Risk Assessment

Risk assessment concerns how people evaluate uncertain outcomes when choosing between options with different probabilities and payoffs. Kahneman and Tversky's prospect theory (1979) demonstrated that people do not evaluate risk using the expected-value calculations of classical economic theory. Instead they weight losses roughly twice as heavily as equivalent gains, a pattern called loss aversion, and distort low and high probabilities in predictable directions, producing systematic deviations from purely rational risk-taking.

Reference: Kahneman & Tversky, 1979. The NeuroRank implementation holds the canonical form and scales interference via task-irrelevant stimulus density.

1. Deciding between a full buy and an economy round in CS2 when the outcome of the current round is uncertain.
2. An all-in team fight commitment in a MOBA when a loss would concede map control for the rest of the game.
3. Holding utility in reserve versus using it immediately, weighing a probable small gain against a possible larger loss later.

NeuroRank's Tilt module includes a low-versus-high bet mechanic across baseline, failure, and recovery phases. Shifts in betting behavior after a simulated failure directly measure how risk tolerance changes under pressure, feeding the Tilt Recovery dimension alongside RT and accuracy.