decision making

Question 1

Describe one respect in which Prospect Theory extends on Expected Utility Theory?

Answer 1

Prospect Theory proposes that losses loom larger than gains.

Question 2

In the context of Prospect Theory, what is a ‘frame’?

Answer 2

The characterisation of a possible outcome as a gain or a loss.

Question 3

A prediction of Prospect Theory?

Answer 3

Ad campaigns emphasising loss of good health due to smoking are less effective than might be expected because people are risk-seeking in the face of possible losses.

Question 4

What is a decision?

Answer 4

A choice made between multiple other options, which is processed from our environment through our brains processing system (sensation, perception, short + long term memory).

Transformed in systematic ways
Used stored information
Cognitive process
Tend to decide based on favorable outcomes

Question 5

What is a model?

Answer 5

A model is the framework that describes the underlying process of decision making.

Recognizes the analogy between mind and a computer

Example of a Model = Heuristic and Biases Model of Decision-Making OR ‘Fast and Frugal Heuristics’ Model

Question 6

How have researchers used ‘toy problems’ to build models of decision-making?

Answer 6

Toy Problems are simplified decision-making scenarios with determined answers and well understood cues. The observed behaviour patterns allow researchers to construct a model.

Focus on the nature of the task and the nature of the brain machinery with regard to one of three questions concerning
computational, algorithmic and implementational.

Toy Problems are utilized to build models of decision-making as they allow researchers to study participant behaviour in a controlled, experimental setting.

Question 7

Levels of Analysis

Answer 7

**Computational (strategic) Level
**what does the process solve?

**Algorithmic Level
**through what series of steps is input transformed into output?

**Implementational Level
**how are the transformational steps physically realised in the brain?

Models at the computational and implementational levels are more common and inform models at the algorithmic level.

Question 8

What are the basics of this early theory of decision-making: Expected Utility Theory?

Answer 8

Expected utility theory (1940s)
Predicts risk aversion for monetary gains.
It represents the usefulness or desirability of an outcome.
Calculate gains and losses.
Rational choices involve full information about the environment, preferences and calculating the best actions.
Driven by a goal such as wealth - More likely to take risks.
For example, the likelihood of an individual’s decision to take risks to increase already large wealth.

Question 9

What are the basics of this early theory of decision-making: Prospect Theory?

Answer 9

Prospect Theory (1979)

• Loss aversion, pain is more urgent than pleasure. Due to steeper value/curve for losses.
• Risk aversion, that people settle into habits.
• Predicts framing effects - whether an option is presented as a loss (negative) or a gain (positive).
• Framing effects are reversed for small probabilities.

Question 10

Main difference between prospect and utility theory

Answer 10

Utility theory is based on theory and rational, while prospect theory describes the actual behavior of individuals.

Question 11

Three basic tenants of the Prospect Theory:

Answer 11

1. Predicts loss aversion due to a steeper expected value curve for losses.
2. It predicts the framing effects
   **a concave expected value curve for gains a convex one for losses. **
3. Framing effects are reversed for small probabilities.

Question 12

Tenant of Prospect Theory
1. Predicts loss aversion due to a steeper expected value curve for losses.

Answer 12

Because the value function is steeper for losses, the psychological impact of a loss is greater than that of a gain of the same magnitude. This is why people exhibit loss aversion.

Question 13

Tenant of Prospect Theory
2. It predicts the framing effects
**a concave expected value curve for gains a convex one for losses. **

Answer 13

Framing Effects: The way choices are presented (or framed) can significantly affect decisions.

Explanation of Framing Effects
Concave for Gains: When options are framed as gains, people tend to be risk-averse.

• Scenario: Health Intervention Program
• Example: Imagine a public health official is presenting two programs to combat a disease outbreak.
• Program A (Gain Frame): “This program will save 200 lives out of 600.”
• Program B: “There is a one-third probability that all 600 people will be saved and a two-thirds probability that no one will be saved.”
• Outcome: People tend to prefer Program A because the certainty of saving 200 lives is framed as a gain, which feels more secure and positive.

Convex for Losses: When options are framed as losses, people tend to be risk-seeking. This is because the value function for losses is convex, leading to diminishing sensitivity to increases in losses.

