What Is Implicit Bias? | Definition & Examples

Implicit bias is a collection of associations and reactions that emerge automatically upon encountering an individual or group. We associate negative or positive stereotypes with certain groups and let these influence how we treat them rather than remaining neutral.

Example: Implicit bias
You are walking on a street at night and notice a figure wearing a hoodie coming your way. You immediately sense danger and try to cross the street. The other person pulls an object out of their pocket, and you start running because you think it’s a weapon. Looking back, you realise your mistake: the person was simply answering their phone.

This can lead to discriminatory behaviour in a wide range of contexts such as healthcare, the workplace, and education.

What is implicit bias?

Implicit bias is an unconscious preference for (or aversion to) a particular person or group. Although these feelings can be either positive or negative, they cause us to be unfair towards others. Affinity bias or the tendency to favor people who are similar to us, is an example of this unfair behaviour. However, any aspect of an individual’s identity, such as age, gender, or socioeconomic background, can be the target of implicit bias.

Under implicit bias, we are unaware that our biases (rather than objective facts) affect our decisions and judgments. For example, when most people hear the word “kindergarten teacher,” they are more likely to picture a female. This can happen without intention or awareness and may even contradict openly held beliefs. Because implicit bias is unconscious, it is difficult to acknowledge and control.

What causes implicit bias?

Implicit bias occurs due to unconscious mental processes. There are several factors at play in the development of implicit biases:

  • Our brains create categories. We have the natural tendency to assign everything we see into a category. Even though this happens unconsciously, after categorising things or people, we also assign a positive or negative association to them. Categories allow our brains to know what to do or how to behave. The downside of this is that classifications often cause us to overgeneralise.
  • We rely on mental shortcuts. Most of the time, we rely on “automatic” information processing that involves little conscious thought. This allows us to exert little mental effort in our everyday lives and make swift judgments.
  • Social and cultural influences. Our upbringing, social environment, and direct and indirect experiences with members of various social groups imprint on us. These shape our perception at a deeper level, even if we are not conscious of it.

Implicit vs. explicit bias

Both implicit and explicit bias involve judging others based on our assumptions rather than the situation or the facts at hand. However, they are actually quite different.

  • Implicit bias occurs when we have an inclination for or against a person or group that emerges automatically. In other words, our evaluation, positive or negative, is unintentional and beyond our conscious awareness.
  • Conversely, explicit bias refers to positive or negative attitudes that we are fully aware of. We openly express them and share them with others, because these attitudes are part of our worldview.

Despite their differences, implicit bias can be just as problematic as explicit bias because both may lead to discriminatory behaviour.

Implicit vs. explicit bias

Implicit bias examples

Implicit bias can lead to discriminatory behaviour when it comes to hiring a diverse workforce.

Example: Implicit bias and hiring decisions
Studies have shown that hiring managers who review resumes are more likely to skip those with African-American-sounding names on them.

In a field experiment measuring racial discrimination in the labor market, researchers responded to job ads in Boston and Chicago using fictitious resumes. To manipulate perception of race, each resume was assigned either an African-American-sounding name or a white-sounding name. The results showed significant discrimination against African-American names: applicants with white-sounding names received 50 percent more callbacks for interviews.

The amount of discrimination was uniform across occupations and industries. Additionally, federal contractors and employers who mentioned “Equal Opportunity Employer” in their ad discriminated as much as other employers.

The researchers concluded that there was little evidence that employers were trying to infer something other than race, such as social class, from the name.

These results suggest that implicit bias still runs rampant in the hiring process, despite employers’ declarations to the contrary.

What is the Harvard Implicit Bias Association Test (IAT)?

The Harvard Implicit Bias Association Test (IAT) is a computer-based assessment measuring the strength of associations between concepts or stereotypes to reveal an individual’s implicit or subconscious biases.

The idea behind IAT is that, while we can measure explicit bias by asking respondents directly about their views regarding something like gender roles, the same does not apply for implicit biases. When we want to measure hidden or implicit attitudes, we need to do so indirectly. Otherwise, respondents will not answer truthfully due to social desirability or a lack of awareness of their own biases.

There are different versions of the IAT, but it typically consists of five rounds. In each round, respondents need to quickly sort words (e.g., “parents”) into categories that are on the left- and right-hand side of the screen (e.g., “career” and “family”). The key assumption underlying any IAT is that the stronger the association a respondent has between two concepts, the faster they are to make these associations.

It is important to remember that, like most psychological measures, the IAT can’t predict how particular individuals will behave. IAT measures a “gut reaction,” not behavior, which may be a product of both implicit attitudes and explicit decision-making. However, the IAT is useful for predicting how groups will behave on average or at an organizational or city level. Metro areas with greater average implicit bias, for instance, have larger racial disparities in police shootings.

How to reduce implicit bias

Understanding implicit bias is critical because both positive and negative unconscious beliefs can lead to structural and systemic inequalities. However, because it operates outside our awareness, if we want to reduce it, we first need to become conscious of it. The following strategies can be helpful:

  • Taking the IAT can help you realise that everyone, including you, has implicit biases. Recognising them for what they are increases the likelihood that next time you won’t let these hidden biases affect your behaviour.
  • Positive intergroup contact. Unconscious bias towards a particular group can be reduced through interaction with members of that group. For example, you can make it a point to engage in activities that include individuals from diverse backgrounds.
  • Counter-stereotyping. Exposure to information that defies stereotypes that persist about groups or individuals, such as images of female scientists, can counter gender stereotypes.
  • Implicit bias training. Although raising awareness is important, it’s not enough. The most successful training programs are ones that allow individuals to discover their biases in a non-confrontational manner and also give them the tools to reduce and manage their biases.

Other types of research bias

Frequently asked questions about implicit bias

Is bias positive or negative?

Bias can be either positive or negative. However, all forms of bias (whether favorable or unfavorable) prevent us from judging others fairly.

For example, because of explicit bias, a teacher might openly claim that students from a certain ethnic background are exceptionally good in math. Even though this sounds positive, it means that other students are automatically treated as second-rate. For this reason, bias is linked to unfairness and thus has a negative connotation.

What are the two main types of bias?

There are two main types of bias:

Implicit bias is the positive or negative attitudes, feelings, and stereotypes we maintain about members of a certain group without us being consciously aware of them.

Explicit bias is the positive or negative attitudes, feelings, and stereotypes we maintain about others while being consciously aware of them.

What is bias?

Bias is a systematic error in the design, administration, or analysis of a study. Because of bias, study results deviate from their true value and researchers draw erroneous conclusions.

There are several types of bias and different research designs or fields are susceptible to different types of research bias. For example, in health research, bias arises from two main sources:

  • The approach adopted for selecting study participants
  • The approach adopted for collecting or measuring data

These are, respectively, selection bias and information bias.

What is the opposite of implicit bias?

The opposite of implicit bias is explicit bias, or conscious bias. This refers to preferences, opinions, and attitudes of which people are generally consciously aware. In other words, explicit bias is expressed openly and deliberately.

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, December 18). What Is Implicit Bias? | Definition & Examples. Scribbr. Retrieved June 11, 2024, from https://www.scribbr.com/research-bias/implicit-bias/


Bertrand, M., & Mullainathan, S. (2004). Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination. American Economic Review, 94(4), 991–1013. https://doi.org/10.1257/0002828042002561

Daumeyer, N. M., Onyeador, I. N., Brown, X., & Richeson, J. A. (2019). Consequences of attributing discrimination to implicit vs. explicit bias. Journal of Experimental Social Psychology, 84, 103812. https://doi.org/10.1016/j.jesp.2019.04.010

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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.