Week 12: Decision-Making Flashcards
Enlightenment (18th and 19th century) Views on Judgment and Decision Making: the rational man
- Enlightenment thinkers viewed humans as making rational decisions
- In legal contexts: weighing up whether a defendant is guilty should be compared against what a “rational man” would do in the circumstances
Current Thinking on decision making
- We now know there are many ways in which humans make poor decisions or behave differently from a rational expected outcome
- Humans rely often rely on heuristics (Less time and resources consumed)
- Humans subject to biases due to Systematic errors in our judgments or evaluations
– we are extremely bad at assigning probability to events!
Herbert Simon on decision making (bound rationality and satisficing)
-Bounded rationality: Humans reason and choose rationally, but only within the constraints imposed by their limited search and computational capacities.
-Satisficing: “[U]sing experience to construct an expectation of how good a solution we might reasonably achieve, and halting search as soon as a solution is reached that meets the expectation” (Simon, 1990)
Two major findings from Meehl
- Clinical prediction (e.g., predictions by clinicians) performs very poorly relative to statistical prediction (e.g., regression models).
- Clinical prediction overweights case characteristics and underweights base rates.
Availability Heuristic
(Tversky & Kahneman, 1973)
- Events that come to mind more easily are judged as being more probable than events that are less easily recalled
- The availability heuristic can lead to some very misleading consequences when we estimate probability eg Certain rare events that get a lot of media attention – these often come to mind when we estimate risk of danger
-availability can lead to an illusory correlation
tests in the experiments of Tversky and Kahneman: availability heuristic
Subjects studied lists of ordinary names and celebrity names. They studied both male and female names – the proportions of each were manipulated across the ordinary and celebrity categories but the underlying proportion of male and female names was 50/50
* During the memory test, subjects had to judge how frequent the male or female names were
* Subjects gave higher frequency estimates to whichever gender had the most celebrity names
* E.g., if there were more celebrity male names, but less ordinary male names, subjects estimated that there were more male names
Example of availability of heuristic leading to misleading consequences
- Deaths due to vaccinations: highly publicized, yet extremely rare
- Deaths from assault weapons: attacks using assault weapons are quite rare – handgun violence is considerably more frequent
- Deaths from airplane crashes: deaths from car crashes are much more frequent
Why do we use the availability heuristic
- Because we often do not know the true proportions or probabilities!
- Instead, we approximate these quantities by retrieving examples from memory
As soon as we use our memories to assign judgments or probabilities, we are subject to memory limitations
The Representativeness Heuristic(Tversky & Kahneman, 1974)
We make judgments on the basis of resemblance
-how much does an item resemble the stereotype of a catagory
Base-rate neglect
-where we ignore base rates (the percentage of a population that demonstrates a certain characteristic) when making assessments, and use other information to make our decision (e.g. representativeness).
-It’s not as if we can’t use base rates but we ignore it even when there is a description given, even if there is no information in that description
* This applies even if there are payoffs given for the correct answer
Why is representativeness heuristic:irrational
violation of the conjunction rule of probability
* The probability of two events together (A & B) can never be higher than the probabilities of the individual events (A or B).
-but due to description, we are more likely to choose A & B
Why do we use the representativeness heuristic
-we’re bad at estimating probability or correctly weighing prior probabilities with new information
-Tversky and Kahneman argue that we substitute for that with a simpler cognitive operation: resemblance
The Anchoring Heuristic
- When having to estimate a quantity, we always do it with an intuitive reference to something else
- That reference point is called the anchoreven random numbers can serve as anchors
Experiment on anchoring heuristic even random numbers can serve as anchors
- In one study, subjects were asked to estimate the proportion of African nations in the UN
- They were given a random number from a spinning wheel. What the subjects did not know is that the wheel only returned 10 or 65
- 10 group: their median estimates of African nations was 25
- 65 group: their median estimates of African nations was 45
- Even payoffs for correct responses did not alter the effect
Why do we use these random anchors
- Again, we don’t know the true frequencies or probabilities, and we need a reference point to make our decisions!
- Possibility that the number remains in memory due to its recency
