Lecture 4: Emotion’s relation to mental processes ... · “ The equilibrium or balance between...

Lecture 4: Emotion’s relation to mental processes (judgment and decision-making)

Goals

Give some examples of why important to model

human decision-making

Review rational choice theory (current best model)

Illustrate “emotional” departures from RCT

Provide framework for organizing various ways that

emotion departs from RCT predictions

Experiment

Guest lecture on NeuroscienceGilly KoritzkyBrain and Creativity Institute

Emotion and Rationality

Emotion is often said to “distort” reason. What

does that mean?

It means there is a theory of people “should” make

decisions (Rational Choice Theory)

– Follows from a set of principles that seem an irrefutable

characteristic of good decision-making

And people don’t follow that theory

And emotions help explain departures from

rational choice theory

Why should we care that people not “rational”

Rational models are used to predict human decisions and

make policy decisions across wide range of applications

– Economic decisions: how individuals buy and invest

– Public policy decisions: how will programs impact the happiness and

well-being of populations

– Consumer choice: will consumers be satisfied by a product

– Market mechanisms design: will policies governing transactions in an

online marketplace be efficient

– Technology acceptance

Rational models are used to guide automated systems

– Bargaining agents

– Security agents

– Navigation systems

Example: Security

Milind

Tambe

Rational models (game theory) can help us build

decision-aids for such efficient security resource

allocation. Use computational methods to predict

the decision-making of potential criminals

Example: Navigation

Sarit Kraus

Rational models can help us recommender systems such

as driver navigation systems. Challenge is to recommend

high quality routes that satisfy user preferences while

achieving other goals (energy efficiency)

Rational Choice Theory

Developed over centuries

Central foundation of economic decision-making

Serves two basic purposes– Normative: how people (and machines) should act and think

Helps us avoid confused, poor thinking

Helps us analyze arguments

Aids in design of “optimal” artificial decision-makers

– Descriptive: how people (and machines) actually act and think? Fundamental postulate of economics: people act rationally

(allows that individuals may not be rational but this can be viewed as noise so that the

population will act rationally)

Variants of Rational Choice Theory

Decision theory centers on cost-benefit

calculations that individuals make without

reference to anyone else’s plans

Game theory analyzes how people make choices

based on what they expect other individuals to do.– We will discuss this when we consider social emotions

Axioms of Decision-Theory

Completeness:

– All actions (or objects) can be ranked in an order of preference;

indifference between two or more alternatives is possible

Transitivity: – If action (or object) a1 is preferred to action a2 and action a2 is preferred

to a3, then a1 is preferred to a3.

Tesla Model S BMW M6

AMC Pacer

Axioms of Decision-Theory

Continuity:

– When there are three lotteries (X, Y and Z), X preferred to Y and Y

preferred to Z, then there should be a mixture of X and Z such that an

individual is indifferent between this mix and Y

Independence:– If we mix two lotteries (X, Y) with a third one, the preference ordering

of the two mixtures will not change (is independent of) the particular

third lottery used

90% + 10% = 100%

50% + 50% 50% + 50%

Decision Theory (or Expected utility theory)

Decision framework that satisfies these axioms

Outcomes can be described by a utility function– The value (or happiness) derived from achieving this state

– E.G. Money could be a person’s measure of happiness

The value of winning a $1,000,000 lottery ticket is $1,000,000

Outcomes can be described by a probability fn.– The likelihood that this state might be achieved in the future

Decisions are then driven by Expected Utility

B

Utility1

Utility2

Utility3

2

Utility6

2

Utility4

Utility5

1

Decision Point

Chance Event

Decision Theory: people utility maximizers

Utility Theory doesn’t assume money is people’s utility function

People assign utility to money. Different people have different utility fn.

Money not necessarily equal to happiness

Daniel Bernoulli 1738

Utility is

the “anticipated pleasure” of wealth

rather than wealth per se

14

Utility Theory doesn’t assume money is people’s utility function

People assign utility to money. Different people have different utility fn.

Utility value

Monetary value

This allows us to capture certain attitudes

towards risk

Money not necessarily equal to happiness

15

People have one of three attitudes toward risk. People can be risk avoiders,

risk seekers (or risk lover) , or indifferent toward risk (risk neutral).

Monetary

Value

Utility Value

Risk avoider

Risk lover

Risk neutral

Utility of money shown for different types of people. Note that for equal

increments in dollar value the utility either rises at a decreasing rate (avoider),

constant rate or increasing rate (lover).

