Across many domains of decision making, people seem both rational and irrational. We
review recent work that aims to reconcile these apparently contradictory views by modeling …

Highlights•Computation noise drives human decision variability under uncertainty.•
Computation noise sets cognitive constraints on information processing.•Computation noise …

This article documents the economic relevance of measuring cognitive uncertainty: people's
subjective uncertainty over their ex ante utility-maximizing decision. In a series of …

Humans are generally risk averse, preferring smaller certain over larger uncertain outcomes.
Economic theories usually explain this by assuming concave utility functions. Here, we …

Sensory information encoded by humans and other organisms is generally presumed to be
as accurate as their biological limitations allow. However, perhaps counterintuitively …

We experimentally test a theory of risky choice in which the perception of a lottery payoff is
noisy due to information processing constraints in the brain. We model perception using the …

Pupil size is a widely used metric of brain state. It is one of the few signals originating from
the brain that can be readily monitored with low-cost devices in basic science, clinical, and …

We provide evidence for a bias that we call “representative signal distortion”(RSD), which is
particularly relevant to settings of statistical discrimination. Experimental subjects distort their …

For the past half-century, cognitive and social scientists have struggled with the irrationalities
of human choice behavior; people consistently make choices that are logically inconsistent …

While decision theories have evolved over the past five decades, their focus has largely
been on choices among a limited number of discrete options, even though many real-world …