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    Human Designers' Dynamic Confidence and Decision-Making When Working With More Than One Artificial Intelligence 

    Source: Journal of Mechanical Design:;2024:;volume( 146 ):;issue: 008:;page 81402-1
    Author(s): Chong, Leah; Kotovsky, Kenneth; Cagan, Jonathan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: As 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 ...
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    Reading Users' Minds With Large Language Models: Mental Inference for Artificial Empathy in Design 

    Source: Journal of Mechanical Design:;2025:;volume( 147 ):;issue: 006:;page 61401-1
    Author(s): Zhu, Qihao; Chong, Leah; Yang, Maria; Luo, Jianxi
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In human-centered design, developing a comprehensive and in-depth understanding of user experiences—empathic understanding—is paramount for designing products that truly meet human needs. Nevertheless, accurately comprehending ...
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    The Evolution and Impact of Human Confidence in Artificial Intelligence and in Themselves on AI-Assisted Decision-Making in Design 

    Source: Journal of Mechanical Design:;2022:;volume( 145 ):;issue: 003:;page 31401-1
    Author(s): Chong, Leah; Raina, Ayush; Goucher-Lambert, Kosa; Kotovsky, Kenneth; Cagan, Jonathan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Decision-making assistance by artificial intelligence (AI) during design is only effective when human designers properly utilize the AI input. However, designers often misjudge the AI’s and/or their own ability, leading ...
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