The Psychology of Judgment and

Decision Making

Part 1:

Heuristics and Biases

• How they affect people’s judgments and decisions• How they affect researchers• How they affect MIS

“ …people rely on a limited number of heurisitc principles which reduce cimplex tasks of assessing probabilities and prediciting values to sijmpler judgmental operations. In general, these heurisitcs are quite useful, but sometimes they lead to severe and systematic errors.” (from Tversky, & Kahneman, Science, 185, p.1124-1131.)

-> ‘People are systematically biased’

Definition: Heuristic and Bias

Section 1:

Perception, Memory, and Context Biases

A Foolish Consistency is the Hobgoblin of Small

Minds- Ralph Waldo Emerson

Previous Beliefs and Expectations Affect

PerceptionIt Looks Red

People Reconstruct Memories

Guess 4 NumbersNot Bad Guesses!My Numbers are1, 2, 5, and 16

Later

I Guessed 2, 3, 6 and 15I was Right!

Save The Red Elephan

ts

Cognitive Dissonance

Later

Joe

It WAS RedYou’ll Sign

My Petition, Won’t you?

I saw red Elephant,

X

The Halo Effect

That Elephant Has a Big Smile;

I bet He’s Red

Contextual Clues

Small Elephant Big Elephant

Parables of context biases and Purple Red elephants• People see what they expect to see (Mr.

Red)• People reconstruct memories (“I was right”)• People try to be “consistent” (It was red)• Nearby things affect perception (relativity)• People believe good things about good

people (The halo effect)

Escaping Context Biases

• Take note of context• Know yourself• Consider the possibility of

alternative outcomes

How to get the results you want from an

experiment, capitalizing on Perception, Memory

and Context(A roll play emphasizing the impact

perception, memory, and context can have in a research setting)

Halo Effect

Their Tool

•Host uses bad grammar

•Host has unkempt appearance

•Hosts uses poor body language (slouches)

Our Tool

•Host smiles and conveys excitement about the new tool

•Host is nicely dressed

•Host greets people as they enter the experiment

Create Expectations

Their Tool

•Host says “there is a chance our tool might work”

•Host says “we think our tool produces marginally better search results”

Our Tool

•Host expresses confidence about the performance of the new search tool.

•Host says “ we are excited about how effective our tool is”

Control Comparatives

Their Tool

•Begin with a warm-up exercise using state-of-the-art technology that is well polished.

•Show the group the best of breed searching tools available.

Our Tool

•Run the warm-up exercise on an old, slow computer attempting an impossible task.

•Provide a poor tool to achieve the task.

Get Them to Commit to Your Result

Their Tool

Conduct the following pre-experiment survey:

A. I am a good searcher who gets good results.

B. I am a jerk

(Please choose only A or B)

Our Tool

Conduct the following pre-experiment survey:

A. I learn quickly and do well with new tools.

B. I am a jerk

(Please choose only A or B)

Give Them Cues About How They Did

Their Tool

•Host frowns when he/she looks at the screen.

•Host shakes head and makes low grunting noises.

Our Tool

•Host smiles as he/she looks at the participants screen.

•Host takes notes by noticeably checking items off a list while nodding head.

Give Them Time to Reconstruct Memory

Their Tool

•Host ends the session by saying “Wow that took a long time….um…come back next week to fill out the survey.

Our Tool

•Host ends the session by saying “we were doing so well, we lost track of time. Oh well, just come back next week to fill out the survey.”

Section 2:

Survey Question Biases

Question phrasing, what answer choices are presented and how they

are presented...

Survey Questions Biases

On September 27, 2001, President Bush put forth the UN Hostile Powers resolution forbidding UN

Humanitarian Economic aid to Afghanistan. Was President Bush within his powers as the President of the US to enact such a United Nations Resolution?

a. President Bush was definitely within his power. b. President Bush overstepped his authority.

Will you vote in favor of a special finance package costing the average taxpayer $475 to finance

Operation Enduring Freedom?a. Yes, since it is likely Congress with provide for another tax rebate when the economy turns around.b. No, $475 in taxes negates the recent tax rebate.I would need to understand more about the finance package.

On September 27, 2001, President Bush put forth the UN Hostile Powers resolution forbidding UN Humanitarian Economic aid to Afghanistan.

Was President Bush within his powers as the President of the US to enact such a United Nations Resolution?

a. President Bush was definitely within his power. b. President Bush overstepped his authority.

