Lecture 17: Decision making and reasoning Flashcards
Review from last class: decision making
- Decision-making: When we make decisions or judgments, we use heuristics guided by the principles of what we expect.
- Psychological theory: Framing of information as well as emotions
can guide how we assess risk when we make choices (the words we use can affect our assessment of risk) - Prospect Theory
- Neuroscience: Activity in emotional areas in the brain (amygdala) are linked to framing effects and prospect theory predictions
- there is a key role of the emotional system in the mediating of some decision biases.
Loss Adversion
- Amygdala is important with emotion and particularly with processing salience or arousal and is often implicated in fear.
- Loss avoidance: the avoidance of a choice that could lead to loss (even if that choice is accompanied by equal or larger gains)
Research to see how amygdala might mediate loss adversion.
* People avoid gambles (choices) when they are equally likely to either lose a smaller amount $10 or win a larger amount $15
* Tested patients with bilateral lesions of the amygdala
* Impairments in processing fear despite normal cognition
* Lacked loss aversion on gambling task. They were able to respond to expected value and risk, but they had a dramatic reduction in loss aversion compared to healthy controls.
EVIDENCE: that the amygdala in the brain plays a key role in generating loss aversion which could be because it removes sort of the fear of poor outcome.
Neuroeconomics
- Studying how we make decisions, formalizing theories and linking it to the development of the brain
- Combination of economic theory, psychology and neuroscience that is trying to understand why people make the decisions that they do.
economic angle: understanding decision making or value based judgments.
neuroscience angle: how it relates to why humans develop or use certain parts of the brain.
psychology: develop and test theories of these brain behavior processes
Decision making and reasoning
- Reasoning guides decision making
- People make 35,000 decisions a day!
- Reasoning is a thought process that brings an individual to a conclusion
- A broad concept that is an umbrella to other cognitive domains
*Reasoning (high order cognitive domain) is when we have to use limited information from whatever we see in the world to draw a conclusion. - Understanding if we are logical (are we logical when we reason - we aren’t really)
* More like … when or how are we not logical
Inductive reasoning
- Making general conclusions from specific observations (making a generalization from observations). Making a hypothesis from data that you’ve collected through senses or perceptions.
* A detective enters a crime scene. They notice glass from a broken window; strewn books; spilled milk. They use these observations to make a conclusion about what happened - The conclusions can be false because they are only going off the observations. Require some sort of interpretation.
- A “probably but not definitely true”–type of reasoning
Inductive reasoning (continued)
- We also use inductive reasoning to make predictions about what will happen in our future based on observations of what happened in the past.
ex: * Claire bought ice cream from the same Dairy Queen five times
* Claire enjoyed it each time.
* Claire concludes that the next time she is at Dairy Queen, she will have quality ice cream that she will enjoy (broadly predicting what will happen next time based on her past.
* When we are unaware of inductive reasoning, it can become a heuristic. If we over generalize or use them too much then this can lead to a biased outcome and these can have some negative consequences.
Inductive reasoning
- But inductive reasoning is also the basis of much of human learning. Our knowledge is based on inferential guessing or inductive reasoning.
* ex: learning to make associations that are really important for your survival.
* Applying learned rules to new situations - Language learning
* inductive reasoning is central to word learning.
* Learning the meaning of balloon when you see “the purple balloon dog” and already know ‘purple’ and
‘dog’
Deductive reasoning
- Using general theories to reason or make predictions about specific observations, instances and information.
- My general belief is that “The Cog Dog loves Cognition”
- The Cog Dog is a dog
- I assume all dogs love cognition
Deductive vs inductive reasoning
- inductive reasoning is about making observation. So you are generalizing from observations to form theories. So you are reasoning from information.
- deductive reasoning is like the opposite, you start with a theory or a big idea, and the you make predictions and then observe with experiments. So you are reasoning towards information.
Logic and syllogisms
- Deductive reasoning: formal systems for generating statements that will be true if rules of the system are followed. We are logical if we follow these rules of reason without being influenced by other factors like content or prior knowledge. So logic is about formal systems for generating statements that will definitely be true if you follow those rules.
- Syllogisms: they are deductive reasoning problems that involve 2 premises and a conclusion. Each premise shares a term with the conclusion.
* Premises are presumed to be true
* Determine if the premise statements support the conclusion
based on the logical structure not content
All dogs are animals
All animals have four legs
Therefore, all dogs have four legs
* Major premise (general)
* Minor premise (specific)
* Conclusion (test)
Validity of syllogisms
- Validity: Is the conclusion true given the premises’ logical form?
- Valid = logical rules ≠ Truth = world knowledge content
- A valid structure (All A are B : All B are C: Therefore, all A are C)
Types of syllogism
some = at least one, possibly all.
