A cognitive bias is a systematic error in thinking that occurs when people are processing and interpreting information in the world around them and affects the decisions and judgments that they make. We are often presented with situations in life when we need to decide with imperfect information, and we unknowingly rely on prejudices or biases.

For example, we might:

  • Trust someone more if they’re an authority figure than if they’re not
  • Assume someone’s gender based on their profession
  • Make poor decisions based on the information that we’re given

The reasons for our poor decision-making can be a consequence of heuristics and biases. In general, heuristics and biases describe a set of decision-making strategies and the way that we weigh certain types of information. The existing literature on cognitive biases and heuristics is extensive, but this post is a user-friendly summary.

Central to this post’s topic is how cognitive heuristics and biases influence our decision-making. We will also learn more about how to overcome them.

What Are Cognitive Biases?

When considering the term ‘cognitive biases,’ it’s important to note that there is an overlap between cognitive biases and heuristics. Sometimes these two terms are used interchangeably, as though they are synonyms; however, their relationship is nuanced.

In his book, Thinking, Fast and SlowProfessor Daniel Kahneman (2011, p. 98) defines heuristics as

a simple procedure that helps find adequate, though often imperfect, answers to difficult questions.

Tversky and Kahneman (1974, p. 1130) define the relationship between biases and heuristics as follows:

… cognitive biases that stem from the reliance on judgmental heuristics.

Gonzalez (2017, p. 251) also described the difference between the two terms:

Heuristics are the ‘shortcuts’ that humans use to reduce task complexity in judgment and choice, and biases are the resulting gaps between normative behavior and the heuristically determined behavior.

Types

Learn more about a few of the most common types of cognitive biases that can distort your thinking.

  • Actor-observer bias: This is the tendency to attribute your actions to external causes while attributing other people’s behaviors to internal causes. For example, you attribute your high cholesterol level to genetics while you consider others to have a high level due to poor diet and lack of exercise.
  • Anchoring bias: This is the tendency to rely too heavily on the very first piece of information you learn. For example, if you learn the average price for a car is a certain value, you will think any amount below that is a good deal, perhaps not searching for better deals. You can use this bias to set the expectations of others by putting the first information on the table for consideration.
  • Attentional bias: This is the tendency to pay attention to some things while simultaneously ignoring others. For example, when deciding on which car to buy, you may pay attention to the look and feel of the exterior and interior, but ignore the safety record and gas mileage.
  • Availability heuristic: This is placing greater value on information that comes to your mind quickly. You give greater credence to this information and tend to overestimate the probability and likelihood of similar things happening in the future.
  • Confirmation bias: This is favoring information that conforms to your existing beliefs and discounting evidence that does not conform.
  • False consensus effect: This is the tendency to overestimate how much other people agree with you.
  • Functional fixedness: This is the tendency to see objects as only working in a particular way. For example, if you don’t have a hammer, you never consider that a big wrench can also be used to drive a nail into the wall. You may think you don’t need thumbtacks because you have no corkboard on which to tack things, but do not consider their other uses. This could extend to people’s functions, such as not realizing a personal assistant has the skills to be in a leadership role.
  • Halo effect: Your overall impression of a person influences how you feel and think about their character. This especially applies to physical attractiveness influencing how you rate their other qualities.
  • Misinformation effect: This is the tendency for post-event information to interfere with the memory of the original event. It is easy to have your memory influenced by what you hear about the event from others. Knowledge of this effect has led to a mistrust of eyewitness information.
  • Optimism bias: This bias leads you to believe that you are less likely to suffer from misfortune and more likely to attain success than your peers.
  • Self-serving bias: This is the tendency to blame external forces when bad things happen and give yourself credit when good things happen. For example, when you win a poker hand it is due to your skill at reading the other players and knowing the odds, while when you lose it is due to getting dealt a poor hand.
  • The Dunning-Kruger effect: This is when people believe that they are smarter and more capable than they are. For example, when they can’t recognize their incompetence.

At times, multiple biases may play a role in influencing your decisions and thinking. For example, you might misremember an event (the misinformation effect) and assume that everyone else shares that same memory of what happened (the false consensus effect).

