Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review

This review explores the frontiers of large language models (LLMs) in psychological applications. Psychology has undergone several theoretical changes, and the current use of artificial intelligence (AI) and machine learning, particularly LLMs, promises to open up new research directions. We aim to provide a detailed exploration of how LLMs are transforming psychological research. We discuss the impact of LLMs across various branches of psychology—including cognitive and behavioral, clinical and counseling, educational and developmental, and social and cultural psychology—highlighting their ability to model patterns, cognition, and behavior similar to those observed in humans. Furthermore, we explore the ability of such models to generate coherent, contextually relevant text, offering innovative tools for literature reviews, hypothesis generation, experimental designs, experimental subjects, and data analysis in psychology. We emphasize the importance of addressing technical and ethical challenges, including data privacy, the ethics of using LLMs in psychological research, and the need for a deeper understanding of these models’ limitations.

Introduction. Artificial intelligence (AI) has a history spanning nearly seven decades, beginning with the 1956 Dartmouth Conference. The field has recently been revolutionized with the advent of large language models (LLMs) such as ChatGPT, Google’s Bard, and Meta’s LLaMA. Among them, GPT-4, in particular, could signify a paradigm shift given its impressive capabilities (e.g., solving difficult tasks in math, coding, vision,