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  1. Hiring, Algorithms, and Choice: Why Interviews Still Matter.Vikram R. Bhargava & Pooria Assadi - 2024 - Business Ethics Quarterly 34 (2):201-230.
    Why do organizations conduct job interviews? The traditional view of interviewing holds that interviews are conducted, despite their steep costs, to predict a candidate’s future performance and fit. This view faces a twofold threat: the behavioral and algorithmic threats. Specifically, an overwhelming body of behavioral research suggests that we are bad at predicting performance and fit; furthermore, algorithms are already better than us at making these predictions in various domains. If the traditional view captures the whole story, then interviews seem (...)
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  • AI and the need for justification (to the patient).Anantharaman Muralidharan, Julian Savulescu & G. Owen Schaefer - 2024 - Ethics and Information Technology 26 (1):1-12.
    This paper argues that one problem that besets black-box AI is that it lacks algorithmic justifiability. We argue that the norm of shared decision making in medical care presupposes that treatment decisions ought to be justifiable to the patient. Medical decisions are justifiable to the patient only if they are compatible with the patient’s values and preferences and the patient is able to see that this is so. Patient-directed justifiability is threatened by black-box AIs because the lack of rationale provided (...)
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  • Black box algorithms in mental health apps: An ethical reflection.Tania Manríquez Roa & Nikola Biller-Andorno - 2023 - Bioethics 37 (8):790-797.
    Mental health apps bring unprecedented benefits and risks to individual and public health. A thorough evaluation of these apps involves considering two aspects that are often neglected: the algorithms they deploy and the functions they perform. We focus on mental health apps based on black box algorithms, explore their forms of opacity, discuss the implications derived from their opacity, and propose how to use their outcomes in mental healthcare, self‐care practices, and research. We argue that there is a relevant distinction (...)
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  • Response to our reviewers.Juan Manuel Durán & Karin Rolanda Jongsma - 2021 - Journal of Medical Ethics 47 (7):514-514.
    We would like to thank the authors of the commentaries for their critical appraisal of our feature article, Who is afraid of black box algorithms?1 Their comments, suggestions and concerns are various, and we are glad that our article contributes to the academic debate about the ethical and epistemic conditions for medical Explanatory AI. We would like to bring to attention a few issues that are common worries across reviewers. Most prominently are the merits of computational reliabilism —in particular, when (...)
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