Decision Making under Uncertainty: From Heuristics and Biases to Neuroeconomics

Hartmut LeutholdDepartment of Psychology

Outline

Normative TheoriesDescriptive TheoriesHeuristics and BiasesDual-Process ModelsPreference, Valuation and Brain

Assumptions

Psychology Economics[Neuroscience]

1 N(agents)

Limited processing powerTime constraintsDynamic cognitive-affective system Prior experiences shape expectationsUse of diagnostic information

Will share values go up?

Can I trust the expert’s advice when making a risky

financial decision?

A fuel efficient car or a fancy sports car?

Organic or standard range products?

Judgment and Decision

Judgments involve an evaluation along a single entity

→ how attractive is a person, how likely is X to occur?

“I decided against my better judgment …”

Decisions are defined by

a choice among at least 2 alternatives

expectation about potential outcomes

value of outcomes can be assessed

uncertainty – ambiguity and risk of outcome

Judgment and Decision

Blaise Pascal Choose the option with highest Expected Value

risk neutral = indifferent between gamble and EV

risk averse = preference for sure payment to a risky

gamble of equal or higher EV

risk seeking = preference for gamble with lower EV

Coin flipping game: Head = £ 100 and Tail = £ 0,

Certain £ 49

Normative Theories

Daniel BernoulliChoose the option with highest Expected Utility

→ psychological value assigned to outcomeconcave utility function implies that utility gained by receiving £50 is more than half the utilitygained by receiving £100

→ Perception of monetary value

depends on your current wealth

Normative Theories

Herbert SimonBounded Rationality – models need to reflect the

properties and limits of the mind and environment

Kahneman & TverskyJudgment under uncertainty: Heuristics and biases

Prospect Theory (1979):

implies risk seeking for low-probability gains and high-

probability losses and risk aversion for reverse scenario

Descriptive Theories

Which lottery ticket would you choose?

Heuristics and Biases

A   01   02   03   04   05  06 A   04   07   19   24   37   41

A   01   02   25   26   48   49A   05   10   15   20   25   30

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 social justice and also participated in anti-nuclear demonstrations. Please rank the following statements by their probability (1-8).

(5.2) Linda is a teacher in elementary school(3.3) Linda works in a bookstore and takes Yoga classes(2.1) Linda is active in the feminist movement(3.1) Linda is a psychiatric social worker(5.4) Linda is a member of the League of Women Voters(6.2) Linda is a bank teller(6.4) Linda is an insurance salesperson(4.1) Linda is a bank teller and is active in the feminist movement

Heuristics and Biases

Heuristics and Biases

RepresentativenessWe judge the likelihood of an entity in terms of how well it represents, or matches, a particular prototype

AvailabilityIn English words, does k appear more often as the first or third letter?Which has more people – Cuba or Venezuela?

People estimate the frequency of an event or the likelihood of its occurrence “by the ease with which instances or associations come to mind”

Heuristics and Biases

Memory

Which is the capital of France?

AnchoringGroup A: Would you pay £25 to clean up River Clyde to maintain

fish population?

Group B: Would you pay £200 to clean up River Clyde to maintain fish population?

A + B: How much do you think would the average Glaswegian pay?

A + B: Please estimate the percentage of Glasgow residents who would pay £ 100.

An uninformative number biases judgment Priming effect - activation in working memory system?

Heuristics and Biases

Evaluation of ExperiencesPatients who are undergoing a painful medical procedure (colonoscopy) report every 60 secs their experienced pain intensity. After the episode, they evaluate the global pain or discomfort.

Heuristics and Biases

From Kahneman & Frederick, 2006

Evaluation of Experiences

Peak and end pain accurately predicted global evaluations and future choices, whereas the duration effect was small.

Episode is represented by a prototypical moment. Associated affective value substitutes the global target attribute.

Peak/end ruleDuration neglect

Heuristics and Biases

Redelmeier & Kahneman (1996) 

Heuristics and Biases

Framing effectDr. X tells his patient A that 10% of people diewhile undergoing the surgery. Dr. Z tells another patient B that 90 % survive while undergoing the surgery. Will A and B be equally open to surgery?

Affect heuristic – reliance on a state of feeling that represents a positive or negative quality such as “good” or “bad”

Emotional Memory

From LaBar & Cabeza, 2006

Heuristics and Biases

Framing effect (DeMartino et al, 2006)

Two concurrently active systems, performing automatic (hot, intuitive) versus controlled (cold, rational) processing operations, compete for the control of behaviour.

Dual-Process Model

Name the ink colour of printed colour words

red - green - blue - black

Dual-Process Model

MacDonald et al. (2000)

Dual-Process Model

From Botvinick et al., 2001

Dual-Process Model

From Lieberman, 2007

Neuroanatomy

From Purves et al., 2008

Dual-Process Model

From Lieberman, 2007

Preference

Coca Cola – Pepsi Cola (McClure et al. 2004)VMPFC activity correlates with preference

To guide our behaviour we rapidly evaluate themotivational consequences of eventsGehring and Willoughby (2002) study neuralcorrelates in a game situation: → expected value of monetary outcome is zero → same probability of gains and losses in long run

Choice and Valuation

Medial Frontal Negativity (MFN) ~ motivationaloutcome of the event

0 ms = onset of outcome stimulus

Choice and Valuation

Context effects on choicebehaviour → losses leadto risk seeking behaviour

Correspondence betweenrisk-taking behaviour andoutcome processing as reflected by MFN

Short-term adjustmentsin decision making

Choice and Valuation

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