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  1. 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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  • Opening the black boxes of the black carpet in the era of risk society: a sociological analysis of AI, algorithms and big data at work through the case study of the Greek postal services.Christos Kouroutzas & Venetia Palamari - forthcoming - AI and Society:1-14.
    This article draws on contributions from the Sociology of Science and Technology and Science and Technology Studies, the Sociology of Risk and Uncertainty, and the Sociology of Work, focusing on the transformations of employment regarding expanded automation, robotization and informatization. The new work patterns emerging due to the introduction of software and hardware technologies, which are based on artificial intelligence, algorithms, big data gathering and robotic systems are examined closely. This article attempts to “open the black boxes” of the “black (...)
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  • Individuals and (Synthetic) Data Points: Using Value-Sensitive Design to Foster Ethical Deliberations on Epistemic Transitions.Jean-Christophe Bélisle-Pipon, Vardit Ravitsky, Bridge2AI-Voice Consortium & Yael Bensoussan - 2023 - American Journal of Bioethics 23 (9):69-72.
    Cho and Martinez-Martin (2023) provide a compelling critique of the profound influence that data sourcing for artificial intelligence (AI) has on the healthcare sector. They emphasize the need for...
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  • AI and the falling sky: interrogating X-Risk.Nancy S. Jecker, Caesar Alimsinya Atuire, Jean-Christophe Bélisle-Pipon, Vardit Ravitsky & Anita Ho - forthcoming - Journal of Medical Ethics.
    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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  • The shift of Artificial Intelligence research from academia to industry: implications and possible future directions.Miguel Angelo de Abreu de Sousa - forthcoming - AI and Society:1-10.
    The movement of Artificial Intelligence (AI) research from universities to big corporations has had a significant impact on the development of the field. In the past, AI research was primarily conducted in academic institutions, which foster a culture of peer reviewing and collaboration to enhance quality improvements. The growing interest in AI among corporations, especially regarding Machine Learning (ML) technology, has shifted the focus of research from quality to quantity. Corporations have the resources to invest in large-scale ML projects and (...)
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