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Normalcy bias

Normalcy bias is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Normalcy bias rather than just read about it. In short: Normalcy bias, or normality bias, is a cognitive bias which leads people to disbelieve or minimize threat warnings. Consequently, individuals underestimate the likelihood of a disaster, when it might affect them, and its potential adverse effects.

Normalcy bias — main illustration
Normalcy bias — illustration

Key takeaways

  • Normalcy bias belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Normalcy bias to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Normalcy bias from memory before moving on to harder problems.

Reference excerpt

Normalcy bias, or normality bias, is a cognitive bias which leads people to disbelieve or minimize threat warnings. Consequently, individuals underestimate the likelihood of a disaster, when it might affect them, and its potential adverse effects. The normalcy bias causes many people to prepare inadequately for natural disasters, market crashes, and calamities caused by human error. About 80% of people reportedly display normalcy bias during a disaster. The normalcy bias can manifest in response to warnings about disasters and actual catastrophes. Such events can range in scale from incidents such as traffic collisions to global catastrophic risk. The event may involve socially constructed phenomena such as loss of money in market crashes, or direct threats to continuity of life: as in natural disasters like a tsunami or violence in war. Normalcy bias has also been called analysis paralysis, the ostrich effect, and by first responders, the negative panic. The opposite of normalcy bias is overreaction, or worst-case scenario bias, in which small deviations from normality are dealt with as signals of an impending catastrophe.

Phases Amanda Ripley, author of The Unthinkable: Who Survives When Disaster Strikes – and Why, identifies common response patterns of people in disasters and explains that there are three phases of response: "denial, deliberation, and the decisive moment". With regard to the first phase, described as "denial", Ripley found that people were likely to deny that a disaster was happening. It takes time for the brain to process information and recognize that a disaster is a threat. In the "deliberation" phase, people have to decide what to do. If a person does not have a plan in place, this causes a serious problem because the effects of life-threatening stress on the body (e.g. tunnel vision, audio exclusion, time dilations, out-of-body experiences, or reduced motor skills) limit an individual's ability to perceive information and make plans. Ripley asserts that in the third and final phase, described as the "decisive moment", a person must act quickly and decisively. Failure to do so can result in injury or death. She explains that the faster someone can get through the denial and deliberation phases, the quicker they will reach the decisive moment and begin to take action.

Examples

Journalist David McRaney wrote that "Normalcy bias flows into the brain no matter the scale of the problem. It will appear whether you have days and plenty of warning or are blindsided with only seconds between life and death." It can manifest itself in phenomena such as car crashes. Car crashes occur very frequently, but the average individual experiences them only rarely, if ever. It also manifests itself in connection with events in world history. According to a 2001 study by sociologist Thomas Drabek, when people are asked to leave in anticipation of a disaster, most check with four or more sources of information before deciding what to do. The process of checking in, known as milling, is common in disasters. It can explain why thousands of people refused to leave New Orleans as Hurricane Katrina approached and why at least 70% of 9/11 survivors spoke with others before evacuating. Officials at the White Star Line made insufficient preparations to evacuate passengers on the Titanic and people refused evacuation orders, possibly because they underestimated the odds of a worst-case scenario and minimized its potential impact. Similarly, experts connected with the Fukushima nuclear power plant were strongly convinced that a multiple reactor meltdown could never occur. A website for police officers has noted that members of that profession have "all seen videos of officers who were injured or killed while dealing with an ambiguous situation, like the old one of a father with his young daughter on a traffic stop". In the video referred to, "the officer misses multiple threat cues...because the assailant talks lovingly about his daughter and jokes about how packed his minivan is. The officer only seems to react to the positive interactions, while seeming to ignore the negative signals. It's almost as if the officer is thinking, 'Well I've never been brutally assaulted before so it certainly won't happen now.' No one is surprised at the end of the video when the officer is violently attacked, unable to put up an effective defense." This professional failure, notes the website, is a consequence of normalcy bias. Normalcy bias, David McRaney has written, "is often factored into fatality predictions in everything from ship sinkings to stadium evacuations". Disaster movies, he adds, "get it all wrong. When you and others are warned of danger, you don't evacuate immediately while screaming and flailing your arms." McRaney notes that in the book Big Weather, tornado chaser Mark Svenvold discusses "how contagious normalcy bias can be. He recalled how people often tried to convince him to chill out while fleeing from impending doom. Even when tornado warnings were issued, people assumed it was someone else's problem. Stake-holding peers, he said, would try to shame him into denial so they could remain calm. They didn't want him deflating their attempts at feeling normal".

Hypothesized cause The normalcy bias may be caused in part by the way the brain processes new data. Research suggests that even when the brain is calm, it takes 8–10 seconds to process new information. Stress slows the process, and when the brain cannot find an acceptable response to a situation, it fixates on a single and sometimes default solution that may or may not be correct. An evolutionary reason for this response could be that paralysis gives an animal a better chance of surviving an attack and predators are less likely to see prey that is not moving.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Normalcy bias

Start with the simplest possible case. Write down what Normalcy bias claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Normalcy bias before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Normalcy bias ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Normalcy bias

In research
Normalcy bias appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Normalcy bias in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Normalcy bias is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cognitive biases, Disaster preparedness, Emergency management, so understanding it makes those chapters shorter.
In everyday life
Look for Normalcy bias outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Normalcy bias in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Normalcy bias means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Normalcy bias out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Normalcy bias in simple terms?

Normalcy bias, or normality bias, is a cognitive bias which leads people to disbelieve or minimize threat warnings. Consequently, individuals underestimate the likelihood of a disaster, when it might affect them, and its potential adverse effects.

Why does Normalcy bias matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Normalcy bias?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Normalcy bias.

Tags

  • Cognitive biases
  • Disaster preparedness
  • Emergency management

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