How we know what isn’t so – cognitive factors in false beliefs

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How we know what isn’t so – cognitive factors in false beliefs Dr. Jeff Saunders Dept of Psychology Hong Kong University

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How we know what isn’t so – cognitive factors in false beliefs. Dr. Jeff Saunders Dept of Psychology Hong Kong University. Topic: cognitive factors in false beliefs How we acquire false beliefs? What cognitive tendencies lead us acquire mistaken beliefs about the world? - PowerPoint PPT Presentation

Transcript of How we know what isn’t so – cognitive factors in false beliefs

Page 1: How we know what isn’t so – cognitive factors in false beliefs

How we know what isn’t so – cognitive factors in false beliefs

Dr. Jeff Saunders

Dept of Psychology

Hong Kong University

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False beliefs

Topic: cognitive factors in false beliefs How we acquire false beliefs?

What cognitive tendencies lead us acquire mistaken beliefs about the world?

Why do false beliefs persist? What tendencies inhibit us from learning from

experience and correcting false beliefs

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Demo: try to outwit the professor in a card guessing game

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Card game strategy?

‘Strategy’: choices were entirely random! But might have perceived that that there

was some causal strategy behind choices No way that opponent could have done

better or worse than chance But might have perceived that there was

some strategy that would have increased the likelihood of winning

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Seeing structure in randomness

One factor in acquiring false beliefs: tendency to see structure in randomness

We are very good at seeing meaningful patterns in the world

Useful and impressive ability! But so pervasive and automatic... can

sometimes lead us astray

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Clustering illusion

Distribution of bombs in London during WWII Was Regent’s Park targeted? No, just random

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Clustering illusion

These are randomly generated points Our minds readily see structure in random

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Home remedy: radishes!

Your friend’s remedy for common cold: eat large amounts of radishes

One day when you are really sick, the friend brings you a bunch of radishes to eat

You think: oh well, might as well try it Next day: you are feeling a lot better! Wow, do radishes really work? Or … could this just be coincidence?

(sounds unlikely to you)

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Health varies over time, semi-randomly, and most illnesses get better on their own

Seek treatment when health at low points Likely to get better regardless of treatment Misinterpretation of spontaneous recovery

could lead to false beliefs about remedies

Spontaneous recovery

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Summary - misperceived causation

We are very good at seeing patterns in the world and generating causal hypotheses

But this tendency can lead us to mistakenly see causal relations in randomness

Clustering illusion Misinterpretation of streaks or clusters that

occur naturally by chance Regression fallacy

Misinterpretation of regression to the mean

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Why do erroneous beliefs persist?

Suppose we have an false belief Due to clustering, regression, coincidence ...

In principle, exposure to counterevidence might allow one to correct the error

However, some cognitive factors interfere with correction of false beliefs…

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Neglect missing information…

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Example: selection criteria

A manager at a company has unusual method for choosing who to hire

Top 8 candidates compete in chess tournament, winner gets the job

Manager: “Everyone I’ve hired with this method has been excellent!”

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Example: selection criteria

Hiring method: chess tournament If previous employees performed well –

does that mean that hiring method is good? Or are we missing information?

Manager: “Everyone I’ve hired with this method has been excellent!”

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Example: selection criteria

Problem: missing data about how rejected candidates would have performed if hired

Only get feedback about the performance of candidates that were hired

If strong candidate pool, even flawed system would select good performers

Some rejected candidates might have been even better, but no way of knowing

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Home remedy: radishes! (again)

Your friend convinced you that radishes are a good treatment for colds, which is false

Will you learn from experience that radishes do not really help?

Problem: missing information If you belief in treatment, then every time

you are sick you will eat radishes Never get to see how quickly you would

recover without radishes

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Confirmatory evidence more noticeable…

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What evidence is noticed?

Example: belief that your roommate never remembers to wash their dishes

Lots of relevant evidence – every meal at home, either does or does not wash dishes

But which cases will be noticed?

