I'm special but A.I. doesn't get it
A growing body of management research on artificial intelligence (AI) has consistently shown that people innately distrust decisions made by AI and find such decision processes simply less fair compared to decisions made by humans. My dissertation adopts a different perspective to propose that aside...
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sg-smu-ink.etd_coll-14102022-07-20T09:02:59Z I'm special but A.I. doesn't get it TEO, Huei Huei Laurel A growing body of management research on artificial intelligence (AI) has consistently shown that people innately distrust decisions made by AI and find such decision processes simply less fair compared to decisions made by humans. My dissertation adopts a different perspective to propose that aside from fairness concerns, AI decision methods trigger perceptions in people that their individual uniqueness has not be adequately considered and this has negative consequences for their psychological or subjective well-being. By combining theories of uniqueness, individuality, power, and well-being, I develop five studies to provide empirical evidence that aversion to AI-mediated decisions also operates through uniqueness neglect particularly in high-stakes contexts, and this mechanism predicts significant incremental variance above other mechanisms identified in existing research. I also extend the consequences of AI decision methods beyond resistance/acceptance of the technology, linking it to subjective well-being, a critical individual outcome that predicts other important employee attitudes and behaviors such as turnover intentions and job performance. Finally, I explore the implications of decision role on AI decision methods to examine responses of decision makers and decision recipients and identify the contexts in which uniqueness neglect is relevant for these different groups of decision stakeholders. In doing so I provide a more comprehensive understanding of the impact of AI decision methods on different stakeholders in organizations. 2022-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/etd_coll/412 https://ink.library.smu.edu.sg/context/etd_coll/article/1410/viewcontent/GPBO_AY2017_PhD_Laurel_Teo_Huei_Huei.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Dissertations and Theses Collection (Open Access) eng Institutional Knowledge at Singapore Management University artificial intelligence (AI) algorithms decision-making uniqueness neglect power subjective well-being Artificial Intelligence and Robotics Organizational Behavior and Theory |
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A growing body of management research on artificial intelligence (AI) has consistently shown that people innately distrust decisions made by AI and find such decision processes simply less fair compared to decisions made by humans. My dissertation adopts a different perspective to propose that aside from fairness concerns, AI decision methods trigger perceptions in people that their individual uniqueness has not be adequately considered and this has negative consequences for their psychological or subjective well-being.
By combining theories of uniqueness, individuality, power, and well-being, I develop five studies to provide empirical evidence that aversion to AI-mediated decisions also operates through uniqueness neglect particularly in high-stakes contexts, and this mechanism predicts significant incremental variance above other mechanisms identified in existing research. I also extend the consequences of AI decision methods beyond resistance/acceptance of the technology, linking it to subjective well-being, a critical individual outcome that predicts other important employee attitudes and behaviors such as turnover intentions and job performance.
Finally, I explore the implications of decision role on AI decision methods to examine responses of decision makers and decision recipients and identify the contexts in which uniqueness neglect is relevant for these different groups of decision stakeholders. In doing so I provide a more comprehensive understanding of the impact of AI decision methods on different stakeholders in organizations. |
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TEO, Huei Huei Laurel |
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TEO, Huei Huei Laurel |
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TEO, Huei Huei Laurel |
title |
I'm special but A.I. doesn't get it |
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I'm special but A.I. doesn't get it |
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I'm special but A.I. doesn't get it |
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I'm special but A.I. doesn't get it |
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I'm special but A.I. doesn't get it |
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i'm special but a.i. doesn't get it |
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Institutional Knowledge at Singapore Management University |
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2022 |
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https://ink.library.smu.edu.sg/etd_coll/412 https://ink.library.smu.edu.sg/context/etd_coll/article/1410/viewcontent/GPBO_AY2017_PhD_Laurel_Teo_Huei_Huei.pdf |
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