Who is Responsible for Tackling Professional Deskilling?

Abstract There has been increasing interest across several professional fields in problems of deskilling , that is, the loss or the lack of development of human skills due to outsourcing tasks to artificial intelligence. Avigail Ferdman (“AI Deskilling is a Structural Problem.” AI & Society 41 (4): 3001–13, 2026) has recently argued that deskilling should be seen as a structural problem. In this paper, based on empirical literature on the relevant heuristics and biases, I present a novel empirically-informed philosophical argument as to why this seems to be the case. According to the empirical literature on deskilling, automation bias, and skill decay, many professionals rely on artificial intelligence much more than is necessary when it is available, and the effects of such overreliance on skill decay are unlikely to be entirely understood by the professionals themselves. I argue that this – what I call the insidious nature of deskilling – supports a normative view, according to which the responsibility for tackling deskilling should not be ascribed to the individual professional but the risks of professional deskilling should be tackled by the professional community instead. Mitigating the risks of deskilling should start from an intra-field analysis of the core skills of the profession that should not be outsourced to artificial intelligence. Then, the individual professional would not be left alone to determine how and when to prevent deskilling during the adoption of artificial intelligence within her profession.

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Publication Details

Journal
Human Affairs
Published
2026-09-22
DOI
https://doi.org/10.1515/humaff-2026-0080
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Who is Responsible for Tackling Professional Deskilling?

Kaisa Kärki
Human Affairs
Ethics and Social Impacts of AI
article

Who is Responsible for Tackling Professional Deskilling?

Kaisa Kärki
article en

Abstract

Abstract There has been increasing interest across several professional fields in problems of deskilling , that is, the loss or the lack of development of human skills due to outsourcing tasks to artificial intelligence. Avigail Ferdman (“AI Deskilling is a Structural Problem.” AI & Society 41 (4): 3001–13, 2026) has recently argued that deskilling should be seen as a structural problem. In this paper, based on empirical literature on the relevant heuristics and biases, I present a novel empirically-informed philosophical argument as to why this seems to be the case. According to the empirical literature on deskilling, automation bias, and skill decay, many professionals rely on artificial intelligence much more than is necessary when it is available, and the effects of such overreliance on skill decay are unlikely to be entirely understood by the professionals themselves. I argue that this – what I call the insidious nature of deskilling – supports a normative view, according to which the responsibility for tackling deskilling should not be ascribed to the individual professional but the risks of professional deskilling should be tackled by the professional community instead. Mitigating the risks of deskilling should start from an intra-field analysis of the core skills of the profession that should not be outsourced to artificial intelligence. Then, the individual professional would not be left alone to determine how and when to prevent deskilling during the adoption of artificial intelligence within her profession.

Human Affairs
University of Helsinki (FI), Helsinki Institute of Physics (FI)
Openalex Percentile: Top 7%
Ethics and Social Impacts of AI
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