What Is Overconfidence Bias? | Definition & Examples

Overconfidence bias is the tendency to overestimate our knowledge and abilities in a certain area. As people often possess incorrect ideas about their performance, behavior, or characteristics, their estimations of risk and success often deviate from reality.

Example: Overconfidence bias
College students often overestimate how quickly they can finish writing a paper and are forced to pull an all-nighter when they realize it takes longer than expected. This is overconfidence bias at play.

Overconfidence bias can impact decision-making and interfere with our ability to exercise caution.

What is overconfidence bias?

Overconfidence bias is a type of cognitive bias that causes us to think we are better in some areas than we really are. Most people believe that they are more intelligent, more honest, or that they have a brighter future than the average person. For example, 93% of American drivers claim to be better than average, which is statistically impossible.

Because human judgment is highly susceptible to overconfidence bias, it is one of the most common types of bias. It is also a very serious one, as it reinforces other decision-making biases, such as hindsight bias, optimism bias, and action bias. Excessive faith in ourselves and our abilities makes it harder for us to see how prone we are to errors and biases.

Why does overconfidence bias matter?

Overconfidence bias causes us to lose objective perspective about our abilities or knowledge. This can create unrealistic expectations and make us more vulnerable to disappointment.

For example, overconfidence often leads students to poor study decisions, such as causing them to choose subjects they don’t really have an aptitude for. Overconfidence bias can also impede our learning if we don’t accurately assess the gap between what we currently know and what we need to know.

However, overconfidence bias does not only lead to poor decisions. Depending on the context, it can sometimes be the source of the right decision. For example, overconfident managers tend to push for innovation more frequently, and they are better at persuading investors to invest in higher-risk projects, which can enable further growth.

Overall, overconfidence bias is a double-edged sword: successful people show overconfidence, but overconfidence is not the determinant of success.

What are different types of overconfidence bias?

There are three distinct types of overconfidence. Each one has different psychological origins, occurs under different conditions, and has different consequences.

  • Overestimation refers to the overestimation of one’s true ability, performance, level of control, or chance of success. For example, doctors may overestimate the accuracy of their diagnoses, employees may overestimate the speed with which they can finish a task, and people tend to overestimate the level of control they have over situations.
  • Overplacement (or “better-than-average”) occurs when a majority of people rate themselves better than average, even though it is statistically impossible for most people to have better-than-average abilities. For example, in one study, 37% of a firm’s engineers ranked themselves among the top 5% of performers at the firm.
  • Overprecision is the false belief that the individual knows more than they know. It manifests as excessive certainty regarding the accuracy of one’s beliefs. This certainty is expressed using numbers, usually with unrealistic percentages or confidence intervals. For instance, gamblers exhibit overprecision when they assume that they can accurately predict what will appear next on the roulette.

Overconfidence bias example

Overconfidence bias is a common decision trap, or a thought process that can lead to suboptimal decisions. Anyone can fall for it, even experts.

Example: Overconfidence bias in business decisions
Overconfidence bias and optimism bias often cause company managers to underestimate the risk of entering a new market or introducing a new product. Because they are convinced that their product is innovative, managers overlook the intensity of the competition which endangers successful entry and the sales of the product in a new market.

Thanks to this, managers might succeed in entering the market, but studies show that this entry has a lower chance of survival and may cause the company to remain in an unprofitable market for too long.

One would expect that seasoned executives don’t make this type of mistake—however,  experience, level of knowledge, and past achievements actually all strengthen the overconfidence bias.

How to reduce overconfidence bias

Because overconfidence bias operates at an unconscious level, it is difficult to eliminate completely. However, there are steps you can take to keep it in check.

  • Perform a “premortem” on your decisions. Imagine that your decision led to a negative outcome and work backwards, thinking of all the possible reasons this might have occurred. This allows you to anticipate risks and be better prepared for negative outcomes.
  • Ask for feedback. Hearing other people’s perspectives, whether family members or colleagues, can help you identify areas where you may need improvement, and become less likely to fall for the overconfidence bias.
  • Instead of being afraid of mistakes, try to learn from them. When a decision doesn’t pan out the way you hoped, think about what you could have avoided, or in what areas you can do better. This will lead you to better-informed decisions and shield you from being overly optimistic in the future.

Other types of research bias

Frequently asked questions

What is a real-life example of overconfidence bias?

A real-life example of overconfidence bias is people’s assumptions about their sense of direction. Some people may think they have a great sense of direction even when visiting an unknown area. Because they trust their ability, they refuse to check a map or ask others for help. This can cause them to end up lost.

What is the opposite of overconfidence bias?

The opposite of overconfidence bias is underconfidence bias. Under this cognitive bias, people underestimate their ability to successfully perform a task or they underrate their own performance when comparing themselves to others.

What is the difference between overconfidence bias and the Dunning-Kruger effect?

Overconfidence bias and the Dunning-Kruger effect are quite similar in that they both refer to unwarranted confidence. However, there is a difference between them:

  • Overconfidence bias refers to people’s tendency to wrongly overestimate their knowledge or ability in a specific area, sometimes in comparison to others.
  • On the other hand, the Dunning-Kruger effect specifically refers to how people who lack experience, ability, or expertise in a certain domain of knowledge or in a given task tend to overestimate themselves.

In other words, overconfidence bias denotes a more universal tendency while the Dunning-Kruger effect denotes the overconfidence of those who are unskilled at a particular task.

Sources in this article

We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.

This Scribbr article

Nikolopoulou, K. (2023, March 18). What Is Overconfidence Bias? | Definition & Examples. Scribbr. Retrieved November 28, 2023, from https://www.scribbr.com/research-bias/overconfidence-bias/

Sources

Aren, S., & Hamamci, H. N. (2021). Biases in Managerial Decision Making: Overconfidence, Status Quo, Anchoring, Hindsight, Availability. Journal of Business Strategy Finance and Management, 3(1–2), 08–23. https://doi.org/10.12944/jbsfm.03.01-02.03

Čuláková, T., Kotrus, P., Uhlírová, A., & Jirásek, M. (2017). The overconfidence bias and CEO: a literature overview.

Moore, D. A., & Healy, P. M. (2008). The trouble with overconfidence. Psychological Review, 115(2), 502–517. https://doi.org/10.1037/0033-295x.115.2.502

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Kassiani Nikolopoulou

Kassiani has an academic background in Communication, Bioeconomy and Circular Economy. As a former journalist she enjoys turning complex scientific information into easily accessible articles to help students. She specializes in writing about research methods and research bias.