A Literature Review of Human–AI Synergy in Decision Making: From the Perspective of Affordance Actualization Theory
Ying Bao, Wankun Gong, Kaiwen Yang
China University of Petroleum, Beijing Beijing Normal University University of International Business and Economics
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摘要与影响
The emergence of artificial-intelligence (AI)-powered information technology, such as deep learning and natural language processing, enables human to shift their behaving or working diagram from human-only to human–AI synergy, especially in the decision-making process. Since AI is multidisciplinary by nature and our understanding of human–AI synergy in decision-making is fragmented, we conducted a literature review to systematically characterize the phenomenon. Adopting the affordance actualization theory, we developed a framework to organize and understand the relationship between AI affordances, the human–AI synergy process, and the outcomes of human–AI synergy. Three themes emerged from the review: the identification of AI affordances in decision-making, human–AI synergy patterns regarding different decision tasks, and outcomes of human–AI synergy in decision-making. For each theme, we provided evidence on the existing research gaps and proposed future research directions. Our findings provide a holistic framework for understanding human–AI synergy phenomenon in decision-making. This work also offers theoretical contributions and research directions for researchers studying human–AI synergy in decision-making.
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社会科学Human-Automation Interaction and Safety
Information Systems Theories and Implementation · Cybernetics and Technology in Society
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