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date: 18 February 2020

Abstract and Keywords

Judgment and prediction comprise the front end of decision making (Mosier & Fischer, 2010 ). These processes are of critical importance in technological systems and are impacted by characteristics of the engineered environment. The study of front-end processes in complex and engineered environments propelled a revival of classic models of judgment and prediction such as Brunswik’s lens model (1943, 1955, 1956), the re-examination of frameworks of heuristic judgment processes and associated biases (e.g., Kahneman, Slovic, & Tversky, 1982 ), and the development of new models and frameworks such as naturalistic decision making (e.g., Klein, 1989, 1993, 2008 ). These models vary according to the assumed goal of front-end processing—accuracy (correspondence) vs. coherence (consistency and rationality)—and in terms of the purported role or impact of intuitive vs. analytical processes. I make the argument that in engineered environments, coherence is an essential strategy/goal, and analysis is often the most appropriate tactic for judgment and prediction. Systems must be designed to facilitate the appropriate cognitive mode for judgment, diagnosis, and prediction—with the dual goals of maintaining operator involvement and producing more coherent and accurate judgments and predictions.

Keywords: judgment, prediction, coherence, correspondence, expertise, heuristics

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