AI Errors in Health? The problem of scientific bias and the limits of media debate in Europe

Item Type Journal paper
Abstract The ever-greater use of AI-driven technologies in the health sector begs moral questions regarding what it means for algorithms to mis-understand and mis-measure human health and how as a society we are understanding AI errors in health. This article argues that AI errors in health are putting us in front of the problem that our AI technologies do not grasp the full pluriverse of human experience, and rely on data and measures that have a long history of scientific bias. However, as we shall see in this paper, contemporary public debate on the issue is very limited. Drawing on a discourse analysis of 520 European news media articles reporting on AI-errors the article will argue that the ‘media frame’ on AI errors in health is often defined by a techno-solutionist perspective, and only rarely it sheds light on the relationship between AI technologies and scientific bias. Yet public awareness on the issue is of central importance because it shows us that rather than ‚fixing‘ or ‚finding solutions‘ for AI errors we need to learn how to coexist with the fact that technlogies – because they are human made, are always going to be inevitably biased.
Authors Barassi, Veronica & Patra, Rahi
Projects Barassi, Prof. Ph.D Veronica & Scharenberg, Dr. Antje The Human Error Project [fundamental research project]
Journal or Publication Title Morals and Machines
Language English
Keywords scientific bias - health tech - AI errors - Media discourse - Public awareness
Subjects computer science
information management
social sciences
political science
Refereed Yes
Date 2022
Publisher Nomos
Volume 2
Number 1
Page Range 34-43
Publisher DOI
Official URL
Depositing User Prof. Ph.D Veronica Barassi
Date Deposited 04 Oct 2022 10:30
Last Modified 10 Oct 2022 07:06


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Barassi, Veronica & Patra, Rahi (2022) AI Errors in Health? The problem of scientific bias and the limits of media debate in Europe. Morals and Machines, 2 (1). 34-43.

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