Representative Heuristics

Representative heuristics is a shortcut in which one reaches a decision based on past experience or on the similarity of the event with a preconceived notion. In this, one reaches a decision or conclusion quickly without analyzing the available factual information.

A representative heuristic can often lead to incorrect or biased decisions which lack the judgment skills of a person. Some representative heuristics examples include basing an investment decision on the historical returns of a stock, assuming a person wearing glasses to be an engineer, concluding that product X has good quality if it is costly, and so on.

• Representative heuristic involves making decisions based on past experiences or typical examples. The similarity between an event and its outcomes forms the basis of decisions.
• A decision based on representative heuristics is quick though it can be misleading and flawed.
• In the availability heuristic, decisions are based on events that took place recently. The more one is impacted by an event, the easier it is to recall it, and the higher the chances of basing decisions on it.
• A representative heuristic can be overcome by becoming aware of its usage, making judgments backed by data, bringing in a fresh perspective, and changing with the feedback obtained.

The representative heuristic is also called the representativeness heuristic. The representative heuristics psychology was formulated and explained by Daniel Kahneman and Amos Tversky in the 1970s. Their book “Judgment under Uncertainty: Heuristics and Biases” discusses the decisions based on representative heuristics and the way they can be improved.

A decision based on the representative heuristic relies on prototypes, stereotypes or preconceived notions. Precisely, the decision-maker identifies a pattern or similarity in the happening of an event and its outcome.

The concept of representative heuristic works in the following way:

1. A person, P, believes that whenever event B occurs, its outcome is D. This is because event B is similar to the group of events that have happened in the past.
2. The next time event B occurs, P jumps to the conclusion that the outcome will be D. So, P bases his decision on outcome D.

Due to the representative heuristic, P thinks that the event B is a typical case of D. While making a decision, P ignores that event B could occur because of several logical factors and can have different outcomes other than D. Consequently, P makes a wrong decision based on just one aspect, that is, his past impression of a similar event.

The decisions may be based on a representative heuristic for the following reasons:

• Existence of a prototype–The happening of an event may depend on a prototype or a typical example. If the event represents a particular case of the past, the future decisions of a human being will be impacted by this heuristic.
• Usage of mental shortcuts–A person may rely on mental shortcuts while making decisions. Such decisions ignore the statistical probability or the rationale of an argument. The decisions based on mental shortcuts consider only one characteristic (i.e., the existing impression) and ignore all the other characteristics of the supplied information.
• Existence of a resemblance–There is often a resemblance or similarity in the happening of events and their outcomes. This similarity creates a preconceived notion of a person. Such a notion forms the basis of a biased decision.

Therefore, decisions based on the representative heuristic are often biased, flawed, and lack logical reasoning. This is because, in representative heuristics, a person compares an event with a pre-defined mental representation and then acts accordingly.

Let us consider a few examples to understand the concept of representative heuristics.

Example #1

The security, S, of a company has not been performing well in the last four years. However, after the lockdown was over, the company entered a new international market where its services were in high demand.

The inferences are stated as follows:

• An investor sells the security S. This is because he thinks that if this security did not perform well in the last four years, it would not perform well now too. This decision is based on representative heuristics.
• The investor who sold S faces a loss as the market price increases. He relied on the representative heuristic rather than evaluating the logical factor, market demand.

Example #2

A bank, R, is operating successfully in several countries, due to which its shares are performing fairly well. However, in the preceding month, a major corporate customer defaulted on a huge loan as it experienced losses in the business.

The inferences are stated as follows:

• An investor buys the shares of the bank R. The reason is the belief that the shares have been performing well, consistently, for a long time. This decision is an outcome of representative heuristics.
• The investor who bought the shares of R suffers a loss as the market price begins to fall. Rather than acting on the representative heuristic, the investor should have collected factual information before buying the shares of the bank.

Since the representative heuristic is a cognitive flaw of the human brain, it is difficult to avoid it completely. However, its negative impact can be reduced or prevented to some extent.

The ways to overcome the impact of a representative heuristic are listed as follows:

• One should be aware that his/her decision is based on representative heuristics. This will help prevent errors in decision-making.
• One must think in different directions. He/she must assess several factors and think logically at each step. In this way, the decision will be an outcome of reasoning rather than a representative heuristic.
• One should ask his/her peers and friends for feedback while making important decisions. This will help one realize whether he/she is relying on the representative heuristic or not.
• One must approach each situation from a fresh perspective rather than a preconceived notion or past experience.

In the works of Daniel Kahneman and Amos Tversky, there is another heuristic called the availability heuristic. In this heuristic, decisions are based on recent information or the most easily available information.

The differences between representative heuristic and availability heuristic are listed as follows:

This has been a guide to Representative Heuristics and its definition. Here we discuss the examples of representative heuristics, how to control it, and the differences between representative and availability heuristics. You can learn more from the following articles –