Heuristics & Biases

MAR 3053

February 28, 2012

Part 1: Heuristics & intuitive judgment

The use and misuse of affect, availability, representative-ness, and anchors

Two systems of reasoning

System 1• “Intuitive”• Automatic• Effortless• Rapid & parallel• Concrete• Associative

System 2• “Reflective”• Controlled• Effortful• Slow & often serial• May be abstract• Rule-based

Which bet would you choose?

1 in 10 9 in 100

Who chooses the large box?

Percentage of participants choosing the box with greater # of total balls(odds with small box = 10%; odds with large box = value shown on x-axis)

What is a heuristic?

• “Mental shortcut” used in judgment and decision making– Essential for living in an uncertain world– But they can lead to faulty beliefs and suboptimal

decisions– By looking at errors and biases, we can learn how

people are reasoning under uncertainty

Two types of heuristics

• Special purpose heuristics – use restricted to specific domains– Height as a guide for ability as basketball player– # of publications as guide for quality as an

academic• General use heuristics– Affect– Availability– Representativeness (similarity)

The affect heuristic

• ## migrating birds die each year by drowning in uncovered oil ponds, which the birds mistake for bodies of water. Covering the ponds with nets could prevent these deaths. How much money would you be willing to pay to provide the needed nets?

• 2,000 birds -- $80• 20,000 birds -- $78• 200,000 birds -- $88

The identifiable victim effect

• “A death of a single Russian solder is a tragedy. A million deaths is a statistic.” – Joseph Stalin

Affect

• Judgments of life happiness:• People asked 2 questions:– 1) How satisfied are you with your life these days?– 2) How many dates have you had in the last month?

• Correlation = -.12• Another group asked in opposite order – 2), then

1)• Correlation = .66

Strack et al., 1993

The availability heuristic

Kansas? Nebraska?

• Making judgments about the frequency or likelihood of an event based on the ease with which evidence or examples come to mind– Example: Category size

Availability

• Egocentric allocations of responsibility: “Overclaiming”

• People claim more responsibility for collective endeavors than is logically possible

• Self-allocations sum to more than 100%• Why? Because one’s own contributions are

more available than those of others

Availability• Experimental evidence• Married couples asked to allocate responsibility

for:– Positive events: Making breakfast, planning activities,

shopping for family, making important decisions– Negative events: Causing arguments, causing messes,

irritating spouse• Results: – Overclaiming occurred for 16 of 20 activities– Equivalent overclaiming for positive and negative

events

Ross & Sicoly, 1979; Kruger & Gilovich, 1999

Availability

• What is availability? Two possibilities:– 1. Number – amount of information generated– 2. Ease – the ease with which information can be

generated• Iconic study teased them apart:– Participants were asked to evaluate their own

assertiveness…– By generating either 6 (easy) or 12 (hard)

examples of assertiveness or unassertiveness

Availability: number versus ease

Moral: Ease influences judgments sometimes in spite of numberSchwarz et al., 1991

Representativeness• Determining class inclusion or likelihood by

similarity:– A member ought to resemble the overall category– An effect ought to resemble or be similar to the cause– An outcome ought to resemble the process that

produced it• Like goes with like• Often easier to assess similarity than probability– Does he look like an engineer?– Does it look like it could cause a clogged artery?– Does it look like a random sequence?

Representativeness

• Leads to several classic judgment errors– Conjunction fallacy– Misperceiving randomness– Regression fallacy

The Linda problem• Linda is 31 years old, single, outspoken, and very

bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and criminal justice, and also participated in anti-nuclear demonstrations.

• Rank likelihood that Linda is:– A teacher in elementary school– Active in the feminist movement– A member of the League of Women Voters– A bank teller– An insurance salesperson– A bank teller and active in the feminist movement

The Linda problem

• Class data (rankings—lower numbers mean more likely):

• Active in the feminist movement: • A bank teller: • Active in feminist movement a bank teller:

Representativeness: Conjunction fallacy

• Judging the conjunction of two events to be more probable than one of the constituent elements

Feminists

Bank tellers

P(A & B) > P(A) or P(B)/

Conjunction fallacy

• How much would you be willing to pay for a new insurance policy that would cover hospitalization for:

• 1. Any disease or accident– Mean = $89.10

• 2. Any reason– Mean = $41.53

Johnson et al., 1993

Conjunction fallacy

• How much would you be willing to pay for flight insurance (1 flight to London) that covers death due to:

