Decision-Making PDF

Judgement & Decision Making  What is a heuristic? A short cut, a rule of thumb Decisions Contrasts with an algorithm which is exhaustive Making step-by-step procedure that guarantees the correct solution, but may be time-consuming Heuristics and require a...

Judgement & Decision Making  What is a heuristic? A short cut, a rule of thumb Decisions Contrasts with an algorithm which is exhaustive Making step-by-step procedure that guarantees the correct solution, but may be time-consuming Heuristics and require a lot of mental effort Our minds tend to rely a lot on heuristics Heuristics = System 1  Systematic, not just random error from noise System 1 Not bugs or flaws Successful at solving problems in a natural environment Each card has a number on one side and color on the other. Which card or cards must be turned over to test the idea that if a card shows an even number on one face, then its opposite face is blue? The correct response is to turn over the 8 card and the red card. Each card has an age on one side and a drink on the other. Which card(s) must be turned over to test the idea that if you are drinking alcohol, then you must be over 18? Each card has an age on one side and a drink on the other. Which card(s) must be turned over to test the idea that if you are drinking alcohol, then you must be over 18? The correct response is to turn over "16” and "drinking beer" Cheater-detection module Evolutionary psychologists Leda Cosmides and John Tooby (1992) identified that the selection task tends to produce the "correct" response when presented in a context of social relations Human reasoning is governed by mechanisms that solve specific problems of social interaction, rather than context- free, general-purpose mechanisms In this case, the module is described as a specialized cheater- detection module During World War II, the U.S. wanted to add reinforcement armor to specific areas of its planes Analysts examined returning bombers, plotted the bullet holes and damage on them, and answered that adding armor to the tail, body, and wings would improve their odds of survival. But a young statistician named Abraham Wald noted that this would be a tragic mistake. Why? By only plotting data on the planes that returned, they were systematically omitting the data on a critical, informative subset: the planes that were damaged and unable to return. The "seen" planes had sustained damage that was survivable. The "unseen" planes had sustained damage that was not. Survivorship Bias  We learn about the decisions of famous, rich people, such as their decisions to drop out of college But we don’t learn about the vast majority of dropouts who don’t experience this same level of success Default Making an option a default increases the likelihood that it is effect chosen  Anchoring effect Anchoring occurs when individuals use an initial piece of information to make subsequent judgments The anchor can be absurdly high or absurdly low, or even unrelated to the issue Important implications for negotiations  People judge the probability of an event by the ease with which it comes to mind Availability heuristic Brains search engine (images, anecdotes) = surrogate for probability (# events)  What % of deaths are caused by war and conflict? Availability heuristic People estimate 5% Reality = 0.1% Availability heuristic Very low % of deaths are caused by nuclear power Yet there is massive opposition to nuclear power because of salient examples (e.g. Fukushima) The difference between 100 people going to a casino and one person going to a casino 100 times, i.e. between (path dependent) and conventionally understood probability. The mistake has persisted in economics and psychology since age immemorial. “Beyond, in real life, every single bit of risk you take adds up to reduce your life expectancy. If you climb mountains and ride a motorcycle and hang around the mob and fly your own small plane and drink absinthe, your life expectancy is considerably reduced although not a single action will have a meaningful effect. This idea of repetition makes paranoia about some low probability events perfectly rational.” -Nassim Taleb  Availability heuristic We use immediate examples that come to our mind when evaluating a specific decision The more easy something is to recall from memory, the more probable we judge it to be Solution: Look at the data and be mindful of this bias when reading the news Tom W. is of high intelligence, although lacking in true creativity. He has a need for order and clarity, and for neat and tidy systems in which every detail finds its appropriate place. His writing is rather dull and mechanical, occasionally enlivened by somewhat corny puns and by flashes of imagination of the sci-fi type. He has a strong drive for competence. He seems to have little feel and little sympathy for other people and does not enjoy interacting with others. Self- centered, he nonetheless has a deep moral sense. What is Tom’s major at university? Tom W. is of high