Zusammenfassung der Ressource
Decision Making
- Heurisitics
Anmerkungen:
- Tversky & Kahneman (1974) emphasized
use of heuristics to make up for lack of
information
- Strategies that can be applied
easily to a wide variety of
situations and often lead to
reasonable decisions
- They provide plausible conjectures, but not irrefutable conclusions.
- Availablity Huristic.
- Decisions based on the most "available" Memories
Anmerkungen:
- Judgments based on ease with which relevant instances can be retrieved from memory.
– E.g., Estimate in 7 seconds how many flowers, or Russian novelists you could name in two minutes.
- Preference for recent anecdotal evidence
- Is the letter 'r' more commonly the first or the third letter in words?
- Media coverage makes certain causes of
death seem more likely then others
- Generally we are less confident of decisions when asked
to produce more arguments in support (Bless & Pham,
2011).
- Representativeness Heuristic
- If something or someone appears to fit a category, you will use
what you know about that that category to make judgments.
- coin flips and subset judgements
- We should take statistics seriously
Anmerkungen:
- We aren’t good with probabilities.
– Overconfidence takes over and we tend to think we can
beat the odds
– “statistics happen to other people.”
In risky financial markets this can get people into a lot of trouble.
E.g., most people lose their money in futures markets
– but the spectacular profits that can be gained draw in people who believe they will be the ones to win.
- Biases
- Overconfident
- Confidence in decisions
climbs as more information
is obtained, even if
information is dubious
Anmerkungen:
- This bias greater in more difficult tasks.
– Estimating our potential productivity.
– “I can do the assigned paper in 3 hours, no problem”
However, an under-confidence bias may be even more problematic.
– May never make any decisions.
- Loss Aversive
- We weigh prospect of losses
more heavily. Sell gains, hold
losses.
- Kynamen called this Prospect theory
- The Endowment Effect
- Place higher value on what’s mine. – Bias may be
adaptive because losses could threaten survival.
- Framing of the Problem
- Framing Effects
- We judge choices by comparing them to
others in the same category
- Marketers often use products that no one wants
- We tend to ignore base
rates, even when stated
explicitly
Anmerkungen:
- Implications of analysis
Testing the whole population for HIV may kill more people than it saves.
Should you get a full-body scan that can randomly look for many diseases?
– Initial diagnosis effectively raises base-rate, thus makes specific tests more accurate.
Should we develop nation-wide databases for fingerprints and DNA?
– Only if we understand limitations.
– E.g., Man from US state of Oregon whose fingerprints matched some in Madrid after 2004 train bombing.
- Favor guaranteed option when framed as a
gain, risky option when framed as loss.
- Framing effects important decisions, like
organ donation. opt in v opt out.
- Evidence of the effect of un important information
- influence of faulty information
- Distortions in Judgements
- Status Quo Bias
- may be maintained by Loss Aversion
- Adaptivity
- We have limited memory, cognitive capacity, and time, so make
the best decisions we can rather best that are possible.
- We pick-up a lot of valid information from environment
- Problems with Expected Utility theory
Anmerkungen:
- Often doesn’t fit to empirical data. – Leads to various paradoxes.
– “Sunk cost” fallacy
Probabilities and utilities may be subjective, based on our own experience.
– Could represent individual beliefs
– Savage (1954) developed subjective expected
utility theory.
Can think of expected utility theory as a normative
theory
– what people should do, given certain assumptions.
- Often doesn’t fit to empirical data
- Probabilities and utilities
may be subjective,
based on our own
experience
- Can think of expected
utility theory as a
normative theory