A cautionary tale about the impact of AI on human design teams

Guanglu Zhang; Ayush Raina; Jonathan Cagan; Christopher McComb

doi:10.1016/j.destud.2021.100990

A cautionary tale about the impact of AI on human design teams

Guanglu Zhang, Ayush Raina, Jonathan Cagan, Christopher McComb

Research output: Contribution to journal › Article › peer-review

29 Scopus citations

Abstract

Recent advances in artificial intelligence (AI) offer opportunities for integrating AI into human design teams. Although various AIs have been developed to aid engineering design, the impact of AI usage on human design teams has received scant research attention. This research assesses the impact of a deep learning AI on distributed human design teams through a human subject study that includes an abrupt problem change. The results demonstrate that, for this study, the AI boosts the initial performance of low-performing teams before the problem change but always hurts the performance of high-performing teams. The potential reasons behind these results are discussed and several suggestions and warnings for utilizing AI in engineering design are provided.

Original language	English (US)
Article number	100990
Journal	Design Studies
Volume	72
DOIs	https://doi.org/10.1016/j.destud.2021.100990
State	Published - Jan 2021

All Science Journal Classification (ASJC) codes

Architecture
Arts and Humanities (miscellaneous)
Engineering(all)
Social Sciences(all)
Computer Science Applications
Artificial Intelligence

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10.1016/j.destud.2021.100990

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title = "A cautionary tale about the impact of AI on human design teams",

abstract = "Recent advances in artificial intelligence (AI) offer opportunities for integrating AI into human design teams. Although various AIs have been developed to aid engineering design, the impact of AI usage on human design teams has received scant research attention. This research assesses the impact of a deep learning AI on distributed human design teams through a human subject study that includes an abrupt problem change. The results demonstrate that, for this study, the AI boosts the initial performance of low-performing teams before the problem change but always hurts the performance of high-performing teams. The potential reasons behind these results are discussed and several suggestions and warnings for utilizing AI in engineering design are provided.",

author = "Guanglu Zhang and Ayush Raina and Jonathan Cagan and Christopher McComb",

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AU - Raina, Ayush

AU - Cagan, Jonathan

AU - McComb, Christopher

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A cautionary tale about the impact of AI on human design teams

Abstract

All Science Journal Classification (ASJC) codes

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