Key point: Absolute value of outcome not important. It is feeling this evokes

Summary: Rational Choice Theory

Decision theory centers on cost-benefit

calculations that individuals make without

reference to anyone else’s plans

Captures many aspects of how people make

decisions (maximize pleasure)

Core assumption underling most economic theory

and economic decision

Core assumption underlying most artificially

intelligent systems

Is Expected Utility a good model of human choice?

Test

Test

50% + 50% 50% + 50%

Influences of Emotion on decision-making(Loewenstein and Lerner 2003)

Start with decision theoryPeople try to maximize expected pleasure (utility)

Decision/

behavior

Expected

consequences

Expected

emotions

Daniel Bernoulli

PROBLEM: If decision theory argues people trying to maximize

future happiness, there are a couple of big problems here

Adam Smith

First problem with equating expected utility with anticipated emotion

Human estimates of future

happiness violate the axioms of

decision-theory

Expected emotions: Risk

Expected emotions are shaped by uncertainty (risk) in ways

not predicted by utility theory

People overweigh small probabilities

People underestimate large probabilities

Losses Loom larger than gains

Maximize

Expected

Utility

ProbabilityExpected

emotions

Prospect TheoryKahneman & Tversky, 1979

Relaxes the independence assumption

– Distinguishes subjective from objective probability: People overweigh small

probabilities and underestimate large ones

– People assign different utility to losses and gains

Maximize

Expected

Utility

ProbabilityExpected

emotionsS

ub

jecti

ve

pro

ba

bil

ity

Probability

function

Utility

function

Probability bias shaped by fear

Su

bje

cti

ve p

rob

ab

ilit

y

Probability

function

Another Test

Again, most people’s preferences violate the

independence assumption

Expected emotions: Regret

Expected emotions are shaped by our regret over what might

have happened

Maximize

Expected

Utility

ProbabilityExpected

emotions

Mellers (1997) decision affect theory

Assume play lottery with outcomes A and B. A occurs

RegretA ≈ UtilityA + d(UtilityA – UtilityB) (1 – ProbA)

Where d is a “disappointment function”

Argues people try to minimize regret

Second problem with equating expected utility with anticipated emotion

Humans are bad at forecasting how

they will feel in the future

(estimated happiness ≠ experienced happiness)

It seemed a good idea at the time…

Affective forecasting

People not so good at forecasting – What: what emotion they will feel following a decision

– How much: the intensity of the experience

– How long: the duration of the emotion

People fail to account for their ability to cope

– Become desensitized to positive circumstances

– Become resigned to negative circumstances

People overweigh outcomes in immediate focus

– E.g., Students in mid-west predicted they would be happier moving to

California; students in California predicted they’d be less happy in mid-

west; yet both equally happy

Affective forecasting (see guest lecture)

Some evidence that there are two distinct

mechanisms for forecasting

– Simulation route:

Vividly imagine being in a certain situation

“read” our bodily reactions to that situation (Damasio’s somatic

marker hypothesis)

– Reasoning route:

Reason about emotions: e.g., I expect I would feel this way

Evidence that the “reasoning” approach more suspect to mis-

forecasting effects

MacInnis. Whan. "Looking through the crystal ball: Affective forecasting and misforecasting in

consumer behavior." Review of Marketing Research 2 (2005): 43-80.

One proposed solution

Expected emotions are time dependent: care less about

events far in the future (explains procrastination?)

Can be modeled with hyperbolic discounting

Make utility a

function of time

Decision/

behavior

Expected

consequences

Expected

emotions

Expected emotions violate axioms of EU

– Prospect theory

– Regret theory

Expected emotion ≠ experienced emotion

– Hyperbolic discounting

Summary of first set of challenges

But that’s not all….

Immediate influences

Maximize

Expected

Utility

Probability UtilityImmediate

emotions

Current emotions changes the decision procedure

Negative emotions narrow intentional focus (on potential threats) and deeper processing of threats

Question pre-conceptions, second guessing

Slower decision making

Positive emotions broaden attentional focus

Shallow processing, quick decisions

Uncritically accept initial judgments/stereotypes

Immediate influences

Maximize

Expected

Utility

Probability UtilityImmediate

emotions

Low intensity emotions

Inform cognition (Affect as information – Clore)

Easily suppressed/overcome if aware of them

High intensity emotions

Can overwhelm cognition. People report being “out of control”

Eg. Phobicsreport there is nothing to fear but are helpless to act on that

awareness

AngerLerner&Tiedens06:

Portrait of the angry

decision maker

Anticipatory influences

Maximize

Expected

Utility

Probability Utility

Anticipatory

influences

Immediate

emotions

Anticipated emotions change our immediate

emotions

Incidental influences

Maximize

Expected

Utility

Probability Utility

Anticipatory

influences

Unrelated events can influence our immediate

emotions

– Sunny day

– Happy or sad music

– Disgusting room

Incidental

influences

Immediate

emotions

EmotionAction

Tendencies“Affect”

PhysiologicalResponse

EnvironmentGoals/Beliefs/

Intentions

Appraisal Tendencies Framework (Han, Lerner, Keltner 2007.)