intelligence, although lacking in true creativity. He has a need for order and clarity, and for neat and tidy systems in which every detail finds its appropriate place. His writing is rather dull and mechanical, occasionally enlivened by somewhat corny puns and by flashes of imagination of the sci-fi type. He has a strong drive for competence. He seems to have little feel and little sympathy for other people and does not enjoy interacting with others. Self- centered, he nonetheless has a deep moral sense. Base Rate fallacy – also know as the Representativeness Heuristic Most people say Computer Science Ignoring the base rate Most students are in Arts Difference between the Availability and Representative Heuristic The availability heuristic makes us estimate the likelihood of an event based on our ability to recall similar events The representativeness heuristic makes us estimate the probability of something based on the degree to which it resembles (or is representative of) a known situation The Exponential Growth Bias People grossly underestimate exponential growth  https://www.youtube.com/watch?v=eJmWu18pWtI Why don’t people appreciate exponential growth? Exponential growth produces distributions with thick tails (Not a Normal Distribution)  Represent: - Height - IQ - Speed of cars on the highway Thick-tail distribution Represents populations of cities Also represents pandemics: Most pandemics produce 10 million (due to exponential growth) Prospect Theory  Which do you choose? Option A: Get $900 for sure OR Option B: 90% chance to get $1,000  Which do you choose? Option A: Lose $900 for sure OR Option B: 90% chance to lose $1,000  Loss Aversion Losses loom larger than gains Will be more risk seeking to avoid a loss than to get a gain Will generally work harder to avoid losses than to get gains Ancestral reasons One could keep stockpiling food, but at some point the benefits diminish, especially without refrigeration But every loss of food moves a person closer to starvation  14 degrees for 60 seconds 14 degrees for 60 seconds, then 15 degrees for 30 seconds Asked which trial they wish to repeat Which did they choose? Peak End Rule We neglect the duration of the experience The pain or pleasure we remember from an experience is based on its peak and its end Gambler’s fallacy The mistaken belief that if something happens more frequently than normal during some period, it will or should happen less frequently in the future Can cause investors to trade a stock because it has been going up for a while May be correct for judgments about natural events, such as storms Endowment effect Once ownership is established, people favor the object they own, even when ownership is randomly assigned You are the vice president of a midsized high-tech firm. You have personally initiated a project to develop a radar-scrambling device that would make a plane undetectable by conventional radar. The project was estimated to cost 10 million dollars over a development period of 6 years. It’s been 3 years since the project began, and 5 out of the estimated 10 million dollar budget have already been spent. You have just discovered that while your product is still in development, another firm has already launched and begun marketing a very similar product with a much better design: It takes up less space and is much easier to operate than your design. As you are currently the manager in charge, the project now requires your authorization to allocate money for the next year.  Making a choice based not on what will produce the best outcome but based on a desire to not see your past investments or costs go to waste Sunk Cost Not just financial, but also in domains of time, health, ethics Fallacy It’s never too late to change course  Asked subjects for their predictions based on realistic "best guess" scenarios Or People were Asked subjects for their hoped-for "best asked how case" scenarios It produced indistinguishable results. long a task When people are asked for a "realistic" will take scenario, they envision everything going exactly as planned, with no unexpected delays or unforeseen catastrophes - the same vision as their "best case”. Planning Fallacy The tendency of individuals to underestimate the duration that is needed to complete most tasks Antidote to the Planning Fallacy? Way to overcome this bias is a premortem: Write down everything that could go wrong with the plan, then make your final estimate of how long it will take. Maximizers: People who want the absolute best option Satisficers: People who want the "good enough" option An extreme Maximizer will constantly seek to optimize every aspect of every decision. An extreme Satisficer will accept the first credible option as good enough and move on In a 2006 study, researchers followed 548 college seniors and found that the Maximizers got better jobs with higher salaries but were less satisfied with their jobs than the Satisficers The constant search for the best possible option can lead to better outcomes, but more unhappiness