• Scenario: Health Intervention Program
• Example: Now, imagine the same scenario but framed differently.
• Program C (Loss Frame): “This program will result in 400 deaths out of 600.”
• Program D: “There is a one-third probability that no one will die and a two-thirds probability that all 600 people will die.”
• Outcome: People tend to prefer Program D because the potential to avoid a total loss is framed as a better option, even though it involves more risk.

Question 14

Tenant of Prospect Theory
3. Framing effects are reversed for small probabilities.

Answer 14

Small Probability Gains: For low-probability gains, people tend to be risk-seeking. This is because the potential for a large gain, even with a low probability, is highly attractive. The value function for gains does not apply in the same way for very small probabilities.

Small Probability Losses: For low-probability losses, people tend to be risk-averse. They prefer to avoid a low-probability catastrophic loss, even if it means accepting a smaller certain loss.

Question 15

What is the framing effect? risk aversion = gain
risk seeking = loss

Answer 15

Framing effects: Decisions are influenced by how choices are presented. 

The framing effect occurs because the expected value curve is concave (arch-shaped) for gains and convex (crescent-shaped) for losses.

Example of Framing Effects
Gain Frame:
Option A: A sure gain of $50.
Option B: A 50% chance to gain $100 and a 50% chance to gain nothing.
People typically choose Option A due to risk aversion (concave value function for gains).

Loss Frame:
Option C: A sure loss of $50.
Option D: A 50% chance to lose $100 and a 50% chance to lose nothing.
People typically choose Option D due to risk-seeking behaviour (convex value function for losses).

Recent studies affirm individual and situational variability in preferences for uncertain outcomes.

Question 16

The ‘framing effect’ flips when the probabilities are small
Risk seeks = gain
Risk-averse = loss

Answer 16

Low probabilities (up to about 30%) are perceived as greater than they are, while mid-range and high probabilities are perceived as lower.

Example of Reversed Framing Effects
Small Probability Gain Frame:
Option E: A sure gain of $10.
Option F: A 1% chance to gain $1000 and a 99% chance to gain nothing.
People often choose Option F, seeking the small probability of a large gain.

Small Probability Loss Frame:
Option G: A sure loss of $10.
Option H: A 1% chance to lose $1000 and a 99% chance to lose nothing.
People often choose Option G, avoiding the small probability of a large loss.

Question 17

the expected value curve is concave (arch-shaped) for

Answer 17

gains

Question 18

the expected value curve is convex (crescent-shaped) for

Answer 18

losses

Question 19

Low probabilities are ___ in decision-making processes.

Answer 19

over-weighted

Question 20

higher probabilities are _____ in decision-making processes.

Answer 20

under-weighted

Question 21

Which of the following biases are postulated to be produced by the representativeness heuristic?

Answer 21

The conjunction fallacy, the gambler’s fallacy, and base rate neglect

Question 22

What is the endowment effect, predicted by Prospect Theory?

Answer 22

The endowment effect is the overvalue of current possessions.

People place extra value on goods they own compared to identical goods they do not earn. Therefore, people expect the pain of relinquishing a good to be greater than the pleasure of acquiring it.

• Challenges traditional economic presumptions.
• Highlights the impact of psychological factors on decision making.
  Prospect theory attributes this to loss aversion, where the mere ownership of an item creates a psychological attachment. Therefore, individuals are reluctant to trade it.

Question 23

Which of the following constitutes a display of confirmation bias?

Answer 23

Looking for confirming, rather than disconfirming, evidence for explanations or problem solutions that come to mind

Question 24

When the events connected by a hypothesis (for example, labelled a cause and effect) are rare.

Answer 24

the confirmation bias has been demonstrated to be adaptive

Question 25

Define Heuristics & Biases

Answer 25

Humans have limited cognitive resources that restrict their ability to process all available information/ consider every option when making decisions.

To manage these limitations, people use heuristics—mental shortcuts that simplify decision-making and reduce cognitive effort.

However, reliance on heuristics often leads to systematic biases. For instance, the anchoring heuristic can cause undue influence from the first piece of information encountered.

Question 26

What are the main heuristics

Answer 26

Heuristic: Representativeness

Positive test heuristic

Heuristic: Anchoring and adjustment

Question 27

Representativeness Heuristic
Define Term & Example

Answer 27

Representativeness Heuristic:

Definition: The representativeness heuristic relies on the rule that “A is representative of B to the extent that A resembles B.”