Will you vote in favor of a special finance package costing the average taxpayer $475 to finance Operation Enduring Freedom?

a. Yes, since it is likely Congress with provide for another tax rebate when the economy turns around.b. No, $475 in taxes negates the recent tax rebate.I would need to understand more about the finance package.

Framing

Gain/Loss

Filtering

Ordering

Forbid vs. not allowingAttitude/

Behavior

pseudo-opinion

Research Life Cycle: Observation

• Through the use of surveys, observations verify or contradict MIS research hypotheses.– If the survey is biased, the research is nullified.

• Valid theories could be unnecessarily quashed.– If the survey is manipulated to reinforce the

hypothesis, the research will not withstand further investigation.• This will hider the acceptance of MIS as a discipline

Section 3:

Models of Decision Making

Expected Utility Theory

Wealth

Utility

--A “normative” theory of behavior

--Rational decision making principles

•Ordering of alternatives

•Dominance

•Cancellation

•Transitivity

•Continuity

•Invariance

The Allais Paradox-- Violation of Cancellation Principle

The paradox is that anyone choosing Alternative A in the first situation should also choose Alternative A in the second—otherwise, the Cancellation Principle is violated.

Alternative A: $1,000,000 for sureAlternative B: A 10% chance of getting $2,500,000,

an 89% chance of getting $1,000,000, and a 1% chance of getting $0

Alternative A:Alternative A: An 11% chance of getting $1,000,000, An 11% chance of getting $1,000,000, and an 89% chance of getting $0and an 89% chance of getting $0

Alternative B:Alternative B: A 10% chance of getting $2,500,000, A 10% chance of getting $2,500,000, and a 90% chance of getting $0and a 90% chance of getting $0

Intransitivity

If the difference in intelligence between any two applicants is greater than 10 points, choose the more intelligent applicant. If the difference between applicants is equal to or less than 10 points, choose the applicant with more experience.

IQ Experience (Yrs)

Fritz 120 1

Gertrude 110 2

Ralph 100 3

Prospect Theory--Improvement

– replaces notion of utility with value

– different value functions exist for gains and losses(Endowment Effect)

GrainsLosses

Valu

e

Prospect Theory--Improvement

• People’s tendency to overweight small probabilities.

• A reduction of the probability of an outcome by a constant factor has more impact when the outcome was initially certain than when it was merely probable—Certainty Effect

Other Alternatives to Expected Utility Theories

• Satisficing• Regret Theory• Multi-attribute Choice• Non-compensatory Strategies

Conclusions in MIS Field

• Take caution in making assumptions and principles—they are easily violated.

• Design as many experiments as you can, and consider as many conditions as you can to make your principle complete.

Section 4:

RepresentativenessAvailabilityRiskAnchoringRandomnessCausationAttribution

Heuristics And Biases

• People rely on heuristic when facing complicate decision• Advantage: normally “optimal” answer; reduce time and energy• Disadvantage: lead to biases and inconsistency• Focus: the process reaching the conclusion+consequent biases

Representativeness Heuristic

Definition:Judge probability by the degree to which A is representation of B

Example1:P(A) > P(AB)• Don’t be misled by highly detailed scenarios

Example2: The law of small numbersgambler’s fallacy vs. the hot hand• Remember that chance is not self correcting• Don’t expect too much alternations

Example3:use base rate information only when it’s consistent with their intuitive theories of cause and effect• Whenever possible, pay attention to base rates

Example4:tendency to make “nonregressive” predictions• Don’t misinterpret regression toward the mean

Representativeness Heuristic (2)

Availability HeuristicDefinition: judge probability by the ease with which the instance can be brought to mind

Examples: media, difficult to generate, visualize

The limits of imagination: difficult-to-imagine extremely negative outcome

Vividness Heuristic

Definition:concrete or imaginable; emotionally interesting or exciting; close in space or time

Examples: individual testimonials

it does exist, but is limited(time, laboratory research) how to conquer: explicitly comparing

Probability and Risk

• Bias in heuristic – More statistics: Bayes’ theory; – Wishful thinking: “happens to me? Never!”– Compound events: Welcome to the real world!

• Each of all 500 components has the rate of 99% working great, ….now you feel better?

– I am the expert…..so what?• Perception of risk are strongly biased in the direction of

preexisting view.

