Bartlett, Laura K, Pirrone, Angelo, Javed, Noman and Gobet, Fernand 
ORCID: 0000-0002-9317-6886
(2023)
Computational Scientific Discovery in Psychology.
PERSPECTIVES ON PSYCHOLOGICAL SCIENCE, 18 (1).
pp. 178-189.
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 |
|---|---|
| Uncontrolled Keywords: | computational scientific discovery, AI, creativity, philosophy of science, psychology |
| Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Population Health |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 12 Sep 2022 09:59 |
| Last Modified: | 23 Feb 2023 22:50 |
| DOI: | 10.1177/17456916221091833 |
| Open Access URL: | https://doi.org/10.1177/17456916221091833 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3164360 |
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