Abstract

AI tools hold considerable promise for psychological research. The precise shape of their potential uses has become clearer in recent years as machine learning models have been trained to reproduce a variety of complex human cognitive behaviors with impressive success. The prospect of AI-human performance parity, along with the advantages of AI systems in speed, cost and ease of use, has prompted psychologists to explore how science might benefit from reassigning some traditionally human research roles to machines. This chapter provides an outlook on such methods. We begin by documenting the prospective upsides of what many researchers take to be the most promising types of AI surrogacy, including the use of models to efficiently generate, screen and refine preliminary hypotheses. We then discuss such methods’ limitations and drawbacks, and more generally the methodological considerations researchers must attend to in choosing when and how to rely on machine substitutes for human behavior.