<b>Machine Learning applications to Psychology and Behavioral Science: A case of Personality Psychology</b>

Machine learning (ML) as a field of artificial intelligence is rapidly growing in terms of theory and algorithms, availability of ML tool-kit to behavioral science researchers, as well as applications to various problems associated with human life. Traditionally, psychology has been an experimental science with small samples and tightly controlled conditions. This approach has limitations in predicting behavior and identifying pattern at large scale. Machine learning provides an alternative that has the potential to overcome these limitations. The paper reviews machine-learning methods and demonstrates the application of ML to a problem in personality psychology. The classical approach of going from theory to data in order to verify specific testable hypotheses derived from theory is put to rest by ML methods. The ML approach begins with data and searches for patterns that emerge in the data. This is not completely novel for personality psychologists. The ML approach has many advantages and if used judicially, may lead to an understanding of the psychological processes that remained uncovered so far. The paper attempts to situate machine learning in the epistemology and practice of psychological research and emphasized need to identify proxies for psychological mechanisms.Belhekar, V. M. (2019). Machine Learning applications to Psychology and Behavioral Science: A case of Personality Psychology. Bombay Psychologists, 32, 63-72