A Literature Review of Human–AI Synergy in Decision Making: From the Perspective of Affordance Actualization Theory

Abstract

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.

Risk Analysis of Artificial Intelligence in Medicine with a Multilayer Concept of System Order

“…Tables 8-10 describe 47 initiatives, 50 emergent conditions, and the same 10 scenarios for the risk management of AI trustworthiness in medical implants/devices [22,31,[50][51][52]. Table A1 illustrates the baseline relevance of success criteria for the trustworthy AI in medical implants and devices design.…”