Final Lecture 20: April 3 Flashcards
what is Base Rate Neglect:
When you fail to use information about the prior probability of an event to judge the likelihood of an event
what is Conjunction fallacy:
False belief that the conjunction of two conditions is more likely than either single condition
eg Linda the feminist Bank Teller
¤ Because the description was more representative of both categories people think the
conjunction is the most likely label
Anchoring and Adjust judgements are too heavily influenced bywhat
initial values
what is Regression toward the mean:
when a process is somewhat random (i.e. weak correlation), extreme values will be closer to the mean (i.e. less extreme) when measured a second time
Regression toward the mean is related to what
illusionary correlations
what are illusionary correlations
People tend to see causal relationships even when there are none
A pageant mom rewards her daughter when she preforms unexpectedly well and wins a pageant. But the next pageant she comes in last place, the mom punishes her and the following competition she does well. The mom concludes punishment works better than rewards.
is this accurate
Related to our understanding of the roles of reward and punishment on learning
¤ Can’t always attribute changes in performance to manipulations ¤ Sometimes it’s just noise
Why use Heuristics
People are thought to be Bounded rational
what is Bounded rational
meaning they are limited by both environmental constraints (e.g. time pressure) and individual constraints (e.g. working memory, attention)
People are Satisficers
what is this (Bounded Rationality)
look for solutions that are “good enough”
¤ ”Making do” with the limitations we have as humans
¤ Although heuristics sometimes provide incorrect answers and lead to biases; they also work
what is Ecological Rationality
which sees heuristics not as a “good enough” approach to solving a problem but as the optimal approach
While previous views on heuristics drew a separation between how we should act and how we do act, Ecological rationality does what
does not distinguish these two
Given the right environment, a heuristic can be better than what
optimization or other complex strategies
Say you have some money you want to invest and a bunch of options to choose form, but limited information about how risky each one is or the past performance…
¤ Equally dividing your assets (money) among the options (1/N heuristic) has been shown to provide better results than other more complex optimization algorithms
¤ Sometimes heuristics (give the right circumstances) can be better than complex strategies
what is this an example of
Ecological Rationality
Summary: Heuristics and Biases
Heuristics and biases arise from the limitations we face but can sometimes produce correct responses
¤ Applying heuristics too often can lead to biases
Several examples of Heuristics ¤ Availability
¤ Representativeness
¤ Anchoring and adjustment ¤ Regression towards the Mean
Which of the following is not true about Heuristics and biases?
¤ A) The Conjunction Fallacy arises because people use the Availability Heuristic ¤ B) Regression towards the mean only happens where there is not a perfect correlation ¤ C) Heuristics sometimes can give the right answer
¤ D) People use heuristics because we are boundedly rational
A) The Conjunction Fallacy arises because people use the Availability Heuristic
wha are the Kinds of Decision-Making
Perceptual Decision Making
Value-based Decision making
Risk
what is Perceptual Decision Making:
objective (externally defined) criterion for making your choice ¤ Are the dots moving left or right?
what is ¤ Value-based Decision making:
subjective (internally defined) criterion for making your choice ¤ Do I want cake or ice cream for dessert?
¤ Depends on motivational state and goal
what is ¤ Risk
can be defined as taking an action despite the outcome being uncertain ¤ Specific to Value-based decision making
explain Risky decision making
¤ It is adaptive to be able to make decisions when there is risk
¤ Most people are risk averse
¤ Extremes in risk taking (high or low) can be very harmful ¤ Stagnant living
¤ Addiction and impulsivity
wha are the 4 Risk attitude profiles
Risk premium
Risk averse
Risk neutral
Risk seeking:
what is Risk premium
difference between expected gains of a risky option and a certain option
what is Risk averse:
decision maker has positive risk premium
¤ Need a chance at winning a lot more than a certain option to select the risky option
what is ¤ Risk neutral:
decision maker has zero risk premium
¤ No difference in the options
what is ¤ Risk seeking:
decision maker has negative risk premium
¤ Doesn’t need the chance at winning more than the certain option to gamble
are Risk preferences irrational
Risk preferences are not themselves irrational
what can account for individuals’ risk
preferences
Classic (rational) economic theories (Expected Utility theory)
Classic (rational) economic theories (Expected Utility theory) can account for individuals’ risk
preferences
¤ However, it has been empirically observed that people are inconsistent in their preferences which has been taken as awhat
bias
Classic (rational) economic theories (Expected Utility theory) can account for individuals’ risk
preferences
¤ However, it has been empirically observed that people are inconsistent in their preferences which has been taken as a bias
¤ These inconsistencies cannot be explained using rational economic theories (How should people act? what cane explain thm
Birth of Behavioural Economics: How do people act?
what is The framing effect
¤ Inconsistent Risk preference depending on the framing (loss vs gains) of the problem
Imagine that the country is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Which program would you choose?
¤ If Program A is adopted, 200 lives being saved.
¤ If Program B is adopted, there is a 1 in 3 probability of saving 600 lives and a 2 in 3 probability of saving no lives.
