-support tool in the context of intrapartum care.Angeliki Kerasidou, Antoniya Georgieva & Rachel Dlugatch - 2023 - BMC Medical Ethics 24 (1):1-16.
    BackgroundDespite the recognition that developing artificial intelligence (AI) that is trustworthy is necessary for public acceptability and the successful implementation of AI in healthcare contexts, perspectives from key stakeholders are often absent from discourse on the ethical design, development, and deployment of AI. This study explores the perspectives of birth parents and mothers on the introduction of AI-based cardiotocography (CTG) in the context of intrapartum care, focusing on issues pertaining to trust and trustworthiness.MethodsSeventeen semi-structured interviews were conducted with birth parents (...)
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  24.  56
    AI assisted ethics.Amitai Etzioni & Oren Etzioni - 2016 - Ethics and Information Technology 18 (2):149-156.
    The growing number of ‘smart’ instruments, those equipped with AI, has raised concerns because these instruments make autonomous decisions; that is, they act beyond the guidelines provided them by programmers. Hence, the question the makers and users of smart instrument face is how to ensure that these instruments will not engage in unethical conduct. The article suggests that to proceed we need a new kind of AI program—oversight programs—that will monitor, audit, and hold operational AI programs accountable.
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  25. Ethics of AI and Cybersecurity When Sovereignty is at Stake.Paul Timmers - 2019 - Minds and Machines 29 (4):635-645.
    Sovereignty and strategic autonomy are felt to be at risk today, being threatened by the forces of rising international tensions, disruptive digital transformations and explosive growth of cybersecurity incidents. The combination of AI and cybersecurity is at the sharp edge of this development and raises many ethical questions and dilemmas. In this commentary, I analyse how we can understand the ethics of AI and cybersecurity in relation to sovereignty and strategic autonomy. The analysis is followed by policy recommendations, some (...)
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  26.  30
    Business Data Ethics: Emerging Models for Governing AI and Advanced Analytics.Dennis Hirsch, Timothy Bartley, Aravind Chandrasekaran, Davon Norris, Srinivasan Parthasarathy & Piers Norris Turner - 2023 - Springer.
    This open access book explains how leading business organizations attempt to achieve the responsible and ethical use of artificial intelligence (AI) and other advanced information technologies. These technologies can produce tremendous insights and benefits. But they can also invade privacy, perpetuate bias, and otherwise injure people and society. To use these technologies successfully, organizations need to implement them responsibly and ethically. The question is: how to do this? Data ethics management, and this book, provide some answers. -/- The authors (...)
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  27. More Process, Less Principles: The Ethics of Deploying AI and Robotics in Medicine.Amitabha Palmer & David Schwan - 2024 - Cambridge Quarterly of Healthcare Ethics 33 (1):121-134.
    Current national and international guidelines for the ethical design and development of artificial intelligence (AI) and robotics emphasize ethical theory. Various governing and advisory bodies have generated sets of broad ethical principles, which institutional decisionmakers are encouraged to apply to particular practical decisions. Although much of this literature examines the ethics of designing and developing AI and robotics, medical institutions typically must make purchase and deployment decisions about technologies that have already been designed and developed. The primary problem facing (...)
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  28.  15
    The Rise of Particulars: AI and the Ethics of Care.David Weinberger - 2024 - Philosophies 9 (1):26.
    Machine learning (ML) trains itself by discovering patterns of correlations that can be applied to new inputs. That is a very powerful form of generalization, but it is also very different from the sort of generalization that the west has valorized as the highest form of truth, such as universal laws in some of the sciences, or ethical principles and frameworks in moral reasoning. Machine learning’s generalizations synthesize the general and the particular in a new way, creating a multidimensional model (...)
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  29. Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI.Juan Manuel Durán & Karin Rolanda Jongsma - 2021 - Journal of Medical Ethics 47 (5):medethics - 2020-106820.
    The use of black box algorithms in medicine has raised scholarly concerns due to their opaqueness and lack of trustworthiness. Concerns about potential bias, accountability and responsibility, patient autonomy and compromised trust transpire with black box algorithms. These worries connect epistemic concerns with normative issues. In this paper, we outline that black box algorithms are less problematic for epistemic reasons than many scholars seem to believe. By outlining that more transparency in algorithms is not always necessary, and by explaining that (...)
