Leveraging decision consistency to decompose suboptimality in terms of its ultimate predictability

While the suboptimality of perceptual decision-making is indisputable in its strictest sense, characterizing the nature of suboptimalities constitutes a valuable drive for future research. I argue that decision consistency offers a rarely measured, yet important behavioral metric for decomposing suboptimality (or, more generally, deviations from any candidate model of decision-making) into ultimately predictable and inherently unpredictable components.