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The principle of trust has been placed at the centre as an attitude for engaging with clinical machine learning systems. However, the notions of trust and distrust remain fiercely debated in the philosophical and ethical literature. In this article, we proceed on a structural lev ...
The advancement of AI-based technologies, such as machine learning (ML) systems, for implementation in healthcare is progressing rapidly. Since these systems are used to support healthcare professionals in crucial medical practices, their role in medical decision-making needs to ...

From ethics to epistemology and back again

Informativeness and epistemic injustice in explanatory medical machine learning

In this paper, we discuss epistemic and ethical concerns brought about by machine learning (ML) systems implemented in medicine. We begin by fleshing out the logic underlying a common approach in the specialized literature (which we call the informativeness account). We maintain ...

Machine learning for mental health diagnosis

Tackling contributory injustice and epistemic oppression

In their contribution, Ugar and Malele shed light on an often overlooked but crucial aspect of the ethical development of machine learning (ML) systems to support the diagnosis of mental health disorders. The authors restrain their focus on pointing to the danger of misdiagnosing ...
Machine learning (ML) systems play an increasingly relevant role in medicine and healthcare. As their applications move ever closer to patient care and cure in clinical settings, ethical concerns about the responsibility of their use come to the fore. I analyse an aspect of respo ...
In my paper entitled 'Testimonial injustice in medical machine learning',1 I argued that machine learning (ML)-based Prediction Drug Monitoring Programmes (PDMPs) could infringe on patients' epistemic and moral standing inflicting a testimonial injustice.2 I am very grateful for ...

Automated opioid risk scores

A case for machine learning-induced epistemic injustice in healthcare

Artificial intelligence-based (AI) technologies such as machine learning (ML) systems are playing an increasingly relevant role in medicine and healthcare, bringing about novel ethical and epistemological issues that need to be timely addressed. Even though ethical questions conn ...