Decision Making

Decision Making

1. Heurisitics

   • 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
       • 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
       •  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.

2. Biases

   • Overconfident
     • Confidence in decisions climbs as more information is obtained, even if information is dubious
       • 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
         • 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

3. 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

4. Problems with Expected Utility theory

   •  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