Week 10 Flashcards
Objectives:
Explain, with examples, the role of heuristics in common errors of judgment and decision-making.
Explain, with examples, prospect theory, loss aversion and the sunk cost effect—what are their implications for decision-making in everyday life?
1 Tversky and Kahneman proposed three heuristics—availability, representativeness, and anchoring and adjustment. Subsequent work has identified many more. Heuristics that underlie judgment are called “judgment heuristics”.
What is the bounded rationality framework?
Human beings try to make rational decisions (such as weighing the costs and benefits of a choice) but our cognitive limitations prevent us from being fully rational.
What is the bounded rationality framework?
Human beings try to make rational decisions (such as weighing the costs and benefits of a choice) but our cognitive limitations prevent us from being fully rational.
Bazerman and Moore (2013) outline the following six steps that you should take to make a rational decision:
(1) define the problem (i.e., selecting the right graduate program),
(2) identify the criteria necessary to judge the multiple options (location, prestige, faculty, etc.).
(3) weight the criteria (rank them in terms of importance to you),
(4) generate alternatives (the schools that admitted you),
(5) rate each alternative on each criterion (rate each school on each criteria that you identified, and
(6) compute the optimal decision.
Acting rationally would require that you follow these six steps in a fully rational manner.
How are biases created?
By the tendency to short-circuit a rational decision process by relying on a number of simplifying strategies, or rules of thumb, known as heuristics.
What are heuristics?
Strategies that allow us to cope with the complex environment surrounding our decisions. Unfortunately, they also lead to systematic and predictable biases.
One critical path to fixing our biases is provided in Stanovich and West’s (2000) distinction between System 1 and System 2 decision making.
System 1
System 2
System 1 processing is our intuitive system, which is typically fast, automatic, effortless, implicit, and emotional.
System 2 refers to decision making that is slower, conscious, effortful, explicit, and logical. The six logical steps of decision making outlined earlier describe a System 2 process.
The role of heuristics
When we are making decisions, any initial anchor that we face is likely to influence our judgments, even if the anchor is arbitrary. That is, we insufficiently adjust our judgments away from the anchor.
The role of heuristics
When we are making decisions, any initial anchor that we face is likely to influence our judgments, even if the anchor is arbitrary. That is, we insufficiently adjust our judgments away from the anchor.
What is anchoring
The bias to be affected by an initial anchor, even if the anchor is arbitrary, and to insufficiently adjust our judgments away from that anchor.
Heuristics
Cognitive (or thinking) strategies that simplify decision making by using mental short-cuts.
Judgement
Involves deciding on the likelihood of various events using incomplete information. For example, you might use information about your previous examination performance to work out the probability you will succeed in your next examination. What matters in judgement is accuracy.
Decision making
- Involves selecting one option from several possibilities. You probably had to decide which university to attend, which courses to study and so on.
- The factors involved in decision making depend on the importance of the decision. For example, the processes involved in deciding which career path to follow are much more complex and time-consuming than those involved in deciding whether to drink Coca-Cola or Pepsi-Cola!
Judgement often forms an important initial part of the decision-making process.
For example, someone deciding which car to buy might make judgements about how much various cars would cost to run, how reliable they would be and how much they would enjoy owning each one.
Base rate information
The relative frequency of an event within a given population.
According to Koehler (1996), the “relative frequency with which an event occurs or an attribute is present in the population” is called the base rate
Base rate information
The relative frequency of an event within a given population.
According to Bayes’ theorem, people making judgements should take account of base-rate information (the relative frequency with which an event occurs within a population).
Thus, many people use base-rate information when they understand the underlying causal factors.
In sum, we often use base-rate information in everyday life when we possess relevant causal knowledge. We also use such information when it is advantageous to us but ignore it when it is disadvantageous to us.
Heuristics
are “strategies that ignore part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods”.
“Heuristics primarily serve the purpose of reducing the effort associated with a task.
a) They are ‘rules of thumb’ that allow us to make quick decisions
b) They allow us to cope with the complex environment surrounding our decision
c) They are not always reliable
Representativeness heuristic
Our liking for heuristics can lead us to ignore base-rate information. More specifically, we use the
:which involves deciding an object or person belongs to a given category because it/he/she appears typical or representative of that category. Thus, for example, Jack’s description sounds like that of a typical engineer.
