What Is Normalcy Bias? | Definition & Example

Normalcy bias is the tendency to underestimate the likelihood or impact of a negative event. Normalcy bias prevents us from understanding the possibility or the seriousness of a crisis or a natural disaster.

Example: Normalcy bias
Officials issue a hurricane warning in your area, advising everyone to evacuate their homes. On your way out, you run into your neighbor, who has no intention of leaving because they believe it is “just another storm.” Their conviction that it’s not going to be that bad and their refusal to heed the warnings are signs of normalcy bias.

Because normalcy bias can lead us to believe that nothing serious is going to happen, we may not take appropriate or adequate preparations for a crisis and might put ourselves at risk.

What is normalcy bias?

Normalcy bias (or normality bias) is a cognitive bias that occurs in times of crisis, leading us to disregard any signs or warnings that we are in danger. Even when we are advised on what to do, we may downplay the possibility of something bad happening to us or disregard how disruptive a disaster might actually be. As a result, we often fail to take preventive measures or cope with the situation effectively.

Under normalcy bias, people exhibit denial or disbelief, even in the face of imminent danger. Phrases like “that won’t happen here” or “it won’t be that bad” are signs of normalcy bias. Although we may think that people will start running in response to danger (as they would in the movies), in reality people may react with a delay—or not react at all. Normalcy bias is a defense mechanism that lulls us into thinking life will just continue as it always has.

What causes normalcy bias?

Normalcy bias is a complex phenomenon that occurs as a result of several different factors.

Attachment to current beliefs

Crisis communication sometimes requires people to do something that seems counterintuitive, such as evacuating their homes even when the weather seems fine. Changing our beliefs during an emergency may be difficult due to confirmation bias: we tend to interpret ambiguous messages in a way consistent with our beliefs. For example, experts may advise us to evacuate unsafe locations and take shelter in stronger buildings, but if we are convinced that our house is a safe place, we can easily misinterpret the recommendation and stay put.

Need for information

The delay associated with normalcy bias is often disguised as a need for more information. This makes sense because when people are not well informed about a potential danger, they cannot fully understand the consequences. However, even when a clear warning has been issued, people often stall, trying to confirm the warning and relay it to others (this phenomenon is called “milling” in psychology). People in emergency situations usually ask four people on average what’s going on and what they should do prior to taking any action.

Social influence

People turn to others for cues about what is considered appropriate behavior or the right response in a situation. If others around us are not taking potential risks seriously, we are likely to follow their example. Nobody wants to be perceived as alarmist or overreactive if it turns out to be a false alarm. In other words, conformity bias may reinforce normalcy bias.

Resistance to change

Threats represent a change in our environment. Our natural tendency is to resist change and to believe that life will continue as it is. This resistance is a normal response and can occur even during the initial phase of stressful events. We become so accustomed to our everyday normal life that we are optimistic that things will continue as they are. This makes it hard for us to register and deal with impending disasters.

Why does normalcy bias matter?

Normalcy bias can prove dangerous because it prevents us from preparing for a threat, like a tsunami. On a wider scale, normalcy bias can lead to government failure to prepare for an impending disaster, at the cost of human lives.

Under normalcy bias, people find it hard to cope with a disaster as it unfolds, especially if they have never experienced a catastrophic event before. This may cause them to disregard official information, interpret any warning signs in an optimistic way, and insist that things are not as bad as they look.

Normalcy bias example

Normalcy bias can help explain why people fail to change their behavior during a crisis, even though they are instructed on what to do.

Example: Normalcy bias and COVID-19
In the early days of the pandemic, although the authorities urged people to practice social distancing, many people continued living their lives as usual: media footage showed crowded bars and beaches and indicated that many people were acting like there was no crisis.

The fact that this was an invisible threat made things worse: many people didn’t know anyone with an infection or hadn’t seen anyone seriously ill. Due to this, they thought COVID wasn’t much of a threat and that it wouldn’t affect them personally. They “normalized” an unusual situation and carried on with their everyday routines, even when urged to take precautions. This was normalcy bias at work.

Although governments usually worry that people will panic during a crisis, research has shown that people tend to do the opposite: they carry on as though nothing new is happening.

Other types of research bias

Frequently asked questions about normalcy bias

What is the difference between normalcy bias and optimism bias?

Normalcy bias and optimism bias are closely related as they both influence our risk perception. However, they are two separate phenomena.

  • Normalcy bias denotes our tendency to minimize or ignore threat warnings and to believe that nothing can seriously disrupt our everyday life.
  • Optimism bias, on the other hand, denotes the tendency to overestimate the likelihood of positive events and underestimate the likelihood of negative events.

Although normalcy bias and optimism bias are distinct types of bias, they may reinforce each other. For instance, an individual who receives a hurricane alert may underestimate how serious it is (normalcy bias) and may also think that even if the hurricane affects their area, nothing bad will happen to them personally (optimism bias).

What is the opposite of normalcy bias?

The opposite of normalcy bias is overreaction or worst-case scenario bias. This happens when people exaggerate the likelihood of negative outcomes or consequences when faced with a threat warning. In other words, people jump to the worst possible conclusion, no matter how improbable it is. For instance panic-buying of toilet paper, face masks, and food in the early days of the COVID-19 outbreak are examples of overreaction.

What is normality bias?

Normality bias (or normalcy bias) is the tendency to underestimate the likelihood or impact of a potential hazard, based on the belief that things will continue as they have in the past. For example, you hear a sudden noise and think it must be fireworks. However, in reality it’s a gunshot. Instead of finding a safe spot, you go about your business because your brain “normalizes” the noise.

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 24). What Is Normalcy Bias? | Definition & Example. Scribbr. Retrieved July 18, 2024, from https://www.scribbr.com/research-bias/normalcy-bias/


Murata, A., Nakamura, T., & Karwowski, W. (2015). Influence of cognitive biases in distorting decision making and leading to critical unfavorable incidents. Safety, 1(1), 44–58. http://dx.doi.org/10.3390/safety1010044

Ross, C. (2020). Covid-19 pandemic from a “normalcy bias” approach. Journal of Community & Public Health Nursing, 6(242). https://www.omicsonline.org/open-access/covid19-pandemic-from-a-normalcy-bias-approach-112064.html

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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.