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  30.  27
    Artificial Aesthetics and Ethical Ambiguity: Exploring Business Ethics in the Context of AI-driven Creativity.Cheng Xu, Yanqi Sun & Haibo Zhou - forthcoming - Journal of Business Ethics:1-22.
    In an era of technological ubiquity, artificial intelligence (AI) is reshaping not only industries but also fundamental human experiences, including artistic creativity. Rooted in a Posthumanist theoretical framework, this research scrutinizes the intricate ethical and aesthetic challenges that artists confront in AI-enabled art creation, with a particular focus on a novel phenomenon we term 'aesthetic loss of control.’ This phenomenon bears significant implications for notions of authorship, copyright, and business ethics in the art industry. Utilizing a mixed-methods approach, our (...)
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  31.  96
    Cognitive, emotive, and ethical aspects of decision making in humans and in AI.Iva Smit, Wendell Wallach & G. E. Lasker (eds.) - 2005 - Windsor, Ont.: International Institute for Advanced Studies in Systems Research and Cybernetics.
  32.  13
    AI and the falling sky: interrogating X-Risk.Nancy S. Jecker, Caesar Alimsinya Atuire, Jean-Christophe Bélisle-Pipon, Vardit Ravitsky & Anita Ho - 2024 - Journal of Medical Ethics 50 (12):811-817.
    The Buddhist Jātaka tells the tale of a hare lounging under a palm tree who becomes convinced the Earth is coming to an end when a ripe bael fruit falls on its head. Soon all the hares are running; other animals join them, forming a stampede of deer, boar, elk, buffalo, wild oxen, rhinoceros, tigers and elephants, loudly proclaiming the earth is ending.1 In the American retelling, the hare is ‘chicken little,’ and the exaggerated fear is that the sky is (...)
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  33.  20
    AI Through Ethical Lenses: A Discourse Analysis of Guidelines for AI in Healthcare.Laura Arbelaez Ossa, Stephen R. Milford, Michael Rost, Anja K. Leist, David M. Shaw & Bernice S. Elger - 2024 - Science and Engineering Ethics 30 (3):1-21.
    While the technologies that enable Artificial Intelligence (AI) continue to advance rapidly, there are increasing promises regarding AI’s beneficial outputs and concerns about the challenges of human–computer interaction in healthcare. To address these concerns, institutions have increasingly resorted to publishing AI guidelines for healthcare, aiming to align AI with ethical practices. However, guidelines as a form of written language can be analyzed to recognize the reciprocal links between its textual communication and underlying societal ideas. From this perspective, we conducted a (...)
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  34. Smart Health : The Intersection of IoT, AI, and Ethical Challenges in Healthcare.Rajiv Iyer & Poornima Mahesh - 2025 - In Bhupindara Siṅgha, Christian Kaunert, Balamurugan Balusamy & Rajesh Kumar Dhanaraj, Computational intelligence in healthcare law: AI for ethical governance and regulatory challenges. Boca Raton: Chapman & Hall, CRC Press.
     
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  35.  42
    AI research ethics is in its infancy: the EU’s AI Act can make it a grown-up.Anaïs Resseguier & Fabienne Ufert - 2024 - Research Ethics 20 (2):143-155.
    As the artificial intelligence (AI) ethics field is currently working towards its operationalisation, ethics review as carried out by research ethics committees (RECs) constitutes a powerful, but so far underdeveloped, framework to make AI ethics effective in practice at the research level. This article contributes to the elaboration of research ethics frameworks for research projects developing and/or using AI. It highlights that these frameworks are still in their infancy and in need of a structure and (...)
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  36.  78
    Ethics of AI and Health Care: Towards a Substantive Human Rights Framework.S. Matthew Liao - 2023 - Topoi 42 (3):857-866.
    There is enormous interest in using artificial intelligence (AI) in health care contexts. But before AI can be used in such settings, we need to make sure that AI researchers and organizations follow appropriate ethical frameworks and guidelines when developing these technologies. In recent years, a great number of ethical frameworks for AI have been proposed. However, these frameworks have tended to be abstract and not explain what grounds and justifies their recommendations and how one should use these recommendations in (...)