• 1. Any act of terrorism– Mean = $14.12

• 2. Any reason– Mean = $12.03

Johnson et al., 1993

Representativeness: Randomness

• Effects should resemble the process that produced them

• If something is random, it should look random

• What does random look like?– HTHHHTTTTHTHHTTTHHHTH– HTHTHTTTHHTHTHTTHHHTH

The hot hand

• “If I’m on, I find that confidence just builds…you feel nobody can stop you. It’s important to hit that first one, especially if it’s a swish. Then you hit another, and…you feel like you can do anything.”– --Lloyd Free (a.k.a. World B. Free)

The hot hand• The belief that success breeds success, and

failure breeds failure• 100 basketball fans…– 91% thought player has a better chance of making a

shot after having just made his last two or three shots than he does after having just missed his last two or three shots

– Given a player who makes 50% of his shots, subjects thought that shooting percentage would be…• 61% after having just made a shot• 42% after having just missed a shot

– 84% thought that it’s important to pass the ball to someone who has just made several shots in a row

Gilovich, Vallone, & Tversky, 1985

The hot hand

• Calculate probability of making a shot after missing previous 1, 2, or 3 shots and after making previous 1, 2, or 3 shots

Gilovich, Vallone, & Tversky, 1985

What the hot hand results mean• “The independence between successive shots, of

course, does not mean that basketball is a game of chance rather than skill, nor should it render the game less exciting to play, watch, or analyze. It merely indicates that the probability of a hit is largely independent of the outcome of previous shots, although it surely depends on other parameters such as skill, distance to the basket, and defensive pressure…The availability of plausible explanations may contribute to the erroneous belief that the probability of a hit is greater following a hit than following a miss.” – –Gilovich et al., 1985, pp.312-313

Regression to the mean

The SI jinx

The SI jinx

• In sports (the SI jinx, the sophomore slump, rehiring the interim manager, etc.)

• In education (the illusory superiority of punishment over reward)

• In medicine (why it’s so easy to believe that a worthless “remedy” really works)

• In politics (be careful about taking office during an economic boom or a drop in crime)

Part 2: BiasesOverconfidence and its causes

Overconfidence in social predictions

• Would the target person…– Prefer to subscribe to Playboy or the New York Review of

Books?– Describe his/her lecture notes as neat or messy?– Say s/he would pocket or turn in $5 found on the ground?– Object when the experimenter referred to him/her by the

wrong name?– Comb his/her hair before posing for a photograph in the

lab?• How confident are you in your answer (50-100%)?• Mean confidence: 75.7%• Mean accuracy: 60.8%– When 100% confident, accuracy = 78.5%!

Dunning et al., 1990

Overconfidence in self predictions• Will you…– Visit San Francisco more than 3 times this year?– Participate in the dorm play?– Drop a course?– Question your decision to attend Stanford?– Become best friends with your roommate?– Visit a friend more than 100 miles away?– Get a new boy/girlfriend?

• Overall confidence: 82.3%• Overall accuracy: 68.2%– When participants were 100% confident, they were

correct only 77.4% of the time!Vallone et al., 1990

Causes of overconfidence

• Hindsight bias• Motivated and non-motivated confirmatory

thinking– Confirmation bias– Wishful thinking

• Naïve realism

Naïve realism• You drive up to San Francisco with friends to

celebrate the end of the quarter. The plans include dinner and then some entertainment afterward.– How much money will you personally spend on the

dinner?• You receive a telephone call from a survey firm.

You initially agree to answer some questions. There is a long series of questions– How many minutes will you spend answering

questions before you end the call?

Griffin, Dunning, & Ross, 1990

Naïve realism

• Three conditions:– Control condition: Confidence intervals simply

given a second time– “Assumers” condition: Asked to assume that their

image of the situation was, in fact, correct in all details

– Multiple construal condition: Asked to describe several alternative ways the situation they would be in could turn out

Griffin, Dunning, & Ross, 1990

Naïve realism

Griffin, Dunning, & Ross, 1990

Summary• Engage “System 2”– Learn the common errors that people make in our

uncertain world• They rely too much on affect, availability and representativeness• They’re overconfident in their decisions

– Take a skeptical mindset even when you like an initial judgment• Don’t be an “assumer”

– Invoke an audience to which you need to justify your thinking

– Next time: What is construal?