Example: In a scenario comparing the likelihood of Linda being a bank teller versus a feminist bank teller, people may incorrectly choose the second option due to the representativeness heuristic.

Question 28

Biases due to Representativeness

Answer 28

Conjunction Fallacy: Erroneously believing that specific combinations of events are more likely than the individual events themselves.

Gambler’s Fallacy: Expecting past events to influence the probability of future events.

Base Rate Neglect: Ignoring general information about the prevalence of an event when making specific judgments.

Question 29

Positive Test Heuristic
Define Term, Example and Adaptive?

Answer 29

Definition: Positive test heuristic involves asking questions that affirm a hypothesis under consideration.

Example: In the Wason Selection Task, individuals tend to confirm a hypothesis rather than disprove it.

Adaptive? No.
Research questions the adaptiveness of the positive test heuristic, emphasizing its limitations in complex real-world situations.

Question 30

Anchoring-and-Adjustment Heuristic
Definition, Example and Biases

Answer 30

*Definition: Individuals start with an initial value (anchor) and adjust their judgment based on additional information. *

Example: In experiments where participants were provided anchors, their final estimates were influenced by these initial values.

Biases:
**Anchoring bias **
is the tendency to rely too heavily on the first piece of information encountered (the “anchor”) when making subsequent judgments or decisions, even if the anchor is irrelevant or inaccurate.

Question 31

Main Limitations of the Heuristic and Biases Approach?

Answer 31

Not enough research to establish the conditions required to produce correct judgments.

Too simplistic - under some conditions, unable to explain why biases are reduced or disappear.

Gigerenzer’s traditional approach did not explain why heuristics enable bounded rationality (= ‘deviations’).

Does not answer: How do people achieve accuracy in most everyday decisions?

Question 32

Bounded Rationality

Answer 32

the idea that in decision-making

• the cognitive limitations of the mind
• reliance on heuristics
• the complexity of the environment
  AND
• amount of time available to make a decision

restrict the rationality of individuals,
lead to deviations from the optimal decision-making model proposed by classical economics.

Question 33

Dual systems perspective

Answer 33

In putting forward the dual systems view of decision-making, Kahneman proposes that the two systems are distinct in the brain, with System 2 largely contained in the frontal lobes, and having evolved later. System 2 is conscious, slow, intentional and controllable, whereas System 1 is the opposite – unconscious, fast, unintentional, and uncontrollable.

Question 34

System 1 and Heuristic and Biases Approach

Answer 34

Usage of Heuristics: System 1 frequently employs heuristics because they allow for quick decision-making with minimal cognitive effort.
Source of Biases: Since heuristics are simplified rules, they often lead to biases. For instance, the availability heuristic leads to overestimating the frequency of easily recalled events, and the representativeness heuristic can cause stereotyping.
Biases and System 1:

Automatic Biases: Many biases identified in the heuristic and biases model, such as confirmation bias, anchoring bias, and overconfidence, originate from the automatic and intuitive nature of System 1 thinking.

Question 35

System 2 and Heuristic and Biases Approach

Answer 35

System 2 as a Corrective Mechanism:

Monitoring and Correction: System 2 can monitor and override the automatic responses of System 1. When individuals have the time and cognitive resources to engage System 2, they can correct or mitigate the biases introduced by System 1.
Cognitive Load: Under cognitive load or time pressure, individuals are more likely to rely on System 1, leading to greater reliance on heuristics and higher susceptibility to biases.

Question 36

Dual Systems Perspective and Heuristic and Biases Approach

Answer 36

In summary, the Dual Systems perspective explains the cognitive mechanisms underlying the heuristic and biases model, illustrating how fast, automatic thinking (System 1) leads to the use of heuristics and the resulting biases, and how slow, deliberate thinking (System 2) can potentially correct these biases when conditions allow.

Question 37

Criticisms of Dual Systems Perspective

Answer 37

Criticisms
- Little to say about when exactly System 2 ‘takes over’. In the passage above, it is unclear what is meant by ‘when the going gets tough’.

• Brain imaging research overwhelmingly points to processing centres in different parts of the brain working in a way that is more integrated (i.e., connected) and iterative (i.e., back-and-forth).

Question 38

Why is research on confirmation bias often considered exempt from the limitations of the heuristics and biases approach?

Answer 38

Research on confirmation bias shows that the positive test heuristic that drives the bias produces accurate judgements when the cause and effects people are making judgments about rarely appear in the environment.