Desirability

Controllability

Causal Attribution

Emotion

Withdraw Sadness Lo Arousal

EnvironmentGoals/Beliefs/

Intentions

UNDESIRABLE

UNCONTROLABLE

BLAMEWORTHY

EmotionAction

Tendencies“Affect”

PhysiologicalResponse

EnvironmentGoals/Beliefs/

Intentions

Appraisal Tendencies Framework (Han, Lerner, Keltner 2007.)

Desirability

Controllability

Causal Attribution

Emotion

Withdraw Sadness Lo Arousal

EnvironmentGoals/Beliefs/

Intentions

UNDESIRABLE

CONTROLABLE

BLAMEWORTHY

APPROACH ANGER Hi Arousal

EmotionAction

Tendencies“Affect”

PhysiologicalResponse

EnvironmentGoals/Beliefs/

Intentions

Appraisal Tendencies Framework (Han, Lerner, Keltner 2007.)

Desirability

Controllability

Causal Attribution

Emotion

APPROACH ANGER Hi ArousalWithdraw Sadness Lo Arousal

EnvironmentGoals/Beliefs/

Intentions

UNDESIRABLE

CONTROLABLE

BLAMEWORTHY

UNCONTROLABLE

Summary

People don’t follow rational choice theory

Good mathematical models of some departures– E.g. prospect theory; discounting functions

Not so go mathematical models of others– Though appraisal theory (ATF) gives us some insight

Some influences integral to the situation– And therefore probably sensible adaptations

Some incidental– And therefore hard to argue that they are beneficial

Human Emotions in Decision-Making:

The Somatic Marker Hypothesis

Presented by Gilly Koritzky, Ph.D.

Brain and Creativity Institute

University of Southern California

Most of us are taught from early on that sound decision can only be based on logical, rational thinking.

- Emotion can only cloud the mind and interfere with good judgment.

- “Don’t get all emotional! Be rational!”

But there is evidence to suggest that “rational” decision making in fact depends on prior accurate emotional processing.

A Brief History

Phineas P. Gage (1823–1860), an American railroad construction

foreman, who survived a rock blasting accident in which a large iron rod

was driven completely through his head, destroying much of his brain's

left frontal lobe.

Before the accident, Phineas Gage was a man of normal intelligence, responsible, sociable, and popular among peers and friends.

He survived this accident with normal intelligence, memory, speech, sensation, and movement.

However, his (social) behavior changed completely: “ The equilibrium or balance between his intellectual faculties and animal propensities, seems to have been destroyed…

“ fitful, irreverent…

“ manifesting but little deference for his fellows…

“ impatient of restraint or advice when it conflicts with his desires…

“ obstinate, yet capricious and vacillating…

“In this regard his mind was radically changed, so decidedly that his friends and acquaintances said he was "no longer Gage".”

A Brief History

What region of Gage’s brain was damaged by the rod?

Many years later, scientists generated a computer modelling with the exact

dimensions of Gage’s skull.

Parietal, Temporal, and mid-brain areas, responsible for sensory and motor

function, speech, and memory were intact.

As can be seen, only the frontal lobe was affected.

Or, more precisely: the orbitofrontal cortex.

Patients with lesions in the

Ventro-Medial (Orbital) Prefrontal Cortex

Normal intelligence, But:

• Severe impairments in judgment and decision-making in real-life - In the financial domain (bankruptcies). - In the social domain (involvement with unscrupulous people). - Loss of close relationships, marriage, family, and friendship.

• Abnormalities in emotion Compromised ability to express emotion and to experience feelings in appropriate social situations.

An influential neural theory of decision-making, the Somatic Marker Hypothesis (SMH).

Emotion-related signals (somatic markers) assist cognitive processes in implementing decisions.

These somatic markers can be non-conscious: they can bias behavior even when a person is not really aware of them.

