It’s easy to think that we humans are poor decision-makers. If you read popular press books on decision-making you’ll hear a tale after tale about how we misuse probability, rely on the wrong information and can be most confident when we are most wrong.
The use of heuristics
You might find it a wonder that our species has survived this long, but we are poor decision-makers, at least for the sorts of decisions for which our species evolved. Yes we all make mistakes but those mistakes don’t reveal our weaknesses, but our strengths. In today’s lecture all explore the topic that is received the most attention and probably generate the most misinformation in popular treatments of decision-making: the use of heuristics.
As introducing the previous lecture heuristics are tools for optimizing the process of decision-making. Heuristics change how we approach decisions by ignoring some available information or prioritizing other information so the decisions can be made faster with less effort or more accurately. For example suppose that you are asked to guess the winner of this week’s marquee football game.
Say the Steelers are playing the Packers. If you are a football fan you might have a ready answer based upon the teams past history, their perceived strengths and weaknesses and even knowledge about relevant statistics, but let’s also suppose that you aren’t a football fan, you can’t rely on any of that useful information see you have to guess. You know about one of the players and the Steelers, he’s famous and always in funny commercials, so you pick the Steelers to win.
The definition of a heuristic
This represents something a decision scientists call the familiarity heuristic. People think the familiar things are better, more valuable, more frequent and in the case of sports more likely to win. Let’s see how this decision fits the definition of a heuristic. Does it ignore some available information? Yes! Almost all information that could be useful: who is favored in the game who is the home team and everything else is simply ignored.
Does it prioritize other information? Yes! The decision uses one fact there’s a famous player on the Steelers. Was the decision made faster? With less effort? Yes! It is fast and almost effortless to think: “I’ve heard of that player on the Steelers”. And lastly, was the decision accurate? your task was a predicament of a football game. No one knows ahead of time which team will win there’s too much uncertainty involved.
So accuracy doesn’t mean does the heuristic make the right prediction, instead it means does using the heuristic improve our chances of making the right prediction. In this specific case is familiarity a positive predictor of winning? Let me hold off answering to that specific question for a few minutes, but for now I can say that heuristics are, almost always faster almost always less effortful and often but not always more accurate than other decision-making processes.
Heuristics are not necessarily irrational
Heuristics are not necessarily irrational at least on the way sense of that word. When we don’t have much information toward a decision using a heuristic may be our best approach and, as I’ll describe in several examples, heuristics often work well even when we do have lots of information. Nor are heuristics necessarily emotional. Some heuristics involve emotion, but most do not and one can make vast low effort decisions without ever feeling sadness or anger or any other emotion.
Heuristics are often considered to be special cases of bounded rationality. You might know that bounded rationality arises from the interaction of two factors: our own computational limitations and the existence of structure in the environment. Because of the many ways in which our computational abilities are limited and the many sorts of structuring the environment many different sorts of heuristics have been identified.
Four of the most important heuristics, each of which provides a tool for overcoming a particular sort of cognitive limitation are: the familiarity heuristic – which involves memory, the anchoring heuristic – which involves valuation and reference points, the representativeness heuristic – which involves the estimation of probabilities and the affect heuristic – which involves simulation of feelings and emotions. But, this is another article.