Why do we overestimate the probability of success?


Optimism Bias

, explained.

What is Optimism Bias?

The optimism bias refers to our tendency to overestimate our likelihood of experiencing positive events and underestimate our likelihood of experiencing negative events.

Optimism bias

Where this bias occurs

Consider the following scenario: Tom is a bright and motivated entrepreneur who is in the midst of starting his own restaurant. Previously, six businesses failed in the same building he purchased. Each venture fell short of earning the necessary returns to stay afloat and was forced to close. However, Tom feels as though he has what it takes to make his restaurant a success. After all, he graduated at the top of his class, is overflowing with big ideas, and is in touch with the pulse of young city-goers.

Tom pours his time and money into the venture, refusing to yield to shortcomings or accept failure as an option. His friend warns him that the street layout and surrounding competition make it difficult to draw pedestrians into the area. Tom still feels he can overcome these obstacles with his expertise. However, Tom’s restaurant fails to sustain enough business and is unfortunately forced to shut down—just like the rest before him. 

In this scenario, Tom exhibits the optimism bias because he refuses to take into consideration the past six businesses that failed before him as well as the environmental factors working against him. However, Tom confidently believes he can outperform the rest because of his abilities as an entrepreneur. But at the end of the day, his likelihood of failing is statistically the same as everyone else's, resulting in his inevitable failure.

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Individual effects

Research consistently supports that the overwhelming majority of us exhibit a bias toward optimism.1 However, as in Tom’s case, there can be high costs to overestimating our success in our personal and professional lives. 

For example, we assume that we can complete projects in shorter amounts of time than is actually possible. We assume that our relationships will last longer than they realistically might. We assume that we will make more money than others. And the list goes on and on.

The optimism bias can also encourage risky behaviors like smoking by causing us to ignore the potential of unwanted outcomes.2 On top of this, assuming we will be successful stops us from taking preventative measures, like buying insurance or using contraceptives.

Of course, it is necessary to have some optimism. This way, we can persevere even in the face of hardship or rejection. Sometimes we need to believe in our own abilities, even if no one else does. Plus, it can be too hard to take a step forward if we become too preoccupied with our potential downfall. But as a general rule of thumb, it is important to be aware of how our optimism blinds us to negative outcomes and results in making poor decisions.

Systemic effects

Our overoptimism aggregates into exponentially devastating results. This systematic failure results from two cognitive tendencies. First, we tend to focus on things we are looking forward to rather than negative events. Second, we tend to anticipate bad things that may happen to others but not ourselves. Together, these tendencies inspire us to seek personal rewards without acknowledging the negative impact they might have on the entire system—including ourselves.

Take the stock market for example. Cognitive neuroscientist Tali Sharot proposes that “one of the core causes of the financial downfall in 2008” was the optimism bias.3 Analysts and investors alike had unrealistic expectations of financial growth and success. Banks continued to make high-risk decisions which contributed to the inflating economic bubble, along with its ultimate crash. If these contributors had stopped to consider the systematic consequences of their failure, perhaps they would have thought twice before making risky bargains.

The optimism bias also thwarts our global response to climate change.4 We persistently use products that pollute natural habitats or emit carbon dioxide, assuming the impending disaster will not affect us personally. In particular, environmental psychologist Sabin Pahl and her colleagues discovered that for climate skeptics, optimism results in “less guilt, less perceived responsibility, and lower behavioral intentions”.5  We forget that if we each continue to act so carelessly, we will never be able to join together and take necessary action to save our planet. And we will also have to face the consequences. 

How it affects product

Imagine you need to download a specific song for a video you are editing on your laptop. Rather than paying a couple of dollars to gain secure access, you decide to download it off a sketchy website for free instead. You figure this should work out fine, since you have pirated plenty of free movies and music before and never run into any issues. A couple hours later, you’re shocked to find your laptop glitching out from all of its new viruses.

This anecdote demonstrates how the optimism bias threatens our cybersecurity. We only foresee the positive outcomes of our online activities, like downloading a song for free, and not the negative outcomes, like getting a virus. Our skewed perception deters us from taking important security measures, such as downloading antivirus software or backing up our data regularly. 

