How Occam's razor guides human decision-making

Humans prefer simpler explanations for uncertain data, aligning with formal model selection theories that penalize complexity, with a significant influence on decision-making.

• Why it matters: Understanding how humans choose explanations helps clarify decision-making processes and reveals whether principles like Occam's razor are innate or learned, impacting fields from psychology to artificial intelligence.
• What they did: The study used preregistered behavioral experiments comparing human choices to formal theories, showing humans favor simpler models, while artificial neural networks do not, even when maladaptive.
• The result: Findings suggest that statistical principles like integrating over explanations to prevent overfitting are central to human reasoning, highlighting a potential innate bias toward simplicity in decision-making.