Lists and Types of Biases: The Codex

According to the Cognitive Bias Codex, there are an estimated 180 cognitive biases (this list is frequently updated.)

Created by John Manoogian III and Buster Benson, this codex is a useful tool for visually representing all of the known biases that exist to date.

The biases are arranged in a circle and can be divided into four quadrants. Each quadrant is dedicated to a specific group of cognitive biases:

  1. What should we remember?
    Biases that affect our memory for people, events, and information
  2. Too much information
    Biases that affect how we perceive certain events and people
  3. Not enough meaning
    Biases that we use when we have too little information and need to fill in the gaps
  4. Need to act fast
    Biases that affect how we make decisions

The Cognitive Bias Codex is a handy visual tool that organizes biases in a meaningful way; however, it is worth pointing out that the codex lists heuristics and biases both as ‘biases.’

If you decide to rely on the Cognitive Bias Codex, then keep in mind the distinction between heuristics and biases mentioned above.

4 Examples of Cognitive Biases

There are numerous examples of cognitive biases, and the list keeps growing. Here are a few examples of some of the more common ones.

1. Confirmation bias

This bias is based on looking for or overvaluing information that confirms our beliefs or expectations (Edgar & Edgar, 2016; Nickerson, 1998). For example, a police officer who is looking for physical signs of lying might mistakenly classify other behaviors as evidence of lying.

2. Gambler’s fallacy

This false belief describes our tendency to believe that something will happen because it hasn’t happened yet (Ayton & Fischer, 2004; Clotfelter & Cook, 1993).

For example, when betting on a roulette table, if previous outcomes have landed on red, then we might mistakenly assume that the next outcome will be black; however, these events are independent of each other (i.e., the probability of their results do not affect each other).

3. Gender bias

Gender bias describes our tendency to assign specific behavior and characteristics to a particular gender without supporting evidence (Garb, 1997).

For example, complaints of pain are taken more seriously when made by a male,ather than female, patients (Gawande, 2014); women are perceived as better caregivers than men (Anthony, 2004); specific clinical syndromes are more readily diagnosed in women than in men (Garb, 1997); and students often rate female lecturers lower than male lecturers (MacNeill, Driscoll, & Hunt; 2014; Mitchell & Martin, 2018).

4. Group attribution error

This error describes our tendency to overgeneralize how a group of people will behave based on an interaction with only one person from that group (Pettigrew, 1979).

For example, a negative experience with someone from a different group (e.g., a different culture, gender, religion, political party, etc.) might make us say that all members of that group share the same negative characteristics. Group attribution error forms part of the explanation for prejudice in social psychology.

Examples in Business and Everyday Life

Gender bias in the workplace is a well-documented and researched area of cognitive bias. Women often do not occupy top senior positions. For example, in 2010, only 15.2% of top positions in US Fortune-500 companies were held by women (Soares, 2010). Women tend to earn less than their male counterparts, and women’s salaries differ according to their marital status.

For example, consider these statistics reported by Güngör and Biernat (2009, p. 232):

[In 2005]  … 68.1% of married and 79.8% of single mothers in the U.S. participate in the workforce, but while non-mothers earn 90 cents to a man’s dollar, mothers earn 73 cents, and single mothers earn about 60 cents.”

The social desirability bias is a concern for anyone who uses self-report data. Companies that run internal surveys investigating topics that may cast an employee in a poor light must be aware of how the social desirability bias will affect the validity of their data.

Knowing that people adjust their answers to appear more socially desirable, investigators (such as researchers and clinicians) can try to reframe their questions to be less direct, use formal tests, or anonymize responses.

Another sphere of our lives where biases can have devastating effects is personal finance. According to Hershey, Jacobs-Lawson, and Austin (2012), there are at least 40 cognitive biases that negatively affect our ability to make sound financial decisions, thus hindering our ability to plan for retirement properly. Some of these biases include:

  • Halo effect (just because that real estate agent was nice doesn’t mean it’s a good deal)
  • Optimistic overconfidence (“I’ll be fine in the future, so I don’t need to save that much now.”)
  • Confirmation bias (looking for information to confirm or validate unwise financial decisions)

Role of Biases in Decision Making

Below you might find revealing insight into how biases affect our decision-making.