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“Roommate never washes dishes”

Monday Tues

Weds Friday

Sunday

Thurs

Again??!I need a new roommate!

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What evidence is noticed?

Example: belief that your roommate never remembers to wash their dishes

Pos / neg evidence not equally noticeable Salient evidence would only reinforce belief

Unpleasant event, highly salient!

Going smoothly is non-event, not salient

Reinforce belief(even if rare)

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Example: prophecy

Using my psychic powers, I predict: On the first day of Lunar New Year in 2013, … there will be a major earthquake in China

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Example: prophecy

Prophesy: On the first day of Lunar New Year in 2013, major earthquake in China

Specific, falsifiable prediction But - what outcome would you notice?

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Prophesy: On the first day of Lunar New Year in 2013, major earthquake in China

Example: prophecy

WOW! He really is psychic!

Non-event, unlikelyto remember prophesy

Earthquake!New Year

No earthquakeNew Year

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Prophesy: On the first day of Lunar New Year in 2013, major earthquake in China

Example: prophecy

WOW! He really is psychic!

Earthquake!New Year

No earthquakeNew Year

Noticeable outcome would confirm psychic powers, not disconfirm

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http://xkcd.com/628/

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Bias in seeking information…

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Exercise: rule discovery

Goal: to figure out an unknown rule for sequences of three numbers

Some sequences of numbers satisfy the rule, some sequences do not

Here is one sequence of numbers that satisfied the rule: 2-4-6

Now you can suggest numbers for testing I will tell you “yes” or “no”

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Exercise: rule discovery

Demo: test cases to discover rule Initial example chosen so that you would

likely have some guess about the rule Tendency: test additional examples that

would also satisfy rule Problem: did not get opportunity to learn

that your guess was wrong Restricted test cases could only reinforce

mistaken belief about rule

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Application: medical diagnosis

How might confirmation bias lead to misdiagnosis by doctors?

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Example: test for extroversion

Goal: scale for measuring extroversion Items are self-reflective statements

“I often feel that …” “I generally do not …” Each item is rated on scale agree/disagree

1 – ‘strongly agree’ 2 – ‘agree’ 3 – ‘neither agree not disagree’ 4 – ‘disagree’ 5 – ‘strongly disagree’

Exercise: everyone write down a possible item for an extroversion scale

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Example: test for extroversion

In principle, items could test for either presence or absence of extroversion

Presence: “I am often the life of the party” Extroverts would “agree”

Absence: “I often keep to myself at parties” Extroverts would “disagree”

In your sample items, would extroverts be expected to agree or disagree?

Expected result: mostly “agree” items

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Seeking confirmation

Extroversion test example: tended to seek information that confirms not disconfirms Look for presence of a trait not absence Look for +extroversion not -introversion

If asked to make a test for introversion, would have chosen different statements

… even though these are assumed to be opposites along the same continuum

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Wason selection task

Hypothesis: “Cards with an odd number on one side have a circle on the other side”

Which cards need to be flipped to evaluate this hypothesis?

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Wason selection task

To evaluate hypothesis “if odd, then circle” Typical answer: (a) and (c)

Correct answer: (a) and (d)

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Wason selection task

To evaluate hypothesis “if odd, then circle”

Does not matter

If odd, supports hypothesis

If even, does not refute!

If odd, refuteshypothesis

If not circle, would refute hypothesis

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Wason selection task

To evaluate hypothesis “if odd, then circle”

Does not matter

If odd, refuteshypothesis

If not circle, would refute hypothesis

Could only confirm, never refute

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Wason selection task

To evaluate hypothesis “if odd, then circle”

Obviously irrelevant

Incorrectly treated as strong evidence

Relevant but neglected

Obviously relevant

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Wason selection task

Hypothesis: “If drinking beer, then over 18” Which people need to be checked? Logically, exactly same as previous, but

people tend to get this version correct “Permission” schema seems to help

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Wason selection task

Hypothesis: “If odd, then circle” Logically, need to check: odd, square But typically drawn to check circle card,

which could confirm but never disconfirm Confirmation bias in seeking information

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Summary - Confirmation bias

When evaluating a belief, we tend to seek and focus on confirmatory information

As a result, less likely to be exposed to evidence that might refute a false belief

Example demonstrations: Rule discovery exercise Look for stereotypical extroverted traits Wason selection task

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Expectations influence interpretation of evidence…

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Example: knowledge -> perception

By R. C. JamesOnce you know what it is, looks different!