When people judge the probability that an object or event (A) belongs to a class or process (B), they will often apply the representativeness heuristic
The conjunction fallacy
The mistaken belief that the conjunction or combination of two events (A and B) is more likely than one event (A or B) on its own.
Someone that goes to protests is more likely to be two things than just one. A feminist and a bank teller.
Availability heuristic
The frequencies of events can be estimated on the basis of how easy or hard it is subjectively to retrieve them from long-term memory.
Causes of death that attract much publicity (e.g., murder) were judged more likely than those that do not (e.g., suicide) even when the opposite was the case. These findings suggest people use the availability heuristic.
Doctor used availability heuristic because he was overly influenced by the numerous recent cases of viral pneumonia, which made that disease spring to mind, when really is was a reaction to asprin.
Pachur argued that there are three ways of explaining people’s judged probabilities or frequencies of various causes of death.
- First, people may use an availability heuristic based on their own direct experiences.
- They may use an availability heuristic based on media coverage of causes of death as well as their own experience (availability by total experience).
- They may use the affect heuristic , which they defined as follows: “Gauge your feeling of dread that Risk A and Risk B, respectively, evoke and infer that risk to be more prevalent in the population for which the dread is higher”
He also found that based on recall of direct experiences was the best predictor of the judged frequencies of different causes of death. Judged risks were also predicted by the affect heuristic. Availability based on media coverage was the least successful predictor.
The above findings occurred because the participants used deliberate thought to override the availability heuristic. When participants decided which surname was more common under cognitive load, they used the availability heuristic and so the famous name was mistakenly selected 80% of the time.
Kahneman and Tversky’s approach is more applicable to less intelligent individuals than to more intelligent ones. In fact, intelligence or cognitive ability is almost unrelated to performance on most judgement tasks
Affect heuristic
Using one’s emotional responses to influence rapid judgements or decisions.
There are several limitations with the original heuristics-and-biases approach.
- The heuristics identified by Kahneman and Tversky are vaguely defined. “One-word labels like ‘representativeness’ are theory surrogates [substitutes] that fail to place any testable constraints on the cognitive decision process.”
- theorising based on the heuristics-and-biases approach has been limited. “What is disillusioning and disappointing . . . is how little precision, refinement, and progress has been obtained at the theoretical level.”
- Failed to indicate the precise conditions eliciting the various heuristics or the relationships among different heuristics.
It is sometimes unfair to conclude people’s judgements are biased and error-prone. For example, most people judge skin cancer to be a more common cause of death than cancer of the mouth and throat, whereas the opposite is actually the case. People make this “error” simply because skin cancer has attracted considerable media attention in recent years. More generally, the heuristics-and-biases approach focuses on biased processing, but the problem is often with the quality of the available information.
- Much research is detached from the realities of everyday life. Emotional and motivational factors often influence our judgements in the real world but were rarely studied in the laboratory until fairly recently (see Chapter 15). For example, the estimated probability of future terrorist attacks was higher in fearful individuals than those who were sad or angry.
Tversky and Koehler put forward their support theory which posits:
An event appears more or less likely depending on how it sounds.
Eg. probability you will die on your next summer holiday is extremely low. However, it might seem more likely if you were asked, “What is the probability you will die on your next summer holiday from a disease, a car accident, a plane crash, or from any other cause?” Why is the subjective probability of death on holiday greater in the second case? According to support theory, more explicit event descriptions have greater subjective probability for two main reasons:
1 An explicit description often draws attention to aspects of the event less obvious in the non-explicit description.
2.Memory limitations may prevent people remembering all the relevant information if it is not supplied.
Although: An explicit description can reduce subjective probability if it leads us to focus on low-probability causes.
Providing an explicit description can reduce subjective probability by making it more effortful to comprehend an event.
Limitations to support theory:
- The reason as to why an explicit description generally increases an event’s subjective probability are not clear.
- Explicit descriptions can reduce subjective probability if they lead individuals to focus on low-probability causes.