The Monty Hall problem

This puzzle based on the American game show ‘Let’s Make a Deal is a good illustration of how biases affect our decision-making.

Assume that there are three doors.

  • Behind one door is a fantastic prize: a car.
  • Behind the other two doors are mediocre prizes: $1,000.

You initially choose Door 1. Before revealing what’s behind your chosen door, the presenter opens a different door, Door 2, to reveal the mediocre prize. The presenter then gives you the option to either keep what’s behind your initial chosen door or change your choice, knowing what’s behind Door 2. What should you do now? Should you stay with your initial choice, Door 1, or should you switch to Door 3?

The correct answer is that you have the best chance of winning the car if you change your choice. This is called the Monty Hall problem. Here’s why you should switch:

  1. When you made your initial decision, you didn’t know what the outcome would be (mediocre prize versus awesome prize).
  2. After the host reveals more information, you have a better idea about which prizes are behind which doors.
  3. Based on this information, you’re more likely to find the car if you change your chosen door, an improvement from odds of 1 in 3 for your initial choice, to 2 in 3 if you switch.

Despite the statistics being in favor of switching, most people are hesitant to abandon their first choice and don’t accept the offer to change it.

Impact of Cognitive Bias

Cognitive biases can lead to distorted thinking. Conspiracy theory beliefs, for example, are often influenced by a variety of biases.2 But cognitive biases are not necessarily all bad. Psychologists believe that many of these biases serve an adaptive purpose: They allow us to reach decisions quickly. This can be vital if we are facing a dangerous or threatening situation.

For example, if you are walking down a dark alley and spot a dark shadow that seems to be following you, a cognitive bias might lead you to assume that it is a mugger and that you need to exit the alley as quickly as possible. The dark shadow may have simply been caused by a flag waving in the breeze, but relying on mental shortcuts can often get you out of the way of danger in situations where decisions need to be made quickly.

Tips for Overcoming Cognitive Bias

Research suggests that cognitive training can help minimize cognitive biases in thinking.3 Some things that you can do to help overcome biases that might influence your thinking and decision-making include:

  • Being aware of bias: Consider how biases might influence your thinking. In one study, researchers provided feedback and information that help participants understand these biases and how they influence decisions. The results of the study indicated that this type of training could effectively reduce the effects of cognitive bias by 29%.3
  • Considering the factors that influence your decisionsAre there factors such as overconfidence or self-interest at play? Thinking about the influences on your decisions may help you make better choices.
  • Challenging your biases: If you notice that there are factors influencing your choices, focus on actively challenging your biases. What are some factors you have missed? Are you giving too much weight to certain factors? Are you ignoring relevant information because it doesn’t support your view? Thinking about these things and challenging your biases can make you a more critical thinker

Reducing cognitive bias may also be beneficial in the treatment of some mental health conditions.4 Cognitive bias modification therapy (CBMT) is a treatment approach based on processes that are designed to reduce cognitive bias. This form of therapy has been used to help treat addictions, depression, and anxiety.

Other cognitive biases

The Monty Hall problem is an excellent example of how our intuitions and heuristics lead us to make poor decisions. However, there are lots of other cognitive biases and heuristics that also affect our decision-making.

Kahneman, Slovic, Slovic, & Tversky (1982) list 13 biases that arise from the following three heuristics:

  • Representativeness
    We think that the likelihood of two things happening is higher when the two things resemble or are similar to each other.

    • A cognitive bias that may result from this heuristic is that we ignore the base rate of events occurring when making decisions. For example, I am afraid of flying; however, it’s more likely that I might be in a car crash than in a plane crash. Despite this, I still hate flying but am indifferent to hopping into my car.
  • Availability
    We tend to overestimate how likely something is to happen based on how easily we can remember the same thing happening previously.

    • For example, when a violent crime occurs in a neighborhood, neighbors in that neighborhood will give a bigger estimate of the frequency of these crimes, compared to the reported statistics. The reason for their overestimation is that the memory of the violent crime is easy to retrieve, which makes it seems like violent crime happens more frequently than it does.
  • Adjustment and anchoring
    Our decisions, and the changes to our decisions, are influenced by the first bit of information that we’re given.

