Risk and Decision-Making Flashcards

In the Balloon Analogue Risk Task (BART) used in Pymetrics, what does repeatedly stopping at very low pump counts most likely indicate?

Answer: Extreme risk aversion and overly cautious decision-making

Stopping at very low pump counts suggests excessive caution and risk aversion, leaving potential reward on the table.

During Pymetrics' monetary exchange games, a candidate consistently accepts unfair offers rather than rejecting them. What trait does this behavior most likely reflect?

Answer: High agreeableness and pragmatic compromise

Accepting unfair offers suggests the person prioritizes pragmatic gain over fairness norms, reflecting high agreeableness or compromise orientation.

In a Pymetrics task where you must allocate resources between a guaranteed payout and a gamble, choosing the gamble when its expected value is lower than the guaranteed payout reflects:

Answer: Risk-seeking behavior

Choosing a gamble with lower expected value than a certain alternative is the definition of risk-seeking behavior.

Pymetrics games record reaction time alongside choices. In a risk task, what does a very short reaction time before accepting a high-risk bet most likely suggest?

Answer: The choice was made impulsively without deliberation

Very short reaction times before risky choices typically indicate impulsive decision-making rather than calculated risk-taking.

In the context of Pymetrics assessments, 'loss aversion' is best described as:

Answer: Feeling the pain of a loss more strongly than the pleasure of an equivalent gain

Loss aversion means losses loom larger psychologically than equivalent gains, a core finding from prospect theory.

A Pymetrics candidate increases bet sizes after a series of wins in a risk game. This pattern is best described as:

Answer: Gambler's fallacy in reverse (hot-hand fallacy)

Raising bets after consecutive wins reflects the hot-hand fallacy, the mistaken belief that a winning streak will continue.

In Pymetrics games that involve sequential decisions under uncertainty, which approach is generally considered most adaptive by the algorithm?

Answer: Using early rounds to explore options and later rounds to exploit what you've learned

The explore-then-exploit strategy balances learning and earning, which Pymetrics rewards as adaptive decision-making.