Computational Scientific Discovery in Psychology

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.

A Prototype Implementation of a Virtual Platform with Robotic Integration and Machine Learning Capabilities for the Execution of Cognitive Psychology Experiments in Children

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“…Advocates for the use of Big Data and machine learning in psychological science typically argue that these technologies will allow psychology to address several epistemological and logistical problems that beset the discipline. Firstly, it is argued that the application of machine learning to Big Data has the potential to generate psychological insights that would ordinarily be inaccessible to human researchers because of the sheer size of the datasets (Bartlett, et al., 2023). Others have argued that such techniques would boost the predictive capacities of psychological science (Yarkoni & Westfall, 2017).…”

Call for Papers: Psychology in the Digital Age

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“…The array of possibilities brought by digitalization and the use of technology in psychology raises several questions. If the nature of the context and the tools used do not alter the need for compliance with the psychologists' professional ethical principles (Carvalho et al, 2020), one should take into account not only the opportunities, but also the challenges, the needs, and even the potential threats that arise from the use of digital tools (Bartlett et al, 2023;Fokkema et al, 2022;Iliescu & Greiff, 2019). This involves addressing several issues, from knowledge transfer from the research contexts to professional practice in a way that is useful to people and society, to the nature of the conceptual framework and methodological aspects that should be applied when it comes to using digital technologies in the field of psychology.…”