Computational scientific discovery in psychology

Bartlett, Laura ORCID: 0000-0001-5202-4504, Pirrone, Angelo, Javed, Noman ORCID: 0000-0001-7770-6616 and Gobet, Fernand ORCID: 0000-0002-9317-6886 (2023) Computational scientific discovery in psychology. Perspectives on Psychological Science, 18 (1). 178 - 189. ISSN 1745-6916

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Abstract

Scientific discovery is a driving force for progress involving creative problem-solving processes to further our understanding of the world. The process of scientific discovery has historically been intensive and time-consuming; however, advances in computational power and algorithms have provided an efficient route to make new discoveries. Complex tools using artificial intelligence (AI) can efficiently analyze data as well as generate new hypotheses and theories. Along with AI becoming increasingly prevalent in our daily lives and the services we access, its application to different scientific domains is becoming more widespread. For example, AI has been used for the early detection of medical conditions, identifying treatments and vaccines (e.g., against COVID-19), and predicting protein structure. The application of AI in psychological science has started to become popular. AI can assist in new discoveries both as a tool that allows more freedom to scientists to generate new theories and by making creative discoveries autonomously. Conversely, psychological concepts such as heuristics have refined and improved artificial systems. With such powerful systems, however, there are key ethical and practical issues to consider. This article addresses the current and future directions of computational scientific discovery generally and its applications in psychological science more specifically.

Item Type:	Article
Official URL:	https://journals.sagepub.com/home/pps
Additional Information:	© 2022 The Authors
Divisions:	CPNSS
Subjects:	Q Science > Q Science (General) B Philosophy. Psychology. Religion > BF Psychology
Date Deposited:	21 Mar 2022 16:15
Last Modified:	12 Dec 2024 02:55
URI:	http://eprints.lse.ac.uk/id/eprint/114418

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