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

Abstract

This paper explores the frontiers of large language models (LLMs) in psychology 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 provide a detailed exploration of how LLMs like ChatGPT are transforming psychological research. It discusses 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 potential to simulate aspects of human cognition and behavior. The paper delves into the capabilities of these models to emulate human-like text generation, offering innovative tools for literature review, hypothesis generation, experimental design, experimental subjects, data analysis, academic writing, and peer review in psychology. While LLMs are essential in advancing research methodologies in psychology, the paper also cautions about their technical and ethical challenges. There are issues like data privacy, the ethical implications of using LLMs in psychological research, and the need for a deeper understanding of these models' limitations. Researchers should responsibly use LLMs in psychological studies, adhering to ethical standards and considering the potential consequences of deploying these technologies in sensitive areas. Overall, the article provides a comprehensive overview of the current state of LLMs in psychology, exploring potential benefits and challenges. It serves as a call to action for researchers to leverage LLMs' advantages responsibly while addressing associated risks.

References in corpus (24)

• Sparks of Artificial General Intelligence: Early experiments with GPT-4
• Galactica: A Large Language Model for Science
• Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models
• Pretrained Language Models for Text Generation: A Survey
• Evaluation of ChatGPT for NLP-based Mental Health Applications
• LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving
• ChatCounselor: A Large Language Models for Mental Health Support
• Automating psychological hypothesis generation with AI: when large language models meet causal graph
• Can Large Language Models Be an Alternative to Human Evaluations?
• Turning large language models into cognitive models
• Who is GPT-3? An Exploration of Personality, Values and Demographics
• Generative AI vs. AGI: The Cognitive Strengths and Weaknesses of Modern LLMs
• Large Language Models Can Infer Psychological Dispositions of Social Media Users
• Large Language Models for Scientific Synthesis, Inference and Explanation
• Ethical Implications of ChatGPT in Higher Education: A Scoping Review
• Large language models predict human sensory judgments across six modalities
• Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View
• Mind meets machine: Unravelling GPT-4's cognitive psychology
• Long-form analogies generated by chatGPT lack human-like psycholinguistic properties
• Are LLMs the Master of All Trades? : Exploring Domain-Agnostic Reasoning Skills of LLMs
• In-Context Learning Creates Task Vectors
• Generative Models as a Complex Systems Science: How can we make sense of large language model behavior?
• The Cultural Psychology of Large Language Models: Is ChatGPT a Holistic or Analytic Thinker?
• Heuristic Reasoning in AI: Instrumental Use and Mimetic Absorption

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