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  1. Using artificial intelligence to enhance patient autonomy in healthcare decision-making.Jose Luis Guerrero Quiñones - forthcoming - AI and Society:1-10.
    The use of artificial intelligence in healthcare contexts is highly controversial for the (bio)ethical conundrums it creates. One of the main problems arising from its implementation is the lack of transparency of machine learning algorithms, which is thought to impede the patient’s autonomous choice regarding their medical decisions. If the patient is unable to clearly understand why and how an AI algorithm reached certain medical decision, their autonomy is being hovered. However, there are alternatives to prevent the negative impact of (...)
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  • Detecting your depression with your smartphone? – An ethical analysis of epistemic injustice in passive self-tracking apps.Mirjam Faissner, Eva Kuhn, Regina Müller & Sebastian Laacke - 2024 - Ethics and Information Technology 26 (2):1-14.
    Smartphone apps might offer a low-threshold approach to the detection of mental health conditions, such as depression. Based on the gathering of ‘passive data,’ some apps generate a user’s ‘digital phenotype,’ compare it to those of users with clinically confirmed depression and issue a warning if a depressive episode is likely. These apps can, thus, serve as epistemic tools for affected users. From an ethical perspective, it is crucial to consider epistemic injustice to promote socially responsible innovations within digital mental (...)
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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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  • Enabling the Nonhypothesis-Driven Approach: On Data Minimalization, Bias, and the Integration of Data Science in Medical Research and Practice.C. W. Safarlou, M. van Smeden, R. Vermeulen & K. R. Jongsma - 2023 - American Journal of Bioethics 23 (9):72-76.
    Cho and Martinez-Martin provide a wide-ranging analysis of what they label “digital simulacra”—which are in essence data-driven AI-based simulation models such as digital twins or models used for i...
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  • AIDD, Autonomy, and Military Ethics.Sally J. Scholz - 2021 - American Journal of Bioethics 21 (7):1-3.
    In “Artificial Intelligence, Social Media and Depression,” Laacke and colleagues consider the ethical implications of artificial intelligence depression detector tools to assist pract...
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  • Machines Like Me: 4 Corollaries for Responsible Use of AI in the Bioethics Classroom.Craig M. Klugman & Cheryl J. Erwin - 2023 - American Journal of Bioethics 23 (10):86-88.
    Much of the recent AI-LLM literature has been apocalyptic in pointing out the risks of AI technology, “mitigating the risk of extinction from AI should be a global priority alongside other societal...
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  • Rise of the Bioethics AI: Curse or Blessing?Craig M. Klugman & Sara Gerke - 2022 - American Journal of Bioethics 22 (7):35-37.
    In October 2021, the Allen Institute for Artificial Intelligence publicly released Delphi, an artificial intelligence system trained to make general moral decisions (Allen Institute for Artifi...
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  • Health-Related Digital Autonomy. A Response to the Commentaries.Sebastian Laacke, Regina Mueller, Georg Schomerus & Sabine Salloch - 2021 - American Journal of Bioethics 21 (10):W1-W5.
    The COVID-19 pandemic has been a threat to both physical and mental health. The spreading disease and its impacts, the containment measures and the way all of our lives have dramatically changed ha...
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