    • For example, assume that I offer to sell you a car and I ask for $250. You counter with $200. You might think that this is a good deal because you bought the car for less than the asking price; however, your counteroffer was heavily influenced by my asking price, and you’re not likely to deviate too much from it.

2 Popular Experiments

To further illustrate the effect of cognitive bias, below are two popular experiments.

1. Anchoring and adjustment

Tversky and Kahneman (1974) found that our estimates are heavily influenced by the first number given to us. For example, participants were asked to estimate the percentage of African countries in the United Nations.

Before giving their answer, each participant had to spin a ‘Wheel of Fortune,’ which would determine their initial starting percentage. The result of the ‘Wheel of Fortune was random and meaningless. Despite this, participants’ estimates of African UN member countries didn’t differ much from whatever random ‘Wheel of Fortune’ amount they landed on, regardless of what that amount was.

2. The attractiveness halo effect

Male students were asked to rate essays written by female authors (Landy & Sigall, 1974). The quality of the essays varied: some were poorly written, and others were well written.

Additionally, some of the essays were accompanied by a photograph of the author (who was either attractive or unattractive), and others were not. Male college students rated the quality of the essay and the talent of the authors higher when:

  • the essay was written by an attractive author, and
  • this effect was evident only when the essay was of poor quality.

In this study, the male students demonstrated the halo effect, applying the perceived attractiveness of the female author to the quality of the paper.

4 Ways to Overcome Your Biases

Here is a list of four methods that you can use to overcome your own biases.

1. Reflect on past decisions

If you’ve been in a similar situation before, you can reflect on the outcomes of those previous decisions to learn how to overcome your biases.

An example of this is budgeting. We tend to underestimate how much money we need to budget for certain areas of our life. However, you can learn how much money to budget by tracking your expenditure for the last few months. Using this information from the past, you can better predict how much money you’ll need for different financial categories in the future.

2. Include external viewpoints

There is some evidence that we make better decisions and negotiations when we consult with other people who are objective, such as mediators and facilitators (Caputo, 2016).

Therefore, before making a decision, talk to other people to consider different viewpoints and have your views challenged. Importantly, other people might spot your own cognitive biases.

3. Challenge your viewpoints

When making a decision, try to see the weaknesses in your thinking regardless of how small, unlikely, or inconsequential these weaknesses might seem. You can be more confident in your decision if it withstands serious, critical scrutiny.

4. Do not make decisions under pressure

A final way to protect yourself from relying on your cognitive biases is to avoid making any decisions under time pressure. Although it might not feel like it, there are very few instances when you need to make a decision immediately. Here are some tips for making a decision that can have substantial consequences:

  1. Take the necessary time to ruminate.
  2. List the pros and cons.
  3. Talk to friends or family members for advice (but remember that they may have their own biases).
  4. Try to poke holes in your reasoning.

Bias Modification Exercises and Activities

In the last decade, research has looked at cognitive bias modification (CBM) since cognitive biases are associated with the severity of anxiety and depression. The relationship between cognitive biases and anxiety and depression is assumed to be causal; that is, cognitive biases cause an increase in the severity of symptoms.

CBM exercises are designed with this causal relationship in mind. If the cognitive bias is removed or reduced, then the severity of the symptoms should also lessen.

There are two categories of CBM exercises:

  1. Changing attentional bias: In this type of exercise, participants are trained to pay more attention to positive stimuli instead of negative stimuli.
  2. Changing interpretation bias: Participants are primed with positive information before completing an emotionally ambiguous task.

At least six meta-analyses report conflicting findings (Beard, Sawyer, & Hofmann, 2012; Cristea, Kok, & Cuijpers, 2015; Hakamata et al., 2010; Hallion & Ruscio, 2011; Heeren, Mogoașe, Philippot, & McNally, 2015; Mogoaşe, David, & Koster, 2014).

