Member Only Access
Summary
This study presents a framework for understanding people’s use of predictive algorithms, emphasizing their role as tools designed to support human decision-making. It argues that users’ performance expectations are a primary driver of their decisions to adopt these algorithms. By reviewing and reinterpreting the literature through the lens of laypeople’s performance expectations, the study aims to clarify why some algorithms are accepted and others are rejected. It concludes by suggesting avenues for designing algorithms that better meet users’ expectations, enhancing their usability and acceptance.