The same thing goes for buying the digital products themselves. We often purchase expensive laptops or smartphones without any warranty or insurance, assuming that they will not be damaged or stolen. Little do we realize that we are not in control of these circumstances! 

To avoid letting the optimism bias get the better of us, we should always make sure to have extra security measures in place to protect our digital activity. By expecting the unexpected, we will be ready for whatever viruses might come our way.

The optimism bias and AI

Smart homes enhance our environments by taking over what we once considered human tasks, such as adjusting the temperature or turning on and off lights. This automation helps us optimize our daily routines and build better energy consumption habits.

However, the optimism bias may encourage unrealistic expectations for how easily we can incorporate smart homes into our real homes. For example, we may assume home speakers will understand every command perfectly, regardless of pronunciation or background noise. We also may assume that the machine learning algorithms will continuously learn our habits at a rate that even computers cannot live up to. All of these frustrations might actually make it more difficult to perform what we once considered simple tasks, like flicking a light switch.

Smart homes are smart — but they aren’t geniuses quite yet. Make sure to have a good understanding of how these devices work to ease yourself into this adjustment period, rather than screaming aimlessly at the speaker.

Why it happens

In order to understand the optimism bias, it is important to understand where it comes from and why. By breaking down biases into their cognitive processes and exploring their benefits and harms, we have a better chance of learning how to avoid making bad decisions.

The optimism bias instills feelings of control. We generally want influence over our lives and our fates. Negative events like illness, divorce, or financial loss often threaten our plans or derail our predictions. Optimism prevents us from lingering too long in these possible negative outcomes.

The optimism bias has evolutionarily adaptive functions

Many human traits have adaptive functions that can be traced back to our primitive evolutionary environment. If a trait promoted survival and furthered chances of reproduction, it would continue to be passed onto offspring. 

It might seem as though a realist might be more successful at surviving than an optimist, yet optimism possesses a clear functional benefit. Economists Aviad Heifetz and Yossi Spiegel simulated interactions in an evolutionary environment between participants with different degrees of optimism.6 They concluded that when an optimist and a pessimist are in conflict, the optimist dominates their interaction. Their optimism c bias helps them to be aggressive and ultimately win the disagreement.

Another area in which the optimism bias is adaptive is physical and mental health. Quantitative data reveals that the optimism bias is positively associated with low levels of depression.7 As chronic stress can take a physical toll on our bodies by overworking our nervous systems, the optimism bias is associated with physical health as well. Additionally, optimism encourages healthy eating and exercise.8 If we focus more on the benefits of healthy habits (such as stronger muscles, better immune system, and improved mood), we are likely to meet our fitness goals.

We adjust our beliefs in response to positive occurrences

So how do we stay optimistic in the face of information that tells us our beliefs are false? To investigate this question, Sharot and her colleagues performed a study where they asked participants to “estimate their likelihood of encountering different adverse life events (such as Alzheimer’s disease and burglary).”9 After estimating, participants were given the statistical likelihood of these events and then asked to recalibrate their personal likelihood accordingly. 

The researchers found that if a participant’s initial estimate was lower than the true likelihood, their revised estimate would barely change. However, if a participant’s initial estimate was higher than the true likelihood, their revised estimate would go down a large amount. For example, if the subject said they were 10% likely to get cancer and the true statistic was 25%, their answer would stay almost the same. But, if the subject said they were 20% likely to get robbed and the true statistic was 10%, they might lower their answer to 5%.

With this information, Sharot concluded that we have the tendency to update our beliefs regarding positive information much more than we do with negative information. Through selectively calibrating our expectations with positive events, we can maintain optimism even in the face of negativity.

Why it is important

All of us are susceptible to the optimism bias, no matter how much of an expert we are. In situations where we have a lot at stake surrounding our success, the optimism bias can cause us to ignore important information that can make or break our outcome. 

It is necessary to have some optimism to achieve our goals. However, the fate of our projects, our businesses, our economy, and our planet will be put at risk if we continue moving forward without making necessary changes. We must recognize when our optimism clouds our judgment—and luckily, there are tangible ways to do so.