Question 39

The Heuristics and Biases approach has been criticised by proponents of a Fast-and-Frugal model of heuristics for

Answer 39

Not explaining when decision-making shortcuts produce accurate responses

Question 40

As a whole, what has research on Fast-and-Frugal heuristics discussed in the lectures shown?

Answer 40

Speed of decision-making does not need to be traded off against accuracy.

Question 41

The Take-the-Best heuristic is both fast and frugal in that it

Answer 41

Uses limited information (only a few cues) and relies on validities learned from experience.

Question 42

What are fast-and-frugal heuristics, and how are they different from earlier conceptions of heuristics?

Answer 42

Heuristics are fast and frugal in that they have simple building blocks:

*Searching, which is the process of looking up cues in order of importance for the specific environment

*Stopping, which occurs as soon as one cue allows

*Forming a judgement based on that critical cue

Heuristics can, thus, be thought of as the contents of an ‘adaptive cognitive toolbox’.

People are highly attuned to their environments, and can, thus, select cues and heuristics that are most appropriate in various environments.

Unlike earlier conceptions of heuristics, which often focused on more complex decision-making processes or relied on extensive computation, fast and frugal heuristics operate under the premise that simpler decision rules can be just as effective, if not more so, in achieving satisfactory outcomes. They are designed to be adaptive and efficient in real-world situations where time, cognitive resources, and information may be limited

Question 43

In particular, what is the “less can be more” principle?

Answer 43

Decision-making is a Less-Can-Be-More process, in that there is always a point in the decision-making process when doing more computation or considering more information becomes detrimental to making a good (i.e., more accurate) decision. Less-Can-Be-More is also referred to as ‘ecological rationality’.

Question 44

What is the “Take-the-Best” heuristic?

Answer 44

Used when deciding between two recognisable alternatives – say, when deciding between two rental properties to inspect, or two known routes for driving to work.

Take-the-Best has been suggested to be a heuristic that exploits redundant cues in various environments to produce judgements that are at least as accurate (and in some cases, more accurate) than strategies involving consideration of all cues.

Question 45

NOT a strength of Bayesian computational models of decision-making?

Answer 45

The models demonstrate the power of machine learning

Question 46

What are Bayesian models of decision-making, and how do they improve on the ‘fast-and-frugal’ approach?

Answer 46

Method of deriving rational answers to toy problems; e.g., correct answer to the taxicab problem

Alternative to frequentist statistics for data analysis

Method of deriving rational answers to more complex problems

Basis for approaching decision-making (and human perception and cognition more broadly) as a task that involves applying scientific common sense

Question 47

How dose Bayesian models of decision-makingimprove on the ‘fast-and-frugal’ approach?

Answer 47

Bayes’ rule is a formula that follows logically from probability theory, and it has provided a foundation for innovations even beyond decision-making research.

In its basic form, the rule specifies how to compute the probability of b given a from the probability of a given b, where a and b are values of something that can vary (a variable).

Bayesian modelling has shown that a stock-standard version of the Take-the-best heuristic is not applied by all people. The finding, more generally, demonstrates the power of Bayesian models of cognition to explain fine-grained judgment patterns.

Question 48

What is machine learning, and what are the ethical limitations around using it to guide decisions?

Answer 48

Machine learning focuses on enabling computers to perform tasks without explicit programming.

Ethical issues:
The data being used to “teach” the software systems is embedded with bias, and only serves to reinforce inequality. Eg black neighbourhoods being high risk

Bayesian models of cognition need to be distinguished from the application of Bayesian statistics in data analysis and artificial intelligence, of which machine learning is a type. It is critical to be aware of the ethical implications of using artificial intelligence algorithms that imitate human decisions with data shaped by the same systems that give rise to social inequality.

Question 49

What is metacognition, and what does it tell us about the relationship between confidence and accuracy in decisions?

Answer 49

Metacognition is the process of thinking about thinking or the intentional awareness and control of personal thought process. In other words “thinking about ones own mental thought process”
E.g a student must assess their comprehension for the exam

Metacognition is a third emerging approach to defining ways of explaining and improving decision-making. This lecture provided insight into the progression of findings on one issue relating to the monitoring aspect of metacognition: the extent to which confidence can be considered a cue to accuracy. The answer is that the relationship is positive across many studies. This positive relationship is evident even in research on the Dunning-Kruger effect, which investigates possible exceptions to the positive relationship.

