@article{7611,
  author = {Kevin Crowston and Francesco Bolici},
  title = {Deskilling and upskilling with AI systems},
  abstract = {<p>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.<br>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.<br>Findings. We illustrate these model-predicted effects on work with examples of current studies of AI-based systems.<br>Conclusions. We discuss organizational implications of systems that deskill or upskill workers and suggest future research directions.</p>},
  year = {2025},
  journal = {Information Research an International Electronic Journal},
  volume = {30},
  pages = {1009–1023},
  month = {3/2025},
  doi = {10.47989/ir30iConf47143},
  language = {eng},
}