Probability and Risk (2)

• Managing the information system– Deal with new information

• Maintain accurate records• Avoid conservatism• Avoid convenience

– Be objective• Be aware of wishful thinking• Break component events into simple events

– Realize different perspectives– Reduce risk in system building

• Introductory example: Average January temperature in Pocatello, Idaho

• The insufficient adjustment up or down from an original starting value, or anchor.

• Very Robust– Works with extreme anchors

• Examples– Real estate– Software development

• “Give me a preliminary estimate…”

Anchoring and Adjustment

Anchoring and Adjustment in Research

• Possible problems– Anchoring on previous research– Anchoring on a “hunch”

• Solutions– Be skeptical of previous research– Be thorough with methodology

Perception of Randomness

• Coincidence– Odds of particular episode happening

are low, but odds of some similar episode happening somewhere are high

– Examples• Dr. Booker’s story of meeting Dr.

Nunamaker• Which one is more random?

– 0111001000111001011011– 0010101010110101000101

Randomness and Research• Finding patterns in research data

that don’t exist– Stick to the methodologies and

statistical analysis

• Coincidences happen– Take advantage of those coincidences

that happen– Increase the odds of coincidences by

networking

Correlation, Causation and Control (CCC)

• Correlation: whether two variables are related.– Illusory correlations

• Common sense dominated• bacon-tiger vs. bacon-egg

– Invisible correlations:• Absence of expectation• meat consumption vs. colon cancer

CCC (2)

• Causation– Correlation and Causation

• Control– Self confident: I can control myself

better!– Helps that harms: connections

between health and a sense of control

CCC (3)

• Take-aways– Bias in information colleting and

decision making– Focus on more than confirming and

positive cases– Observation vs. expectation– Distinguish between correlation and

causation

Attribution Theory

• Definition: Attribution theory is a psychological theory about how people make “causal attribution,” or explanations for the causes of actions and outcomes

Important Exception

• Attribution theory works most of the time, but there are several important exceptions

• When people disregard consensus information

• Salience information has more impact• Behavior is the most salient thing in a

social setting

Important Exception (2)

• Difference in focus between actors and observers

• People rely heavily on the most salient factors at the time

• Other attributional biases

Methods to Avoid Attributional Pitfalls

• Pay close attention to consensus information

• Ask how you would have behaved if thrust into the same circumstance

Section 5:

Biases in Decision Making in Social and Group Contexts

Group Influences

• Social facilitation (Mastery vs. Performance, 1965)

• Social loafing (Work in group vs. Work alone, 1965)

• Bystander intervention (Are you above 9?)

Group influences (2)

• Taking cues from those who are similar;

• Social analgesia (Influenced by perceptions of others);

• GroupThink: loyalty and pressures to conform;

• Minority influence on majority.

Biases in Group Research

• Individual-level biases exist in groups as well;

• Preexisting tendencies are amplified;• The less permissive the leader is, the

worse the group performs;• The group performs no better than the

best member;• Brainstorming in group is less effective

than conducting with people individually.

Section 6:

Common Traps

• Overconfidence• Self-fulfilling prophecies• Behavioral Trap

Common Problems

Overconfidence (OC)• A belief in ability or understanding

that adversely affects a decision– Space Shuttle Challenger– Pearl Harbor

• Heuristics– Measure or assessment of confidence

level– Accuracy of decision

• Bias– Discrepancies between accuracy and

confidence

Overconfidence: Causes & Impacts

• Possible Causes– When judgment difficult (no right answer)– Ignorance (initial phases of research)

• Impacts– Extreme

• Overconfidence when essentially certain• Not just a consequence of underestimating risk or

misunderstanding

– Social• Wrongful convictions• Societal/moral losses due to decision maker

overconfidence• more confidence & belief in what U are doing

Overconfidence Fixes• Calibration

– Bringing decision maker’s confidence in line with accuracy

– People can learn– Lots of feedback after decision making– Takeaway:

“Stop to consider reasons why your judgment might be wrong”

Overconfidence and MIS• Design system -> feel good -> overlook

bug

• Literature review -> feel informed -> faulty conclusion

Overconfidence and MIS• May reduce flexibility in judgment

May Reduce

• Dissertation -> ask questions to learn -> ask yourself questions to verify your thoughts

Self-Fulfilling Prophecies (SFP)

• Confirmation Bias– A positive testing pattern (confirmation

bias) leading to difficulties in decision making

Answer

Biased decision space

Total Decision space

SFP Model

Source: http://www.mhhe.com/socscience/social/ibank/set-1.htm

Pygmalion Affect (SFP)