There are many reasons for these differences; for example, the types of studies included, the moderators included, the definition of the interventions, the outcome variable used, the clinical condition studied, and so forth. Therefore, the jury is still out on whether CBM affects symptom severity reliably.

A Look at Cognitive Bias Modification Apps

There are many cognitive bias modification apps available for download. Before purchasing an app, research whether the creator of the app has followed sound research principles or done any research when developing the app (Zhang, Ying, Song, Fung, & Smith, 2018).

Most bias modification apps aim to change attentional bias. For example, the following apps aim to train users to respond more quickly to happy faces than to sad or angry faces. All four hypothesize that repeated use will result in more positive moods.

The Cognitive Bias Cheatsheet is a useful way to remind oneself of the different cognitive biases that exist.

5 Relevant Books

Here is a list of books relevant to anyone interested in cognitive biases.

Firstly, any list of biases would be remiss without Thinking, Fast and Slow by Daniel Kahneman (2011). In this book, Kahneman unpacks some of the most common biases that we experience when making decisions. (Available on Amazon)

Amazon Best Seller
Thinking, Fast and Slow
29,030 Reviews
Thinking, Fast and Slow
  • A good option for a Book Lover
  • It comes with proper packaging
  • Ideal for Gifting
  • Kahneman, Daniel (Author)
  • English (Publication Language)
  • 499 Pages - 04/02/2013 (Publication Date) - Farrar, Straus and Giroux (Publisher)

In the same vein is The Drunkard’s Walk: How Randomness Rules Our Lives by Leonard Mlodinow (2009). This book addresses how humans misjudge the effect that randomness has on our decision-making. (Available on Amazon)

Amazon Best Seller
The Drunkard's Walk: How Randomness Rules Our Lives
  • Mlodinow, Leonard (Author)
  • English (Publication Language)
  • 252 Pages - 05/05/2009 (Publication Date) - Vintage (Publisher)

Predictably Irrational by Dan Ariely (2008) is an excellent and very accessible book about how our behavior is often governed by seemingly random and illogical thought processes. The opening chapter is jaw-dropping. (Available on Amazon)

Amazon Best Seller
Predictably Irrational, Revised and Expanded Edition: The Hidden Forces That Shape Our Decisions
  • Ariely, Dr. Dan (Author)
  • English (Publication Language)
  • 384 Pages - 04/27/2010 (Publication Date) - Harper Perennial (Publisher)

Nassim Nicholas Taleb published a series of books – five, in fact – and I include two of them on this list: Fooled by Randomness (2005) and The Black Swan (2007). The entire series discusses various aspects of uncertainty. (Available on Amazon)

Incerto: Fooled by Randomness, The Black Swan, The Bed of Procrustes, Antifragile
  • Taleb, Nassim Nicholas (Author)
  • English (Publication Language)
  • 1568 Pages - 11/15/2016 (Publication Date) - Random House Trade Paperbacks (Publisher)

A Take-Home Message

We often rely on cognitive heuristics and biases when making decisions.

Heuristics can be useful in certain circumstances; however, heuristics and biases can result in poor decision-making and reinforce unhealthy behavior.

There are many different types of cognitive biases, and all of us are victims of one or more. However, being aware of our biases and how they affect our behavior is the first step toward resisting them.