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  37. Bridging East-West Differences in Ethics Guidance for AI and Robots.Nancy S. Jecker & Eisuke Nakazawa - 2022 - AI 3 (3):764-777.
    Societies of the East are often contrasted with those of the West in their stances toward technology. This paper explores these perceived differences in the context of international ethics guidance for artificial intelligence (AI) and robotics. Japan serves as an example of the East, while Europe and North America serve as examples of the West. The paper’s principal aim is to demonstrate that Western values predominate in international ethics guidance and that Japanese values serve as a much-needed corrective. (...)
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  38. Combating Disinformation with AI: Epistemic and Ethical Challenges.Benjamin Lange & Ted Lechterman - 2021 - IEEE International Symposium on Ethics in Engineering, Science and Technology (ETHICS) 1:1-5.
    AI-supported methods for identifying and combating disinformation are progressing in their development and application. However, these methods face a litany of epistemic and ethical challenges. These include (1) robustly defining disinformation, (2) reliably classifying data according to this definition, and (3) navigating ethical risks in the deployment of countermeasures, which involve a mixture of harms and benefits. This paper seeks to expose and offer preliminary analysis of these challenges.
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  39.  27
    Correction: Ethics of AI and Health Care: Towards a Substantive Human Rights Framework.S. Matthew Liao - 2023 - Topoi 42 (3):903-903.
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  40.  35
    Ethics and Privacy in AI and Big Data: Implementing Responsible Research and Innovation.Bernd Carsten Stahl & David Wright - 2018 - IEEE Security and Privacy 16 (3):26-33.
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  41.  11
    AI and the iterable epistopics of risk.Andy Crabtree, Glenn McGarry & Lachlan Urquhart - forthcoming - AI and Society:1-14.
    The risks AI presents to society are broadly understood to be manageable through ‘general calculus’, i.e., general frameworks designed to enable those involved in the development of AI to apprehend and manage risk, such as AI impact assessments, ethical frameworks, emerging international standards, and regulations. This paper elaborates how risk is apprehended and managed by a regulator, developer and cyber-security expert. It reveals that risk and risk management is dependent on mundane situated practices not encapsulated in general calculus. Situated practice (...)
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  42.  48
    Design publicity of black box algorithms: a support to the epistemic and ethical justifications of medical AI systems.Andrea Ferrario - 2022 - Journal of Medical Ethics 48 (7):492-494.
    In their article ‘Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI’, Durán and Jongsma discuss the epistemic and ethical challenges raised by black box algorithms in medical practice. The opacity of black box algorithms is an obstacle to the trustworthiness of their outcomes. Moreover, the use of opaque algorithms is not normatively justified in medical practice. The authors introduce a formalism, called computational reliabilism, which allows generating justified beliefs on the (...)
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  43. Computational intelligence in healthcare law: AI for ethical governance and regulatory challenges.Bhupindara Siṅgha, Christian Kaunert, Balamurugan Balusamy & Rajesh Kumar Dhanaraj (eds.) - 2025 - Boca Raton: Chapman & Hall, CRC Press.
    This book explores the intersection of legal frameworks, healthcare innovation, and computational intelligence, shedding light on how emerging technologies like AI and ML are reshaping the medical landscape. It presents real life challenges such as patient privacy, data security, and compliance issues in smart healthcare by engaging into associated ethical and regulatory implications. Comprising the concepts of predictive analytics, regulatory compliance algorithms, and legal decision-making processes, this book offers a roadmap for stakeholders to navigate the evolving landscape of healthcare innovation (...)
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  44.  12
    Principles and Virtues in AI Ethics.I. N. Notre Dame, Science Before Receiving A. Phd in Moral Theology From Notre Dame He has Published Widely on Bioethics, Technology Ethics He is the Author of Science Religion, Christian Ethics, Anxiety Tomorrow’S. Troubles: Risk, Prudence in an Age of Algorithmic Governance, The Ethics of Precision Medicine & Encountering Artificial Intelligence - 2024 - Journal of Military Ethics 23 (3):251-263.