- Explicit descriptions can also reduce subjective probability if they are hard to understand
- The theory is oversimplified. It assumes the perceived support for a given hypothesis provided by relevant evidence is independent of the rival hypothesis or hypotheses. In fact, however, people often compare hypotheses and so this independence assumption is incorrect.
Fast-and-frugal heuristics
Involving rapid processing of relatively little information.
We possess an “adaptive toolbox” consisting of several such heuristics. It is also assumed these heuristics are often surprisingly accurate.
Take the best, ignore the rest strategy has three components:
1 search rule : search cues (e.g., name recognition, cathedral) in order of validity;
- stopping rule : stop after finding a discriminatory cue (i.e., the cue applies to only one of the options);
- decision rule : choose outcome.
Recognition heuristic
Using the knowledge that only one out of two objects is recognised as the basis for making a judgement.
The most researched example of the take-the-best strategy is the recognition heuristic
People will ignore
How do people decide which heuristic to use on judgement tasks?
There is a two-step process.
First, the nature of the task and individual memory limit the number of available heuristics.
Second, people select one of them based on the likely outcome of using it and its processing demands.
Hiatus heuristic
The rule of thumb that only customers who have purchased goods fairly recently remain active customers.
Simple heuristics
Take the best strategy.
Information redundancy
– redundancy is high when different cues provide similar information but low when cues provide different information. They argued that simple heuristics (e.g., the take-the-best strategy) are more effective in conditions of high than low redundancy. In crude terms, simple strategies work best (and are more likely to be used) when environmental information is simple.
Natural sampling is
The process of encountering instances in a population sequentially.
evolutionary history makes it easy for us to work out the frequencies of different kinds of events. In contrast, we are ill-equipped to deal with fractions and percentages, which helps to explain why many people perform so poorly on judgement problems involving base rates.
Judgement performance is often much better when?
Problems are presented in frequencies rather than probabilities or percentages
The percentage of participants showing the conjunction fallacy (arguing she was more likely to be a feminist bank teller than a bank teller) dropped by two-thirds
Two strengths of the natural frequency hypothesis.
- The use of natural or objective sampling could enhance the accuracy of many of our judgements.
- judgements based on frequency information are often superior to those based on probability information.
Dual-process theory:
Individuals do sometimes use complex cognitive processes. Such models have also been applied to performance on reasoning problems.
According to Kahneman (2003, p. 698), probability judgements depend on processing within two systems:
System 1 : “The operations of System 1 are typically fast, automatic, effortless, implicit (not open to introspection) and often emotionally charged; they are also difficult to control or modify.”
System 2 : “The operations of System 2 are slower, serial [one at a time], effortful, more likely to be consciously monitored and deliberately controlled; they are relatively flexible and potentially rule-governed.”
How are these two systems related?
System 1 rapidly generates intuitive answers to judgement problems (e.g., based on the representativeness heuristic). These answers are then monitored or evaluated by
System 2, which may correct them. Thus, judgement involves serial processing starting with System 1 and sometimes being followed by System 2.
(Linda problem took 40% longer to complete.
Dual process theory and cognitive load:
According to dual-process theory, cognitive load should reduce System 2 processing and so lead to answers making less use of base-rate information than answers produced without cognitive load.
What did Chun and Kruglanski (2006) find regarding the dual process?
Base-rate information The relative frequency of an event within a given population.
Cognitive load led to increased use of the information presented briefly. This was so regardless of whether this information referred to base rate or personality.
Thus, usage of System 1 and System 2 processing depends more on how information is presented (e.g., briefly vs. lengthily) than on its content (i.e., base-rate vs. personality description).
Which process is more effortful?
How are these (dual systems) two systems related? System 1 rapidly generates intuitive answers to judgement problems (e.g., based on the representativeness heuristic). These answers are then monitored or evaluated by System 2, which may correct them. Thus, judgement involves serial processing starting with System 1 and sometimes being followed by System 2.
System 2 processing is more demanding and effortful than System 1 processing. The notion that people’s judgements are typically determined by System 1 rather than System 2 accords with most findings.
Similar two process theories have proved reasonably successful in accounting for decision making and reasoning
Decision making under risk:
(At one time) People behave rationally and select the best option.
Decision making under risk:
(At one time) People behave rationally and select the best option.
