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  1. Persons or datapoints?: Ethics, artificial intelligence, and the participatory turn in mental health research.Joshua August Skorburg, Kieran O'Doherty & Phoebe Friesen - 2024 - American Psychologist 79 (1):137-149.
    This article identifies and examines a tension in mental health researchers’ growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research specifically, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data points. The (...)
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  • A Systemic Approach to the Oversight of Machine Learning Clinical Translation.Effy Vayena & Alessandro Blasimme - 2022 - American Journal of Bioethics 22 (5):23-25.
    Machine learning heralds highly transformative approaches to the automation of numerous clinical tasks, from diagnosis to risk assessment, and from prognosis to informing treatment decisions....
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  • Promises and Pitfalls of Algorithm Use by State Authorities.Maryam Amir Haeri, Kathrin Hartmann, Jürgen Sirsch, Georg Wenzelburger & Katharina A. Zweig - 2022 - Philosophy and Technology 35 (2):1-31.
    Algorithmic systems are increasingly used by state agencies to inform decisions about humans. They produce scores on risks of recidivism in criminal justice, indicate the probability for a job seeker to find a job in the labor market, or calculate whether an applicant should get access to a certain university program. In this contribution, we take an interdisciplinary perspective, provide a bird’s eye view of the different key decisions that are to be taken when state actors decide to use an (...)
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  • What ethics can say on artificial intelligence: Insights from a systematic literature review.Francesco Vincenzo Giarmoleo, Ignacio Ferrero, Marta Rocchi & Massimiliano Matteo Pellegrini - 2024 - Business and Society Review 129 (2):258-292.
    The abundance of literature on ethical concerns regarding artificial intelligence (AI) highlights the need to systematize, integrate, and categorize existing efforts through a systematic literature review. The article aims to investigate prevalent concerns, proposed solutions, and prominent ethical approaches within the field. Considering 309 articles from the beginning of the publications in this field up until December 2021, this systematic literature review clarifies what the ethical concerns regarding AI are, and it charts them into two groups: (i) ethical concerns that (...)
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