Question 50

How might confirmation bias (defined by research on heuristics and biases) contribute to misdiagnosis, and how can confirmation bias be reduced?

Answer 50

Confirmation bias and misdiagnosis
- the confirmation bias is the tendency to test your hunches (or hypotheses) by asking questions that will yield an affirmirmative response if the hypothesis is true
- the bias arises from the application positive test heuristic: “When testing a hypothesis, as questions that will yield a yes response if the hypothesis under consideration is true
- In medical settings
o Occurs when a health professional attends to symptoms that are present without considering symptoms that are absent OR a health professional ignores evidence that disagrees with a leading diagnosis
o These patterns of decision making can result in misdiagnosis, overtreatment and unnecessary use of diagnostic tests

Question 51

How might Prospect Theory help to motivate health-related behaviour?

Answer 51

Preventative behaviours that preserve good health through potentially preventing disease - behaviours such as applying sunscreen and exercising - are considered unlikely to lead to undesirable/severe consequences, and are thus considered low risk (low in uncertainty)

Detection behaviours that can confirm potential disease, behaviours such as taking a mammogram and testing for diabetes are considered more likely to lead to undesirable outcomes (like finding out you have a disease (they are considered high risk.

Specifically, message framing theories predict that when a procedure is perceived as risky (e.g., cancer screening tests may cause a patient to find out that they have cancer), loss-framed messages will promote testing more strongly than gain-framed messages.

On the other hand, when a procedure is perceived as safe (e.g., sunscreen prevents sunburn and skin cancer), gain-framed messages are predicted to be more effective because people prefer sure prospects to risky prospects in the domain of gains.

Question 52

Conclusion of prospect theory and health messaging

Answer 52

• Despite large amounts of research on appropriate framing for messages depending on the kind of health behaviour they are aimed at
• There is no scientific consensus on the best frame (gain vs loss) for preventative and detection-oriented behaviours
• In light of ongoing debates, prospect theory has not become an overarching theoretical framework for health advertising
• Many detection-oriented behaviours are promoted in the gain frame

Question 53

How has the fast-and-frugal heuristics model shaped the way in which health-related information is presented to practitioners and the public?

Answer 53

• Widespread impact on information presentation
• Research by Hoffrage and Gigerenxer 1998 showed that the natural frequency format is more effective for communicating with doctors about the predictive value of diagnostic tests.

Gigerenzer 2007 wrote a more comprehensive guide for teaching and presenting healthcare-related statistics and we can see the influence of his work on how infographics relating to healthcare and all other topics are designed these days
- Green and Mehr 1997 developed as a decision aid for emergency room doctors at a Michigan hospital when allocating patients to a specialist heart or coronary unit as opposed to a regular bed
- Application of the tree by doctors resulted in fewer patients at risk of heart attack being wrongly sent to a regular bed
The application of the tree also reduced the load on the coronary unit, before the tree’s introduction doctors had been sending 90% of patients with any coronary symptoms directly to the coronary unit preferring to err on the side of caution

Question 54

How has the Bayesian approach improved our understanding of impulsive decision-making in people with addictions?

Answer 54

Used to clearly demonstrate that:

The degree to which an individual is reluctant to accumulate evidence prior to making a decision also known as reflection impulsivity is heightened in people who binge drink - particularly in the sense that they have difficulty thinking ahead

Banca et al 2018; 30 people who binge drink and 30 controls

The findings provide indirect evidence base for ads that support thinking ahead for people at risk of binge drinking

Question 55

Metacognition in the legal system: What is the post-identification feedback effect in eyewitness identification and what can we do about it?

Answer 55

After identifying Ronald Cotton from a live lineup (Jennifer Thomspon) asked Detective Mike Gauldin whether she got the right guy

He said we thought that might be the guy - it’s the same person you picked from the photos

This comment served to cement Jennifer’s certainty in the accuracy of her identification and contributed to the conviction of Ronald Cotton who served 11 years in prison for a crime he did not commit

Confirming post- identification feedback

Feedback that suggests that the witness made a correct identification

Inflates witnesses recollections of how confident they were at the time of the identification

Particularly harmful when identifications are false because confirming feedback produces confident but inaccurate eyewitness evidence against an innocent person