In the Shadow of Judgment: Mapping Out the Landscape of Human-AI Decision-Making Through a Systematic Review

Research on human–AI decision-making (HAID) has grown rapidly across domains. However, the literature on this topic remains fragmented, and conceptual ambiguities hinder systematic synthesis and cross-domain comparison. We present a systematic review of HAID publications from 2016 to 2024. Starting with 269,060 records collected from 20 publishers and databases, we conducted 5 rounds of relevance and quality screening, and ultimately analyzed 1,493 articles in breadth and depth. We contribute: (1) a systematic categorization of the literature, including 6 contribution types, 13 domains of application, and 4 decision levels; (2) taxonomies of 8 AI roles and 6 human roles, their inputs to decision-making, and their influences on each other; and (3) the identification of 4 research gaps and pathways forward. Our efforts unify scattered work into a coherent framework, strengthen the descriptive and rhetorical power of this field, and lay the groundwork for future research and policy development.