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This content will become publicly available on March 11, 2026

Title: Deskilling and upskilling with AI systems
Introduction. Deskilling is a long-standing prediction of the use of information technology, raised anew by the increased capabilities of AI (AI) systems. A review of studies of AI applications suggests that deskilling (or levelling of ability) is a common outcome, but systems can also require new skills, i.e., upskilling. Method. To identify which settings are more likely to yield deskilling vs. upskilling, we propose a model of a human interacting with an AI system for a task. The model highlights the possibility for a worker to develop and exhibit (or not) skills in prompting for, and evaluation and editing of system output, thus yielding upskilling or deskilling. Findings. We illustrate these model-predicted effects on work with examples of current studies of AI-based systems. Conclusions. We discuss organizational implications of systems that deskill or upskill workers and suggest future research directions.  more » « less
Award ID(s):
2129047
PAR ID:
10592287
Author(s) / Creator(s):
;
Publisher / Repository:
National Library of Sweden
Date Published:
Journal Name:
Information Research an international electronic journal
Volume:
30
Issue:
iConf
ISSN:
1368-1613
Page Range / eLocation ID:
1009 to 1023
Subject(s) / Keyword(s):
Generative AI, Deskilling, Upskilling
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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