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contributor authorChong, Leah
contributor authorKotovsky, Kenneth
contributor authorCagan, Jonathan
date accessioned2024-04-24T22:41:58Z
date available2024-04-24T22:41:58Z
date copyright3/5/2024 12:00:00 AM
date issued2024
identifier issn1050-0472
identifier othermd_146_8_081402.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4295705
description abstractAs artificial intelligence (AI) systems become increasingly capable of performing design tasks, they are expected to be deployed to assist human designers' decision-making in a greater variety of ways. For complex design problems such as those with multiple objectives, one AI may not always perform its expected accuracy due to the complexity of decision-making, and therefore, multiple AIs may be implemented to provide design suggestions. For such assistance to be productive, human designers must develop appropriate confidence in each AI and in themselves and accept or reject AI inputs accordingly. This work conducts a human subjects experiment to examine the development of a human designer's confidence in each AI and self-confidence throughout decision-making assisted by two AIs and how these confidences influence the decision to accept AI inputs. Major findings demonstrate severe decreases in a human designer's confidence especially when working with one or more low-performing AI teammates and/or receiving negative feedback. Additionally, a human designer's decision to accept AI suggestions depends on their self-confidence and confidence in one of the two AIs. Finally, an additional AI does not increase a human designer's likelihood of conforming to AI suggestions. Therefore, in comparison to a scenario with one AI, the results in this work caution against the implementation of an additional AI to AI-assisted decision-making scenarios. The insights also inform the design and management of human–AI teams to improve the outcome of AI-assisted decision-making.
publisherThe American Society of Mechanical Engineers (ASME)
titleHuman Designers' Dynamic Confidence and Decision-Making When Working With More Than One Artificial Intelligence
typeJournal Paper
journal volume146
journal issue8
journal titleJournal of Mechanical Design
identifier doi10.1115/1.4064565
journal fristpage81402-1
journal lastpage81402-11
page11
treeJournal of Mechanical Design:;2024:;volume( 146 ):;issue: 008
contenttypeFulltext


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