• A false definition of a situation causing a new behavior making an original false conception true

• Cause:– Stereotypes, perceptions

• Advantage (if used properly):– Treat people what they ought to be and

you help them become what they are capable of being

• Disadvantage:– Self fulfilling prophecies, if not careful

SFP Impacts• Pygmalion Affect

– Favoritism in classroom by teacher towards “gifted” students• Gifted students excel

• Perceptions of women by men – Male subject presented with snapshot of

attractive womenand unattractive woman• Attractive women favored after phone

conversation

SFP Impacts (2)

•Interview process based on race

–Minorities performing differently during interview process when interviewer is postured “defensively” or with “distance”

SFP Fixes

• Focus on motivational factors– Warning interviewers about questions

that indicate closed-mindedness– Can be used to motivate “problem”

students

• Request “disconfirming” information during interviews– Similar to proving null-hypothesis

before conclusion??

• Possibly by asking asking why judgments might be wrong

SFP and MIS• Research question produces results found in

context of original research question• Avoid testing techniques/methodologies that are

too narrow – confirmation bias– System design– Research hypothesis

• Favoritism based on expected or forecasted performance – Pygmalion affect– Design technique– “Upcoming” technology

Behavioral Traps• A course of action that starts out as

promising, but later becomes undesirable– Traps

• Avoiding potentially beneficial behavior– Waiting on hold for tech-support– Exercise

– Counter-Traps• Potentially harmful behavior

– Avoiding chores– Cigarette smoking

Behavioral Trap Categories

• Time delay– Instant gratification vs. long term

consequences• Smoking one more cigarette

• Ignorance– Result of action not understood or predictable

at start of action• Smokers in the 19th century• Starting a new job only to find out that it

sucks.

Behavioral Trap Categories (2)

•Investment

–Prior investment of resources (e.g., time, money) leading to choices not normally made

•Vietnam war

•R & D investment (time, money) only to be out done by competition

–Should project continue????

–Lead to “sunk-costs”

Behavioral Trap Categories (3)

• Deterioration– Similar to Investment traps, but

benefits and costs change over time

Avoid crop loss ($$) even though negative environmental and social impacts

Kill bugs, Increase Crop Yields

Insecticide Use

Avoid withdrawalEnjoymentHeroin User

Over timeStartSymptom

Behavioral Trap Categories (4)

•Collective

–Quest for self interests having negative impacts on group

•Two criminals offered choice: confess or go to jail

–1 Confesses no jail -> partner gets 10 years

–2 Confess -> both get 5 years

–No confession -> both get 1 year

Behavioral Trap Fixes

• These traps often don’t last long– People learn and move on

• Corporate leaders stop wasting money• Girlfriend dumps boyfriend (he calls old

girlfriend)

• Set limits in advance– Use limits to assess continuation

Behavioral Traps and MIS

• Starting system design before jumping to code

• Gather facts before making conclusions• Identifying scope of project before

starting and assessing status and progress regularly

• Identifying that research question may not take expected path and adapting.

Part 2:

Decision Making and Heuristics in a Complex World

Heuristics in a Complex World• Humans are “boundedly rational”

given the amount of information necessary for rationality and human cognitive abilities

• Future is difficult to predict, both externally (states of the world) and internally (future preferences)

-> Humans use simple heuristics to satisfice rather than optimize

“Simple Heuristics that Make Us Smart…”

Heuristics are … frugal: get away with little

information… fast: don’t need long computation… cheap: don’t need costly information

search, storage, and computation… robust: perform better than

“optimal” regression on new data sets; less affected by noise

Overconfidence Revisited

• Questions in overconfidence studies are not randomly sampled from the environment, but selected by researchers

• Frequency judgments of correct answers are quite well-calibrated

-> Should researchers focus on finding biases or explaining normal functioning?

-> Which perspective is better for MIS researchers?

Heuristics and Biases: A Paradigm

• Tversky and Kahneman’s heuristics and biases has been the dominating paradigm in JDM research for about the last 30 years

• What are the benefits and costs of a strong paradigm?

• When does a discipline need a paradigm shift? (When researchers get bored?)

• What is the ruling paradigm in MIS? How “strong” is it? What is its effect?

New Perspective in JDM: Emotions &

Neuroscience

• “Risk as Feeling”• “Regret Avoidance” • Mood and Decision Making• “Descartes’ Paradox”• “Emotion as Information”