Logical difficulty does shift with the use of these different premises in syllogisms. Particularly people have problems reasoning with the “some” statements and the “negative” statements
Problems arise! Atmosphere effect
- “some” statements are hard to reason with because they are quite ambiguous.
- People rate a conclusion as valid when the qualifying word (e.g., ‘all,’ ‘some’) in the premise match those in the conclusion
- Often we will take shortcuts when we are reasoning with some statements and we will kind of go by the mood of syllogism which is called atmosphere effect. The conclusion that “some of these are” feels right.
Problems arise! Negative statements
- Mental model theory
* People construct mental simulations of the world based on statements (e.g., syllogisms) to judge logic and validity.
* We create a description of the world or a mental model based on what we know is true to form these “principles of truth” - “Reasoning is more a simulation of the world fleshed out with all our
relevant knowledge than a formal manipulation of the logical skeletons
of sentences” - Can’t imagine negative statements. It is really hard to imagine the absence of something.
Omission bias
Thus, people tend to have more trouble reasoning with negative information.
* Biased thought that ”withholding is not as bad as doing”
* Inaction is harder to classify as wrong than action. If I don’t do something, I’m not as bad as if I do something bad even if the consequences are the same. This bias emerges because it is harder to classify or interpret inaction than action.
Which is more immoral?
1. A person who accidentally sets fire to a building
2. A person who sees a fire in a building but does not bother to report it.
- People tend to react more to strongly to harmful actions (1) than to harmful
inactions (2)
People with frontal lobe damage will have less moral dilemma.
The belief bias and syllogisms
- We tend to make inferences based on the premises of the syllogism and the conclusion - we bring in our prior knowledge and beliefs.
- If a syllogism’s conclusion is something that we think is true, then we are more likely to accept it as logical event if the premises don’t logically support it.
Both are invalid; but people are more likely to judge (1) as valid as compared to
(2) because it is hard to imagine students as millionaires (easier to believe that there are some irritable old people out there).
The belief bias and syllogisms
- People have problems reasoning with syllogisms in which logical validity
conflicts with truth. - The content of a syllogism can lead to errors due to a belief bias
- The tendency to think a syllogism is valid if the conclusions are believable.
More people are likely to endorse the 2nd syllogisms as valid
The belief bias and syllogisms
- The belief bias is more dominant for invalid syllogisms than valid ones.
- They are not willing to accept unbelievable valid syllogisms.
Wason’s task: Conditional reasoning
- If a card has a vowel on one side, then it has an even number on the
other side, which cards should you flip? - Conditional statement: If ‘vowel’ then ‘even’
- Many do not test this statement correctly
- Very few turn over card ‘E’ and ‘5’ to test if a vowel = even number and if
not even then not vowel ( if p then q and if not q then not p) - Confirmation bias: tendency to seek confirmatory evidence for a hypothesis
In lab, about 1/3 of people will turn over the E to see what is on the other side. We like to seek out evidence to confirm what we believe. We have a hard time trying to falsify things we believe.
Conditional reasoning and falsification
- The falsification principle: You need to look for situations that
would falsify a rule - General logical rule to solve: “ If P then Q ”.
- Choose the P card (is there a not-Q on the back?) and the not-Q
card (is there a P on the back?). Eliminate false statements- you need to falsify the claim.
Familiarity effects
- People are much better at the Wason’s Task when given a version of this task with real world content.
- If a person is drinking a beer (P), then the person is over 21 years old (Q)
- Cards have age on one side and beverage on the other side
- Which card(s) do you need to flip to verify this statement?
about 75% can solve this task
Anchoring & adjustment heuristic
- People’s judgments of the magnitude of something is biased (i.e., adjusted) by some initial value they are exposed (i.e., the anchor)
- Which of the following produces a larger number?
- Most say the first sequence because it has a higher anchor
We will be biased by the first thing and will anchor it based on that (compare to the starting value).
Anchoring & adjustment heuristic
- Participants given a random number between 0 and 100
- “Is this number higher or lower than the percentage of
African nations in the United Nations?” - Estimate the actual percentage
- “Is this number higher or lower than the percentage of
- Those who were given a HIGH random number gave greater
percent estimates than those given a LOW random number - Even when the people knew that these numbers that they were given at the start were random, it still produced an effect.
- We even anchor estimates to unrelated information
Predicting risk and optimism
- Rate the likelihood a positive, negative, neutral events will happen to that person in the next month
- After a month, provide ratings of whether the events occurred
- People overestimate the number of positive predicted events and underestimate the likelihood of negative events.
- we expect to live longer than the other.
- This optimism bias was not present in depression
* Presentation differs with degree of depression- People with mild depression showed no optimism bias
- severe depression = pessimistic bias.
