The revolution of generative artificial intelligence in psychology

The interweaving of behavior, consciousness, and ethics

Bibliographic Data

ID21284039
AuthorsDian Chen (0000-0002-1349-9002, Southeast University), Ying Liu (0000-0001-5584-7805, Chinese Academy of Medical Sciences & Peking Union Medical College), Yiting Guo (0000-0002-1089-6141, Southeast University, corresponding author), Yulin Zhang (0000-0003-1833-7456, Southeast University)
Year2024
Volume251
Pages104593
Publication date2024-11-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueActa Psychologica (JOURNAL)
Journal identifiersISSN: 0001-6918 • E-ISSN: 1873-6297
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.actpsy.2024.104593
PMID39522296
OpenAlexW4404201006
LanguageEN
Citations received11
References cited24

In recent years, there have been unparalleled prospects for psychological study due to the swift advancement of generative artificial intelligence (AI) in natural language processing, shown by ChatGPT. This review article looks into the uses and effects of generative artificial intelligence in psychology. We employed a systematic selection process, encompassing papers published between 2015 and 2024 from databases such as Google Scholar, PubMed, and IEEE Xplore, using keywords like "Generative AI in psychology" "ChatGPT and behavior modeling" and "AI in mental health". First, the paper goes over the fundamental ideas of generative AI and lists its uses in data analysis, behavior modeling, and social interaction simulation. A detailed comparison table has been added to contrast conventional research methodologies with GenAI-based approaches in psychology studies. Next, analyzing the theoretical and ethical issues that generative AI raises for psychological research, it highlights how crucial it is to develop a coherent theoretical framework. This study illustrates the benefits of generative AI in handling vast amounts of data and increasing research efficiency by contrasting traditional research methods with AI-driven methodologies. Regarding particular uses, the study explores how generative AI might be used to simulate social interactions, analyze massive amounts of text, and learn about cognitive processes. Section 5 has been expanded to include discussions on political biases, geographic biases, and other biases. In conclusion, the paper looks forward to the future development of generative AI in psychology research and suggests techniques for improving it. We have included methodological solutions such as the Retrieval Augmented Generation (RAG) approach and human-in-the-loop systems, as well as data privacy solutions like open-source local LLMs. In summary, generative AI has the potential to revolutionize psychological research, but in order to maintain the moral and scientific integrity of the field, ethical and theoretical concerns must be carefully considered before applying the technology

Cognitive science · Consciousness · Epistemology · Generative grammar · Artificial Intelligence · Computer Science · Ethics and Social Impacts of AI · Neuroethics, Human Enhancement, Biomedical Innovations · Philosophy · Psychology · Social Psychology

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