The Future of Psychology: Is Effective Interaction with ChatGPT Possible?

The relevance of this study is due to the need to adapt psychology to the challenges of the digital era and integrate new tools for predicting the future of science. The use of large language models, such as ChatGPT, opens up prospects for analyzing scientific representations and trends in the psychology of the future. The purpose of the article is to determine the possibility of dialogue with ChatGPT for analyzing promising areas of psychology and to highlight ‘representations’ of the future of psychological science encoded in the GPT-3.5 text database. The study was conducted in three stages: (1) determining the optimal interaction parameters for ChatGPT; (2) developing an interview framework based on S. Kvale’s methodology; and (3) conducting a series of interviews followed by text analysis using A. Giorgi’s meaning condensation method. In the process, the prompt parameters were optimized to improve the quality and completeness of the responses, and the model limitations were identified, including the problem of ‘hallucinations’. The results of the study showed that the quality of ChatGPT responses would depend on the structure of the prompts, the described roles, and the context of the task. The optimal prompt length was determined to be up to 13,000 characters, while the key challenges included superficial answers to simple queries and the generation of unreliable data, which required critical verification. The research interview with ChatGPT made it possible to reconstruct representations about the future of psychology, highlighting 73 relevant research areas, including artificial intelligence, positive psychology, virtual reality, and online psychotherapy. It was found that the future design of psychological research would be based on the use of Big Data, machine learning, virtual reality technologies, and multimethod approaches. It was shown that the future of psychological science would largely depend on the integration of psychology with neuroscience, genetics, epigenetics, and artificial intelligence. The study demonstrated the potential of using ChatGPT to analyze scientific representations and identify promising directions for the development of psychology. The results obtained make it possible to assess the capabilities of large language models as tools for specific psychological research, emphasizing their relevance in the context of contemporary interdisciplinary approaches.

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Publication Details

Journal
RUDN Journal of Psychology and Pedagogics
Published
2024-12-15
DOI
https://doi.org/10.22363/2313-1683-2024-21-3-831-857
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.12

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article

The Future of Psychology: Is Effective Interaction with ChatGPT Possible?

А. Н. Воронин, Violetta V. Palenova
1 citations
RUDN Journal of Psychology and Pedagogics
Artificial Intelligence in Healthcare and Education
0.12
article

The Future of Psychology: Is Effective Interaction with ChatGPT Possible?

А. Н. Воронин, Violetta V. Palenova
article en
1 citations

Abstract

The relevance of this study is due to the need to adapt psychology to the challenges of the digital era and integrate new tools for predicting the future of science. The use of large language models, such as ChatGPT, opens up prospects for analyzing scientific representations and trends in the psychology of the future. The purpose of the article is to determine the possibility of dialogue with ChatGPT for analyzing promising areas of psychology and to highlight ‘representations’ of the future of psychological science encoded in the GPT-3.5 text database. The study was conducted in three stages: (1) determining the optimal interaction parameters for ChatGPT; (2) developing an interview framework based on S. Kvale’s methodology; and (3) conducting a series of interviews followed by text analysis using A. Giorgi’s meaning condensation method. In the process, the prompt parameters were optimized to improve the quality and completeness of the responses, and the model limitations were identified, including the problem of ‘hallucinations’. The results of the study showed that the quality of ChatGPT responses would depend on the structure of the prompts, the described roles, and the context of the task. The optimal prompt length was determined to be up to 13,000 characters, while the key challenges included superficial answers to simple queries and the generation of unreliable data, which required critical verification. The research interview with ChatGPT made it possible to reconstruct representations about the future of psychology, highlighting 73 relevant research areas, including artificial intelligence, positive psychology, virtual reality, and online psychotherapy. It was found that the future design of psychological research would be based on the use of Big Data, machine learning, virtual reality technologies, and multimethod approaches. It was shown that the future of psychological science would largely depend on the integration of psychology with neuroscience, genetics, epigenetics, and artificial intelligence. The study demonstrated the potential of using ChatGPT to analyze scientific representations and identify promising directions for the development of psychology. The results obtained make it possible to assess the capabilities of large language models as tools for specific psychological research, emphasizing their relevance in the context of contemporary interdisciplinary approaches.

RUDN Journal of Psychology and PedagogicsVol. 21(3)
State Academic University of Humanities (RU), Institute of Psychology (RU)
Cairo University, Banco Bilbao Vizcaya Argentaria, Fogarty International Center
Openalex Percentile: Top 44%
Artificial Intelligence in Healthcare and Education
0.12
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