How to avoid it

Nobel Prize-winning economist Daniel Kahneman proposes two different ways of mitigating its influence on our decision making: taking an outside view and a post mortem approach.10

Seeing scenarios from an outsider’s perspective

The optimism bias often causes us to overestimate our abilities or our control over our environment. We can all relate to what Kahneman labels the planning fallacy, where we assume that we will finish something much quicker than we actually do. He suggests combatting this tendency by picturing ourselves outside of the scenario and looking for “base rates.” 

Base rates are existing statistics from relevant situations that provide quantitative data to anchor our judgements. This includes the probability of an event occurring, the average amount of time something takes, or whatever figure fits the current situation—as long as the base rate is from existing data. Kahneman proposes taking an outside perspective through the following three steps:

  1. “Identify an appropriate reference class” – Look for a general category to put your task in. This could be grocery shopping, home remodeling, or a professional project.
  2. “Obtain statistics for this reference class” – Look for statistics on how long it takes to complete the type of task on average. These are your “base rates”
  3. “Use specific information about the case to adjust the baseline prediction” – If there are specific details you think are worth changing your predictions for, use your judgment to make the necessary adjustments.

While these steps apply most directly to planning time management, base rates can be a great tool for grounding your expectations in reality and combating the optimism bias once and for all.

Start at the end

Kahneman suggests the “premortem approach” as a tool for organizations to overcome the optimism bias. The premortem approach is an exercise for teams to predict potential areas of failure when beginning a project. Everyone on the team is instructed to imagine it is a year from the present and the project has failed. They are then instructed to write out what has gone wrong and why. By forcing our team members to consider negative outcomes, we can resist being shortsighted by our overconfidence and increase our chances of a successful project.

How it all started

The optimism bias was first encountered in 1980 by psychologist Neil Weinstein, although he then labeled it “unrealistic optimism”.11 Weinstein conducted an experiment with over 200 college students testing the following hypothesis:

“People believe that negative events are less likely to happen to them than to others, and they believe that positive events are more likely to happen to them than to others.”

He tested this by asking students to rate how much their chances of experiencing a certain event differed from their classmates. If over half rated themselves below average for a negative event or above average for a positive event, it would serve as evidence for a widespread optimism bias.

Weinstein’s results supported his hypothesis. There were varying magnitudes for different questions, yet the overall conclusion was strong: we overestimate our chances of achieving things we want and underestimate our chances of experiencing misfortune.

Weinstein posited that there were both cognitive and motivational explanations for these results. His cognitive explanation was that optimism is a mental protector from anxiety or constant distress about the future. His motivational explanation was that optimism served as an indicator of one’s desire to achieve or avoid certain outcomes, pushing individuals to act accordingly.

Example 1 – Clinical research

In clinical research, the optimism bias can lead to unwarranted belief in the efficacy of new therapies. For example, clinical papers tend to cite successful research and underrepresented research proving a treatment ineffective. Health science researchers Iaian Chalmers and Robert Matthews also suggest that the optimism bias causes researchers to selectively report results that shine a positive light on treatments, as well as the “early stopping of studies” that might have negative results.12 This is a dangerous trend because biased results give patients and doctors unrealistic health expectations when starting new protocols.

In their paper, Chalmers and Matthews discuss a study in 1990 that tested a new radiotherapy treatment for head and neck cancer. They surveyed clinicians on their expected outcomes. The clinicians unanimously believed there would be a reduced mortality rate of 30%. However, the results of the trial showed no evidence for a reduced mortality rate. Here we can see how the optimism bias can affect clinical research and lead to poor predictions, even in experts.

On the production side, corporate-funded research has been found to encourage optimism bias more-so than publicly funded research.13 As individuals, it is important to be wary of our own optimism bias, as well as the research industry’s optimism bias, when participating in medical research.

Example 2 – Student debt accumulation

We love daydreaming about a debt-free future. Consequently, we might underestimate how long it will take to pay off our student loans. Psychology researchers Hamish Seaward and Simon Kemp conducted a study to investigate the rise in student debts in New Zealand.14

Seaward and Kemp interviewed over 200 psychology students on their expectations surrounding post-graduation incomes, debts, and pay-back period. They found that the students, on average, expected to pay back their loans in 10 years, even though government statistics revealed it often took considerably more time. Additionally, students assessed their chances of getting high-paying jobs as much more than their classmates, with no real reason as to why.

Through analysis of these results, Seaward and Kemp suggested that the optimism bias causes students to take on more student loans, since students expect higher incomes after graduation than they actually receive.