REFERENCES

  • Anthony, A. S. (2004). Gender bias and discrimination in nursing education: Can we change it? Nurse Educator, 29(3), 121–125.
  • Ariely, D. (2008). Predictably irrational. Harper Perennial.
  • Ayton, P., & Fischer, I. (2004). The hot hand fallacy and the gambler’s fallacy: Two faces of subjective randomness? Memory & Cognition, 32(8), 1369–1378.
  • Beard, C., Sawyer, A. T., & Hofmann, S. G. (2012). Efficacy of attention bias modification using threat and appetitive stimuli: A meta-analytic review. Behavior Therapy, 43(4), 724–740.
  • Caputo, A. (2016). Overcoming judgmental biases in negotiations: A scenario-based survey analysis on third party direct intervention. Journal of Business Research, 69(10), 4304–4312.
  • Clotfelter, C. T., & Cook, P. J. (1993). The “gambler’s fallacy” in lottery play. Management Science, 39(12), 1521–1525.
  • Cristea, I. A., Kok, R. N., & Cuijpers, P. (2015). Efficacy of cognitive bias modification interventions in anxiety and depression: Meta-analysis. The British Journal of Psychiatry, 206(1), 7–16.
  • Edgar, G., & Edgar, H. (2016). Perception and attention: Errors and accidents. In D. Groome and M.W. Eysenck (Eds.), An introduction to applied cognitive psychology (2nd ed) (pp. 9–38). Routledge.
  • Garb, H. N. (1997). Race bias, social class bias, and gender bias in clinical judgment. Clinical Psychology: Science and Practice, 4(2), 99–120.
  • Gawande, A. (2014). Being mortal: Medicine and what matters in the end. Metropolitan Books.
  • Gonzalez, C. (2017). Decision-making: A cognitive science perspective. In S. Chipman (Ed.), The Oxford handbook of cognitive science (pp. 249–264). Oxford University Press. Accessed on July 9, 2020, from https://www.cmu.edu/dietrich/sds/ddmlab/papers/oxfordhb-9780199842193-e-6.pdf
  • Güngör, G., & Biernat, M. (2009). Gender bias or motherhood disadvantage? Judgments of blue-collar mothers and fathers in the workplace. Sex Roles, 60(3–4), 232–246.
  • Hakamata, Y., Lissek, S., Bar-Haim, Y., Britton, J. C., Fox, N. A., Leibenluft, E., … & Pine, D. S. (2010). Attention bias modification treatment: A meta-analysis toward the establishment of novel treatment for anxiety. Biological Psychiatry, 68(11), 982–990.
  • Hallion, L. S., & Ruscio, A. M. (2011). A meta-analysis of the effect of cognitive bias modification on anxiety and depression. Psychological Bulletin, 137(6), 940.
  • Heeren, A., Mogoașe, C., Philippot, P., & McNally, R. J. (2015). Attention bias modification for social anxiety: A systematic review and meta-analysis. Clinical Psychology Review, 40, 76–90.
  • Hershey, D. A., Jacobs-Lawson, J. M., & Austin, J. T. (2012). Effective financial planning for retirement. In M. Wang (Ed.), Oxford handbook of retirement (pp. 402–430). Oxford University Press.
  • Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus, and Giroux.
  • Kahneman, D., Slovic, S. P., Slovic, P., & Tversky, A. (Eds.). (1982). Judgment under uncertainty: Heuristics and biases. Cambridge University Press.
  • Landy, D., & Sigall, H. (1974). Beauty is talent: Task evaluation as a function of the performer’s physical attractiveness. Journal of Personality and Social Psychology, 29(3), 299.
  • MacNell, L., Driscoll, A., & Hunt, A. N. (2014). What’s in a name: Exposing gender bias in student ratings of teaching. Innovative Higher Education, 40(4), 291–303.
  • Mitchell, K. M., & Martin, J. (2018). Gender bias in student evaluations. PS: Political Science & Politics, 51(3), 648–652.
  • Mlodinow, L. (2009). The drunkard’s walk: How randomness rules our lives. Vintage.
  • Mogoaşe, C., David, D., & Koster, E. H. (2014). Clinical efficacy of attentional bias modification procedures: An updated meta‐analysis. Journal of Clinical Psychology, 70(12), 1133–1157.
  • Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220.
  • Pettigrew, T. F. (1979). The ultimate attribution error: Extending Allport’s cognitive analysis of prejudice. Personality and Social Psychology Bulletin, 5(4), 461–476.
  • Soares, R. (2010). 2010 Catalyst census: Fortune 500 women board directors. Catalyst.
  • Taleb, N. N. (2005). Fooled by randomness: The hidden role of chance in life and the markets (vol. 1). Random House.
  • Taleb, N. N. (2007). The black swan: The impact of the highly improbable (vol. 2). Random House.
  • Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124–1131.
  • Zhang, M., Ying, J., Song, G., Fung, D. S., & Smith, H. (2018). Attention and cognitive bias modification apps: Review of the literature and of commercially available apps. JMIR mHealth and uHealth6(5).

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