¤If Program C is adopted, exactly 400 people will die.
¤ If Program D is adopted, there is a 1 in 3 probability that nobody will die and a 2 in 3 probability that all 600 will die.
this is an example of what
the framing effect
People are risk-averse when the options are described as gains explain
¤ They prefer the sure thing and go for safety ¤ The cup is half full – do I need more?
People are risk-seeking when the options are described as losses explain
¤ They can tolerate an uncertain thing and risk a game
¤ The cup half empty – don’t take any more away!
what is Endowment Effect
Once ownership is established, people are averse to give it up
people given a mug want to sell it for more than what people were willing to buy it for
whats Prospect Theory
Birth of Behavioural Economics (Kahneman & Tversky 1979, 1992) ¤ Two major contributions:
¤ Shape of Utility function (losses vs Gains)
¤ Shape of Probability Weighting function (Unlikely vs Likely events)
¤ Describes how people do act not how people should act
Prospect Theory predictswhat
risk preferences when gambling
what is Utility:
Subjective value assigned to an object; satisfaction
¤ Context dependent
Utility is assigned to what
monetary amount as a function of someone’s current state (reference point) and not in absolute value
¤ Deviations from the reference point will determine risk preference
¤ Anchor and Adjustment heuristic
what is Utility function
Describes how people map money to satisfaction
¤ The extra satisfaction earned from gaining a dollar is larger when you only have $1 vs when you have $1M
explain how utility function is Asymmetrical
Steeper for Losses than Gains $1 lost hurts more than one dollar earned
¤ Losses loom larger than gains (framing effect)
for Prospect Theory, are probabilities treated objectively
Probabilities are not treated objectively ¤ Extreme events tend to be rare
explain Extremity of event related to perceived probability
¤ Unlikely events are overestimated ¤ Likely events are underestimated
Availability of an option changes what
the perceived frequency of occurrence
high prob and losses =
Risk Seeking
high prob and gains =
Risk Averse
Low Probability and losses =
Risk Averse
Low Probability and gains =
Risk Seeking
Summary: Prospect Theory
Prospect Theory describes how people behave ¤ What people do vs what people should do?
The Utility function describes how people treat gains & losses ¤ Losses loom larger than gains
¤ Linked to the framing effect
Probability Weighting function describes how people understand likelihoods ¤ People tend to overestimate rare events and underestimate mundane events
what is Dual Process Theory
It is thought that there are two systems for making decisions
system 1 and system 2
what is System 1:
Fast, effortless, automatic, intuitive, emotional
¤ Thought to be related to the evolutionarily ancient parts of the brain (common to many species) ¤ Limbic System
¤ Heuristics and biases
what is System 2:
Slow, deliberative, Effortful, explicit, logical ¤ Thought to be unique to humans, evolutionarily recent ¤ Frontal cortex
Participants made choices between two outcomes framed as gains or losses ¤ A risky (A gamble) outcome
¤ A safe (A Sure thing) outcome
what happens in the amygdala
Increased amygdala activity for chosen safe outcomes for gains and chosen risky outcomes for losses suggests that an emotional response may underlie the framing effect
¤ Unclear if activity is result of choice or predicts choice
Participants read newspaper stories designed to induce positive (happy) or negative (sad) affect
¤ Then, the participants estimated frequencies of death for various causes
¤ High risk
¤ Non-fatal risk
¤ Low risk life problems what was the conclusion
There were higher estimates of death frequency when people were in a negative mood compared to a positive mood
what is Prediction error (PE):
The difference between what you predicted would happen and what actually happened
Example: You go to buy Perrier
¤ Surprise! It’s on special (cheaper than usual)
¤ Inflation! It’s marked up (more expensive than usual)
way are these examples of
prediction error
give the purpose of Prediction Errors
Prediction Errors are thought to drive learning (reinforcement learning)
Prediction errors can be hat
¤ Positive: Unexpectedly good outcome ¤ Negative: Unexpectedly Bad outcome
what is th Mood affect real world Gambling
Prediction errors in sports outcomes and the weather have been found to affect people’s mood
¤ Positive PE increases positive affect
¤ Negative PE increases negative affect
¤ Changes in mood predict risky decision-makingàwhen people are happy they are more likely to gamble
Summary
Evidence suggests biases in risky choice are related to affective (as opposed to deliberative) decision-making
¤ Activity in brain areas implicated in emotion have been linked with biased decision making
¤ Changes in mood relate to assessment of risk level à negative mood increased people’s
estimated frequency of negative events
¤ Changes in mood driven by prediction errors have been found to influence people’s risk attitudes in the real world
Which of the following statements about Prospect Theory is false?
¤ A) It tells us how people do act instead of how the should act
¤ B) The asymmetry of the utility function is made to account for the framing effect
¤ C) People tend to overestimate the probability of rare events and underestimate the probability of common events
¤ D) Utility is an immutable property and is reference independent
D) Utility is an immutable property and is reference independent