The Somatic Marker Hypothesis

(Antonio Damasio & Antoine Bechara)

Definitions:

EMOTION. A collection of physiological changes in body and brain states

triggered in response to an event.

Somatic Marker Hypothesis (SMH)

Definitions:

EMOTION. A collection of physiological changes in body and brain states

triggered in response to an event.

heart rate, skin conductance, endocrine release,

skin color, body posture, facial expression.

Feeling. What the individual senses or subjectively reports.

Somatic Marker Hypothesis (SMH)

Emotion “I have a bad

feeling about

this…” Signals sent to the forebrain

Testing the Somatic Marker Model:

The Iowa Gambling Task (IGT) paradigm for measuring decision-making

(Bechara, Damasio, Damasio, & Anderson)

Iowa Gambling Task (IGT)

DD

Gain per Card

$100

$1250

-$250

$100

$1250

-$250

$ 50

$250

+$250

$ 50

$250

+$250

AA BB CC

“Bad” Decks “Good” Decks

Loss per 10 Cards

Net per 10 Cards

5 sec

Onset of Card Selection

ANTICIPATORY SCR

(Before Choice)

REWARD/ PUNISHMENT SCR

(After Choice)

(a)

(b) Skin Conductance Response (SCR)

Bechara et al., 1994

The physiological measurement indicates that anticipatory emotion is

critical for good decision-making in many settings

What can we learn from all this about how computers can better

understand, sense, or simulate human behavior?

<discussion>

Modulating Factors

One of the fundamental questions in decision-making research is

how humans assign value to options.

Time: information conveying immediacy (e.g. getting a heart

disease tomorrow) exerts a stronger influence on decisions than

information conveying delayed/future outcomes (e.g. getting a

heart disease 20 years from now).

Probability: information conveying certainty exerts a stronger

influence on decisions than information about low-probability

outcomes.

Tangibility: information conveying tangibility exerts a

stronger influence on decisions than information about abstract,

intangible outcomes (easier to spend money on credit cards as

opposed to spending “real money”).

- - + + + Immediacy Delay

DA

5-HT

AC DLPC

VMPC A

Insula

Hy

p

Striatum

Reflective

Impulsive

a. b. c.

What if the same event triggers several, different responses?

Examples:

Immunizations, safety equipment (helmets)

- - + + + Immediacy Delay

DA

5-HT

AC DLPC

VMPC A

Insula

H

yp

Striatum

Reflective

Impulsive

a. b. c.

The mechanisms that determine the nature of this overall somatic state (i.e., being positive or negative) are consistent with the principles of natural selection: survival of the fittest.

Stronger somatic markers gain selective advantage over weaker ones.

The final decision is determined by the relative strengths of the pain/pleasure signals.

Is Emotion Always Beneficial for Decision-Making?

Emotions play a major role in the interaction between environmental conditions and human decision processes.

Our neural systems carry emotional signals, which provide valuable knowledge for making fast and often advantageous decisions.

But sometimes, these emotional signals interfere with rational decisions.

Thus, the challenge is:

- To discover the circumstances in which emotions can be either useful or disruptive

- To use reasoned coupling of circumstances and emotions as a guide to human decisions.

Thank You!

koritzky@usc.edu

Project thoughts

If PhD Student– Great to work on a topic related to thesis (assuming it is related to

emotion)

– Ideally work with another classmate from different research group (but

not required)

– Strongly encouraged to work in group (but not required)

Possible topic (modeling)

Moving beyond laboratory data– Learning from NFL games

Twitter data on “excitement” of ~400 games

Predicting excitement from game structure

– Learning from blog data

“Ground-zero mosque” blogs

Examining role of sacred values

Learning temporal dynamics– Emotions in unfolding situations

– Grit and resilience (persistence in face of failure)

Possible topic (modeling)

Decision-making in “games”– Have lots of data on people’s behavior in various decision games. Would

like to model their data and emotional responses

Other

Yo

u

Possible topic (Recognition)

Recognizing mental state (Video)– Have lots of data on people’s behavior in various decision games. Would

like to model their data and emotional responses

Possible topic (Recognition)

Recognizing mental state (Audio)– Have lots of data on people’s behavior in various decision games. Would

like to model their data and emotional responses

“Serious games”

Other

Yo

u

“Not so serious games”

EmotionAction

Tendencies“Affect”

PhysiologicalResponse

EnvironmentGoals/Beliefs/

Intentions

Desirability

Controllability

Causal Attribution