    One of the most common contemporary approaches for developing an ethics of artificial intelligence (AI) involves elaborating guiding principles. This essay explores the limitations of this approach, using the history of bioethics as a comparative case. The examples of bioethics and recent AI ethics suggest that principles are difficult to implement in everyday practice, fail to direct individual action, and can frequently result in a pure proceduralism. The essay encourages an additional attention to virtue, which forms the dispositions (...)
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  45.  65
    Troubleshooting AI and Consent.Elizabeth Edenberg & Meg Leta Jones - 2020 - In Markus Dirk Dubber, Frank Pasquale & Sunit Das, The Oxford Handbook of Ethics of Ai. Oxford Handbooks. pp. 347-362.
    As a normative concept, consent can perform the “moral magic” of transforming the moral relationship between two parties, rendering permissible otherwise impermissible actions. Yet, as a governance mechanism for achieving ethical data practices, consent has become strained—and AI has played no small part in its contentious state. In this chapter we will describe how consent has become such a controversial component of data protection as artificial intelligence systems have proliferated in our everyday lives, highlighting five distinct issues. We will then (...)
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  46. Balancing AI and academic integrity: what are the positions of academic publishers and universities?Bashar Haruna Gulumbe, Shuaibu Muhammad Audu & Abubakar Muhammad Hashim - forthcoming - AI and Society:1-10.
    This paper navigates the relationship between the growing influence of Artificial Intelligence (AI) and the foundational principles of academic integrity. It offers an in-depth analysis of how key academic stakeholders—publishers and universities—are crafting strategies and guidelines to integrate AI into the sphere of scholarly work. These efforts are not merely reactionary but are part of a broader initiative to harness AI’s potential while maintaining ethical standards. The exploration reveals a diverse array of stances, reflecting the varied applications of AI in (...)
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  47.  97
    AI and the path to envelopment: knowledge as a first step towards the responsible regulation and use of AI-powered machines.Scott Robbins - 2020 - AI and Society 35 (2):391-400.
    With Artificial Intelligence entering our lives in novel ways—both known and unknown to us—there is both the enhancement of existing ethical issues associated with AI as well as the rise of new ethical issues. There is much focus on opening up the ‘black box’ of modern machine-learning algorithms to understand the reasoning behind their decisions—especially morally salient decisions. However, some applications of AI which are no doubt beneficial to society rely upon these black boxes. Rather than requiring algorithms to be (...)
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  48.  5
    Logical Contradictions and Moral-legal Paradoxes at the Intersection of Scientometrics and Ethics of Scientific Publications (Oxymorons “Self-Pillage” and “Self-Theft” in the AI-System Called “Anti-Plagiarism”).В. О Лобовиков - 2024 - Siberian Journal of Philosophy 21 (3):5-19.
    The subject matter of research is contradictions and moral-legal antinomies arising in the philosophy of science, in relation to a set of technologies called “Anti-Plagiarism”. The formal-logical and formal-axiological aspects of the notions “property”, “common property”, “private property”, “theft”, “plundering” and others are considered. The paper argues for the urgent necessity to allow authors unlimited reuse of any fragments of their previously published texts in their new publications actually containing novel scientific results. The condition is that such duplication is indispensable (...)
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  49. In AI We Trust: Ethics, Artificial Intelligence, and Reliability.Mark Ryan - 2020 - Science and Engineering Ethics 26 (5):2749-2767.
    One of the main difficulties in assessing artificial intelligence (AI) is the tendency for people to anthropomorphise it. This becomes particularly problematic when we attach human moral activities to AI. For example, the European Commission’s High-level Expert Group on AI (HLEG) have adopted the position that we should establish a relationship of trust with AI and should cultivate trustworthy AI (HLEG AI Ethics guidelines for trustworthy AI, 2019, p. 35). Trust is one of the most important and defining activities (...)
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  50.  54
    Reading The Minds of Those Who Never Lived. Enhanced Beings: The Social and Ethical Challenges Posed by Super Intelligent AI and Reasonably Intelligent Humans.John Harris - 2019 - Cambridge Quarterly of Healthcare Ethics 28 (4):585-591.
    The somewhat superannuated “problem of other minds” has unexpectedly risen from the dead, and, in its current incarnation, concerns the mental states of those who never lived.
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