Decision making

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Decision making

• Decision making is an important area within
  cognitive psychology, because of the applied
  interest everyone would like to make better
  decisions, including armies, corporations, and
  individuals.
• So, how is the science doing? Do we have a good
  understanding of human decision making? Not
  really

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The basic problem in decision making

• The basic problem is that DM involves choice
  among alternatives. This is only possible if
• You know what the alternatives are
• You know what value each has
• Those values are expressed in a form which
  allows comparison

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The problems for science

• The problems for scientific study of decision
  making primarily have to do with value. As in,
  how can we measure the value of any outcome (any
  choice)?
• Two basic approaches
• Quantitative (expected value models)
• Qualitative (expected utility models)

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Expected value models

• These models originally advanced by economists.
• Basic idea value of an outcome is product of
  value and probability.
• E.g., a one-tenth chance of winning 200 is worth
  .10 200 20

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Expected utility models

• Problem humans do not make their choices on the
  basis of expected value.
• Solution Expected utility essentially, how
  much is it worth to you?
• Problem theres no way to specify this in
  advance. Its subjective.

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Some more recent alternative views

• Some psychologists have argued that we dont, in
  fact, make many decisions. Rather, they say,
  humans behaviour is automatic (e.g., Bargh
  Chartrand, 1999), or rule-guided (e.g.,
  Andersons production rule system in his ACT
  model).
• Loewenstein (2001) summarized arguments against
  the idea that humans make decisions.

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Problems with decision making theory

• Loewenstein (2001)
• Decision making would require too much capacity.
  Few decisions result from analysis and comparison
  of options.
• Few alternatives in everyday life can be
  analyzed in terms of attributes useful in
  decision making.
• Computers are good at computing. Humans are good
  at pattern-matching, categorizing.

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Problems with decision making theory

• Loewenstein (2001)
• Why is context so important? E.g., choice between
  2 gambles affected by whether decision was said
  to involve a gamble or insurance (note buying
  insurance is a gamble) (Hershey et al. 1982).
• Why is there so much intra-individual variation
  (if decision-making is algorithmic)?

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Problems with decision making theory

• Loewenstein (2001)
• Decision making anomalies people prefer
  sequences of outcomes that improve over time. But
  expected utility tells us that delayed rewards
  are discounted.
• Do we know what we want? Ariely et al. (2001)

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Decision making - definition
Decision making occurs when you have several
alternatives and you choose among them.   There
are two characteristics of good decision
making   1. You make the best (most valuable)
choice. 2. You are consistent in the choice you
make in a given situation.
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Decision making how well do we do it?
The best choice   There are two reasons humans
do not always make the best choice A. We don't
always pick the outcome with the highest
value. B. We don't always evaluate all possible
outcomes before choosing. 
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Picking the outcome with the highest value
Economists offer several schemes for measuring
value. The most famous is the theory of expected
value. E.V. outcome measured in dollars X
probability   Thus a 1/10th chance of winning
200 is worth 1/10 X 200 20
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The problem with expected value theory
Which would you prefer - a 1/10th chance of
winning 100, or a 9/10th chance of winning
8?   A. 1/10th X 100 10 B. 9/10th X 8
7.20 But suppose you are hungry - really
hungry. Then, higher probability may be more
attractive, so you choose B.
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Expected utility theory
Expected utility theory argues that we choose
utility. Utility what it is worth to you right
now.  2 differences between objective and
subjective value of money  1. Subjective value
is not a linear function of objective value. (1
million 1000 X 1000 1 billion 1000 X 1
million.)
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2 differences between objective subjective value
2. Subjective value is not symmetric for gains
and losses (losses are more important).   Kahneman
Tversky (1984)   A. You flip a coin. Heads -
win 20. Tails - pay 20. B. You do not flip a
coin. You win nothing.   Most people chose B.
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How can we have a science of value?
Expected value theory is informative but doesn't
work. Expected utility theory works but is not
informative. Subjective value is impossible to
predict. So the first problem with making the
best choice is that we cant objectively measure
value. At least, not as individuals but there
are markets
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The second problem with making the best choice

• Humans often do not consider all possible
  outcomes because doing so would take too long.
•  
• An HR person at a big company hires a new
  employee. She has 500 applications. Each takes 10
  minutes to review. 500 X 10 5000 minutes 80
  hours and 20 minutes of work. She has 6 hours for
  the task. What should she do?

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Heuristics
In 6 hours, she can review 36 applications. She
reads 36 at random and hires the best person
among those 36 candidates. This is called
satisficing (doing well enough). Sometimes we
don't choose the most valuable outcome because
discovering it takes too much time. In such
cases, we use sensible strategies called
heuristics. Heuristics let us satisfice.
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Heuristics
A heuristic is a 'rule of thumb,' a procedure
which is easy to use, though it may not work. In
contrast, an algorithm is a step-by-step
procedure guaranteed to produce the correct
result. We do not always have an algorithm, and
sometimes when we do have one, it cannot be used
(as in the case of the HR person). Then, we use
heuristics.
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Important heuristics in decision making
1. Availability judgment that the more easily
an event comes to mind, the more likely it
is.   Often works - e.g., when was the last time
you met a professor who liked to be yelled
at? Sometimes doesnt work as in cases of
illusory correlation.
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Illusory correlations

• IC is found in cases of rare events that happen
  to co-occur.
• E.g., sports announcer says "X hasn't dropped
  the ball for 100 plays," and X drops the ball on
  the next play.
• You only notice this when the rare, newsworthy
  event happens - not when X doesn't then drop the
  ball.

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Representativeness heuristic

• 2. Representativeness - an event considered
  typical of a large class of events will be
  considered more probable than an atypical event.
•  
• Tversky Kahneman (1983)
• Linda is 31 years old, single, outspoken and
  very bright. She majored in philosophy. As a
  student, she was deeply concerned with issues of
  discrimination and social justice, and also
  participated in antinuclear demonstrations

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Representativeness heuristic
Which of these is more likely? A. Linda
is a bank teller. B. Linda is a bank teller and
is active in the feminist movement. Most
subjects picked B - but that is mathematically
impossible. The set of people (bank tellers who
are feminists) is smaller than the set of people
(bank tellers).
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Simulation heuristic
3. Simulation   Rushing to the airport, you miss
your plane by 5 minutes or by 2 hours. Which is
more annoying?   You can imagine a few things
changing on your trip to the airport, so that you
make up the 5 minutes and catch the plane. But
you can't imagine a few things changing to make
up 2 hours.
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Simulation heuristic

• The simulation heuristic lets us "see" the
  consequences of actions before we do them.
• What if Ben Stiller's character in Meet the
  Parents hadn't gone out on the roof for a
  cigarette? What if you took a year off from
  university and went travelling?
•  Simulation shows both alternative futures and
  alternative pasts that you could learn a lesson
  from.

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Review
There are three things we lack as decision
makers An objective way of evaluating
outcomes Unlimited cognitive processing
capacity Unlimited time to make our decisions
Thats alright. What we have to do to survive as
a species is make good decisions more often than
not. Heuristics help us to do that.