Decision Making Traps

Traps in general Implications for Heuristic methods,

forecasting, modeling in general.

1. Anchoring trap

first impressions

Time series forecasting? Credit risk model

too many inquiries get negative weight (how many is too many?)

2. Status Quo Trap

That’s the way it has always been Inertia School bullying

Key - doing something wrong is punished

doing nothing is generally not punished

3. Sunk Cost trap

Digging the hole deeper being blind to past mistakes corporate strategy -barriers to exit emotional attachment

4. Confirming Evidence Trap

I have made up my mind, don’t confuse me with facts.

Eg. Political candidate – who is more honest/worthy/qualified – Bush or Gore?

5. Framing Trap

Glass half full or half empty?

Biases in surveys

Problem

There are 600 people in a town that have been infected by a certain virus. There are two competing programs, of which one has to be selected. If Program A is adopted, 200 people will be

saved If Program B is adopted, there is a one-third

probability that 600 people will be saved and a two-thirds probability that no people will be saved

Which of the two programs would you favor?

Problem There are 600 people in a town that have

been infected by a certain virus. There are two competing programs, of which one has to be selected. If Program C is adopted, 400 people will die If Program D is adopted, there is a one-third

probability that nobody will die and a two-thirds probability that 600 people will die

Which of the two programs would you favor?

Framing Effects

The two sets of choices are objectively identical.

Changing the description of outcomes from lives saved to lives lost is sufficient to shift prototypic choice from risk-averse to risk-seeking behavior.

6. Estimation traps

Decision calibration Overconfidence - if I am incompetent,

I am probably ignorant of it. Lack of feedback - students may think

they understand but fail on a test. Lack of confidence - learned

helplessness? Recallability -what’s in the news?

Overconfidence Bias

"People generally ascribe more credibility to data than is warranted and hence overestimate the probability of success merely due to the presence of an abundance of data" (Sage, 1981, p. 648).

Predictive accuracy reaches a ceiling at an early point in an information gathering process

Confidence in decisions continues to climb as more and more information is obtained

This bias is most extreme in tasks of great difficulty

List of Names

Margaret Thatcher James Eynon Barbara Walters Charles Stubbart Hillary Clinton Arlyn Melcher Indira Gandhi Jack Smith Madonna Greg White

Instructions

Read the list once.

Recall Test! Are there more men or women on the list? How many men are on the list? How many women are on the list? How confident are you of your answers?

Provide a probability number ranging from 0 to 1 for each answer.

Recallability

Situations in which people assess the frequency of a class or the probability of an event by the ease with which instances or occurrences can be brought to mind.

People inadvertently assume that readily-available instances, examples or images represent unbiased estimates of statistical probabilities.

7. Representativeness

All families of six children in a city were surveyed. In 72 families the exact order of birth of boys and girls was G B G B B G. What is your estimate of the number of

families surveyed in which the exact order of births was B G B B B B?

Representativeness Bias

People consistently judge the more representative event to be more likely, whether it is or not.

Leads to major errors in the estimation of subjective probabilities

Subjective probability denotes any estimate of the probability of an event, which is given by subjects, or inferred from their behavior.