Decision making is an integral part of every person’s day. There is no way to avoid this, as even the act of deciding not to make a decision is, in fact, a decision in and of itself. Life also presents us with many opportunities to solve problems. By understanding the cognitive processes involved in decision making and problem solving, we can analyze our own actions and the actions of others.
This analysis can improve the results of our problem solving and decision making, both personally and professionally. Representativeness heuristics defines several fallacies and cognitive biases, but it can also give us the ability to make decisions quickly when the situation calls for fast action.
What is Representativeness Heuristic?
Let’s start out with a couple of definitions:
- Heuristics- First what are heuristics? In the most basic terms, heuristics are a sort of mental short hand used in problem solving and decision making. We use heuristics when we make a decision or solve a problem by using a rule of thumb strategy in order to shorten the process.
- Representativeness- Representativeness, in terms of problem solving and decision making, refers to an existing group or set of circumstance that exists in our minds as most similar to the problem or decision at hand. This allow for the mental short hand decision making that is typical of representativeness heuristics.
- Representativeness Heuristic- The combined term then refers to the process of decision making or problem solving using a rule of thumb strategy. This strategy seeks to identify a familiar object or event that is similar to the current situation and use the same methods to satisfy the current issue.
Is it a Problem or a Decision?
Often people use the terms problem and decision interchangeably. However, they each have unique definitions and approaches. A problem requires a person or persons to identify various appropriate responses or actions and determine which one will most likely produce the desired results. When making a decision, either individually or in a group, a person uses cognitive processes to select a course of action or a belief from a set of options. There are several different decision making styles and these will affect the way decisions are made. In a group decision making process these styles can make a large impact on how well the group functions together.
History of Heuristics
Early in the 1970’s psychologists Amos Tversky and Daniel Kahneman defined and demonstrated three specific types of heuristics. The types that were identified are availability, anchoring and adjustment, and representativeness heuristics. A number of other heuristics have been identified in the years since the original three were defined. These early findings gave rise to the Heuristics and Biases research program.
This program studied the ways in which individuals and groups make decisions and solve problems and the conditions under which those decisions are unreliable or incorrect. The results of this research called into question the widely held thought that humans are by nature rational actors. It did however provide a theory of information processing that explains how most people make choices or estimates. This research is the basis of most current theory on decision making and problem solving today.
In 2002 Khaneman was awarded The Bank of Sweden Prize in Economic Sciences In Memory of Alfred Nobel.
Types of Heuristics
Availability in heuristics refers to how easily an idea or event can be brought to mind. An idea that is “larger than life” and in the forefront of a person’s mind will often seem much more likely to occur, even though the facts and statistics would indicate otherwise. When buying a lottery ticket, visions of local winners celebrating may be more available in a person’s mind than are the real statistics portraying the likelihood of winning. Availability heuristics account for people being swayed by a big, flashy story as opposed to a large body of scientific evidence. Advertising and political races are often guilty of using availability heuristics against consumers and the general public.
Anchoring and Adjustment Heuristics
Situations in which numbers must be estimated often call into play anchoring and adjustment heuristics. The anchor is the base number from which an estimate process begins. The adjustment is the amount, up or down, that the estimate is moved based on prior knowledge of the situation. In an experiment performed by Tversky and Kahneman, subjects were asked to decide if a percentage was higher or lower for a particular question than an amount chosen at random on a spinning wheel. Subjects tended to answer very closely to the pre-selected random percentage. This and other experiments point to a failure for most people to differ enough from the anchor even when there is no factual basis for said anchor point.
When people use categories in order to make a decision about a person, thing or event they are utilizing representativeness heuristics. Using representativeness heuristics during problem solving or decision making can give rise to several fallacies. These fallacies can lead to poor decision making or problem solving for the person that falls victim to this way of thinking.
The base rate fallacy occurs when a person over estimates the likelihood that something (or some event) has a rare or unlikely property, or under- estimates the likelihood that something (or some event) has a very common property. The base rate fallacy can be observed when an attribute of an individual is assessed based solely upon the individual and not upon the rate at which the attribute occurs in the population. Misperception of randomness can also be a product of representativeness heuristics. In a random event where there is a 50/50 chance of either event occurring, people tend to feel that a more varied result is more likely than a more uniform result. This is illustrated easily using a simple coin toss. People are more likely to expect HHTHTTHT as a result as opposed to HHHHHHHH, even though both are equally likely. This effect is sometimes referred to as the gambler’s fallacy, which is the belief that outcomes will tend to even out after several occurrences. The gambler’s fallacy takes shape as the idea that after several losses an individual is “due” a win. The laws of statistics show us that there is no effect on the next outcome in a series of events based on the outcome of the previous event.
Representativeness Heuristics in Action
For an example, imagine that in an experimental protocol you were given the description of a random person: Catherine is loud, opinionated, intelligent and self-sufficient. From this information would you consider her most likely to be a lawyer, feminist activist, or elementary school teacher? We know that the percentage of each vocation in our survey is 10%, 5%, and 85% respectively. Most people would categorize Catherine as most likely to be a feminist activist even though this group is by far the smallest percentage of the total. This is a demonstration of representativeness heuristics in action. The reality of the situation is that Catherine is in fact an elementary school teacher and our labeling of her as a feminist activist is a function of our own preconceived ideas. The use of stereotypes is by nature representativeness heuristic.
In some instances representativeness heuristics can actually be beneficial. The mental short cuts we take when we indulge in representativeness heuristics can help us make decisions or solve problems quickly. The down side to this is a tendency to not consider any other course of action besides the one that immediately springs to mind. As we can see, the representativeness heuristic also plays into stereotypes of people and even events.