Expert Judgment and Computational Learning

How does human expertise develop, and how does it compare with computational systems that learn from past data? This article from Artificial Intuition Research (AIR) examines experience-based human judgment alongside research on fireground commanders’ decision-making and YouTube’s recommendation system as described in a 2016 publication. It explores how prior experience, learned patterns, and historical data can help people and computational systems guide decisions, recognise possibilities, or narrow options. The article also examines important limitations, including the role of informative feedback in developing reliable expertise and the challenges that arise when familiar patterns no longer fit changing conditions. While these examples reveal a functional similarity in how past information can inform decisions, they do not establish that computational systems learn in the same way as human experts or possess human intuition. Developed from exploratory research undertaken during AIR’s Founding Research Internship Cohort.