What impacts endure: A technologist’s notes on GPT’s impact on expert work.

Imundo et al. (2024) argue that (1) ChatGPT and other chatbots powered by generative Artificial Intelligence (genAI) models can enhance experts' cognition and training, and (2) these benefits are not equally distributed across all users. This commentary commends both arguments. I provide empirical evidence from the field of Human-Computer Interaction (HCI) to show that both statements hold true, not only with ChatGPT, but also with older computational technologies that mimic the behavioral expressions of expertise. By reinforcing Imundo et al. 's arguments, I also argue that now is an opportune time to pursue an even deeper understanding of the relation between ChatGPT and expertise. For instance, how might systems like ChatGPT influence or redefine what it means to be an expert? Rather than distinguishing cognitive, social, and physical expertise, could alternative taxonomies like generative versus evaluative abilities offer more insightful ways to study genAI's cognitive impact?

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Publication Details

Journal
Journal of Applied Research in Memory and Cognition
Published
2024-12-01
DOI
https://doi.org/10.1037/mac0000210
Citations
1
Primary Topic
Big Data Technologies and Applications
Type
article
Field-Weighted Citation Impact
1.05

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article

What impacts endure: A technologist’s notes on GPT’s impact on expert work.

Qian Yang
1 citations
Journal of Applied Research in Memory and Cognition
Big Data Technologies and Applications
1.05
article

What impacts endure: A technologist’s notes on GPT’s impact on expert work.

Qian Yang
article en
1 citations

Abstract

Imundo et al. (2024) argue that (1) ChatGPT and other chatbots powered by generative Artificial Intelligence (genAI) models can enhance experts' cognition and training, and (2) these benefits are not equally distributed across all users. This commentary commends both arguments. I provide empirical evidence from the field of Human-Computer Interaction (HCI) to show that both statements hold true, not only with ChatGPT, but also with older computational technologies that mimic the behavioral expressions of expertise. By reinforcing Imundo et al. 's arguments, I also argue that now is an opportune time to pursue an even deeper understanding of the relation between ChatGPT and expertise. For instance, how might systems like ChatGPT influence or redefine what it means to be an expert? Rather than distinguishing cognitive, social, and physical expertise, could alternative taxonomies like generative versus evaluative abilities offer more insightful ways to study genAI's cognitive impact?

Journal of Applied Research in Memory and CognitionVol. 13(4)
Cornell University (US), New York State College of Agriculture & Life Sciences (US)
National Science Foundation, National Institutes of Health, U.S. National Library of Medicine
Openalex Percentile: Top 11%
Big Data Technologies and Applications
1.05
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