Understanding decision errors

Palminteri and Wyart have established themselves as a productive collaboration in the library's decision-making research, with their previous work scoring 8 for bringing computational insights to human judgment under uncertainty. This follow-up work likely extends their framework for understanding systematic biases in decision-making — the kind of foundational cognitive science that helps product leaders understand why teams consistently make predictable errors in estimation, prioritisation, and strategic choice. The decision-making theme remains underdeveloped in the library relative to its importance for product direction, and these authors have proven they can bridge the gap between laboratory research and practical organisational insight. Their approach to decision errors as computational rather than merely psychological offers product people a more precise framework for designing processes that account for human limitations.