Psychology may benefit from prioritizing prediction over causal explanation
In short: Researchers who review the history of psychological science argue that the field's intense focus on uncovering causal mechanisms has come at a cost. While psychologists prioritize explaining why behaviors happen through controlled experiments, this emphasis may have resulted in complex theories that struggle to accurately predict future behaviors.
By reviewing fundamental machine learning concepts and their application in psychological research, the authors suggest that adopting predictive techniques could enhance the field's utility. They argue that shifting the focus toward prediction might ultimately lead to a deeper understanding of human behavior, though the paper primarily offers a theoretical perspective rather than a new experimental trial.
Why it matters: Moving from explaining causes to predicting outcomes using machine learning might deepen our understanding of psychology.
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Sources
- Summary by Intellect · source: Research: Yarkoni and Westfall (2017). Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning. Perspectives on Psychological Science.
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