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Bias due to expectations

Bias due to expectations can allow us to interpret highly ambiguous information

Perceptual example: experience allows us to see Dalmatian from degraded image

Adaptive use of knowledge and experience Is there a downside to this? Potential problem: re-enforce false beliefs

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Example: Referees’ judgments

Referees in sports often have to interpret ambiguous information to evaluate penalties

Susceptible to bias from expectations

High tackle or not?

Depends: are you an All-Blacks fan??

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Example: Referees’ judgments

Frank & Gilovich (1988) –effect of black uniforms on referee judgments

Referees evaluated possible penalties from videos

Identical situations except varied uniform color

Finding: more penalties for players wearing black

Explanation: stereotype of black as “bad guy”

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Lack of source memory…

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Trivia quiz

Answer trivia quiz

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Trivia quiz

Compute the number of “true” responses for even numbered statements

Actual: equal true/false Even numbered statements were repeated

from previous trivia quiz (if you took it) Prediction: more “true” for statements that

were repeated

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Illusion of truth effect

False True0.3

0.4

0.5

0.6

0.7

test1

test2Pe

rce

nt j

udg

ed

“tru

e”

Data from my HKU class:

For identical statements, more “true” judgments on second test

Change due to just one prior exposure

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Trivia quiz

Why might there be a bias toward “true”? Repeated statements were more familiar General bias: familiar -> perceived true “Validity effect” or “Illusion of truth effect”

Hasher, Goldstein, & Toppino (1977)

Example of a failure of source memory

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Source memory

Take some fact that you know is true: “The largest ocean in the world is the

Pacific Ocean” How do you know this is true? Can you answer: when and where did you

learn this fact? You know that this fact is true, but you don’t

remember the source of knowledge

Hard!

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Source memory

Human memory is very good at recognition … but memory is not as good for source We know many things… .. but not necessarily how we know

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Source memory

Real life example where poor source memory might lead to persistent false beliefs?

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Urban myths

Lack of source memory can explain persistence of “urban myths”

Suppose we have heard a myth many times Hard to remember whether or not we heard

from a reliable source (Also, we don’t tend to question how we know something – we just do)

So if myth is familiar, tend to believe it Then we might repeat the myth to others,

increasing familiarity for them, and so on ...

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Home remedy: radishes!

I’ve discussed a false remedy: radishes Right now, you remember that this is just a

silly example for illustration But years from now… … may only remember hearing something

about radishes curing the cold Sorry for planting a future false belief!

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Summary – persistence of false beliefs

Tend to seek confirmatory evidence Neglect missing information Confirmatory evidence more noticeable Biased interpretation of evidence Lack of source memory Effect of these factors: can be very hard to

change a false belief!

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Avoiding bias?

Try to consider possibility of coincidence We tend to seek causal interpretations, and

neglect the possibility of coincidence Helpful to keep this in mind, and recognize

some specific situations eg. regression to mean

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Avoiding bias?

Be aware of missing information Information required to evaluate a belief is

often unavailable or unnoticeable How well would rejected applicants have performed? If roommate does reliably washes dishes, would I

notice?

Would the condition have improved even without treatment?

Noticing these situations can cue you to be skeptical about beliefs

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Avoiding bias?

Be aware of limited source memory We tend to perceive familiar as true Try to reinforce good information more than

bad information

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Avoiding bias?

Strategy: study science! Thinking like a scientist can help overcome

some of these biases Idea of testing falsifiable predictions Appreciation of randomness and statistics

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Thanks for your attention

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