What it is

The optimism bias refers to our tendency to overestimate our chances of positive experiences and underestimate our chances of negative experiences. This can cause overconfidence in our personal lives and professional ventures. The optimism bias also contributes to global issues such as the 2008 market crash and failure to act against climate change.

Why it happens

The optimism bias is evolutionarily adaptive because it provides us motivation to come out on top of our competitors. However, optimism gives us a false sense of control over our environment and pushes us to make unrealistic goals. We maintain unrealistic optimism even when the world tells us otherwise because we update our beliefs when we are exposed to positive events more than with negative events.

Example 1 – How the optimism bias can affect clinical research

Clinical research, especially when private-sponsored, succumbs to the optimism bias by failing to cite negative trial results. This causes clinicians and patients to have unrealistic expectations about the efficacy of new treatments.

Example 2 – How the optimism bias contributes to the accumulation of student debt

A study by Seaward and Kemp demonstrated that New Zealand college students had considerably high expectations for their post-graduate incomes, and low expectations for the length of time it would take to pay off their debt. They posit that this optimism bias contributes to students amassing loans.

How to avoid it

Kahneman suggests two approaches to combating the optimism bias. One approach is to take an outside view, meaning we should look at base rates to make estimates as if we are looking at someone else’s chances. Another approach for organizations is the premortem approach, where team members predict how a project could fail and then work backward to prevent these issues.

Related TDL Articles

Why do we underestimate how long it will take to complete a task?

As discussed above, the optimism bias can lead to the planning fallacy, where we drastically underestimate how long it will take us to complete a task. Read this article to learn more about what the planning fallacy is, why it happens, and some examples in your everyday life.

Why do we think we're destined to fail?

While the optimism bias makes us think we’re destined for success, the pessimism bias makes us think we’re destined for failure. Read this article to better understand how these biases coexist, and which situations we might expect to experience each of them in.


  1. Sharot, T. (2011). The optimism bias. Current Biology, 21(23), R941–R945. https://doi.org/10.1016/j.cub.2011.10.030
  2. Ibid.
  3. Ibid.
  4. Pahl, S., Sheppard, S., Boomsma, C., & Groves, C. (2014). Perceptions of time in relation to climate change. WIREs Climate Change, 5(3), 375–388. https://doi.org/10.1002/wcc.272
  5. Ibid.
  6. Heifetz, A., & Spiegel, Y. (2000). On the Evolutionary Emergence of Optimism (SSRN Scholarly Paper ID 247355). Social Science Research Network. https://doi.org/10.2139/ssrn.247355
  7. Strunk, D. R., Lopez, H., & DeRubeis, R. J. (2006). Depressive symptoms are associated with unrealistic negative predictions of future life events. Behaviour Research and Therapy, 44(6), 861–882. https://doi.org/10.1016/j.brat.2005.07.001
  8. Sharot, 2011.
  9. Sharot, 2011.
  10. Kahneman, D. (2013). Thinking, Fast and Slow (1st Edition). Farrar, Straus and Giroux.
  11. Weinstein, N. D. (1980). Unrealistic optimism about future life events. Journal of Personality and Social Psychology, 39(5), 806–820. https://doi.org/10.1037/0022-3514.39.5.806
  12. Chalmers, I., & Matthews, R. (2006). What are the implications of optimism bias in clinical research? The Lancet, 367(9509), 449–450. https://doi.org/10.1016/S0140-6736(06)68153-1
  13. Ibid.
  14.  Seaward, H. G. W., & Kemp, S. (2000). Optimism bias and student debt. New Zealand Journal of Psychology; Christchurch, 29(1), 17.

About the Authors

Dan Pilat's portrait

Dan Pilat

Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.

Sekoul Krastev's portrait

Dr. Sekoul Krastev

Sekoul is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. A decision scientist with a PhD in Decision Neuroscience from McGill University, Sekoul's work has been featured in peer-reviewed journals and has been presented at conferences around the world. Sekoul previously advised management on innovation and engagement strategy at The Boston Consulting Group as well as on online media strategy at Google. He has a deep interest in the applications of behavioral science to new technology and has published on these topics in places such as the Huffington Post and Strategy & Business.

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