What Is The Outcome Bias? The Outcome Bias In A Nutshell

Outcome bias describes a tendency to evaluate a decision based on its outcome and not on the process by which the decision was reached. In other words, the quality of a decision is only determined once the outcome is known. Outcome bias occurs when a decision is based on the outcome of previous events without regard for how those events developed.

Outcome BiasOutcome bias is a cognitive bias that occurs when the evaluation of a decision or action is based on the outcome or result, rather than the quality of the decision-making process. In other words, it involves judging the wisdom of a choice based on how things turned out, rather than whether the decision was reasonable given the information available at the time. Outcome bias can lead to unfair assessments of decisions and can hinder learning and improvement.
Key ConceptsJudging Decisions by Outcomes: Outcome bias involves the tendency to judge the quality of a decision or action based on whether it led to a positive or negative result. – Hindsight Bias: It is closely related to hindsight bias, where individuals believe that events were predictable after they have occurred. – Risk and Uncertainty: Outcome bias is often influenced by the level of risk and uncertainty associated with a decision.
ExamplesInvestment Decisions: An investment manager may be praised for a risky investment that happened to yield high returns but criticized for a similarly risky investment that resulted in losses. – Medical Diagnoses: A doctor’s diagnosis may be viewed as competent if a patient recovers, even if the diagnosis was based on uncertain symptoms.
Effect on Decision-MakingRisk Aversion: The fear of negative outcomes due to outcome bias can lead individuals to become risk-averse and avoid making decisions with uncertain outcomes. – Inhibition of Innovation: In organizations, outcome bias can discourage innovation and experimentation, as individuals fear negative repercussions for unsuccessful ventures.
MitigationFocus on Process, Not Just Outcomes: To mitigate outcome bias, it’s essential to evaluate decisions based on the quality of the decision-making process, including the information available and the reasoning behind the choice. – Encourage Learning: Creating a culture that encourages learning from both successes and failures can help mitigate the negative effects of outcome bias.
Cognitive BiasesOutcome bias is related to several other cognitive biases, including: – Confirmation Bias: The tendency to search for, interpret, and remember information that confirms one’s preconceptions. – Hindsight Bias: The belief that events were predictable after they have already occurred. – Overconfidence Bias: The tendency to overestimate one’s own abilities and the accuracy of one’s beliefs.
ApplicationsLegal System: Outcome bias can influence legal judgments, where the outcome of a case can disproportionately affect perceptions of the fairness of a legal decision. – Performance Evaluation: In the workplace, employees may be evaluated based on the success or failure of specific projects, rather than on their competence and effort.
ImplicationsFairness: Outcome bias can lead to unfair evaluations of decisions and actions, as individuals are often not in control of external factors that influence outcomes. – Innovation and Risk-Taking: Organizations may discourage innovation and risk-taking if they excessively punish failures without considering the decision-making process.
Learning and ImprovementTo promote learning and improvement while mitigating outcome bias: – Encourage a culture of transparency, where individuals feel safe admitting mistakes. – Emphasize the importance of reviewing and learning from both successful and unsuccessful outcomes. – Focus on the decision-making process and the factors that were within an individual’s control.
ConclusionOutcome bias is a cognitive bias that can significantly impact decision-making, fairness, and learning. By recognizing its presence and taking steps to mitigate its effects, individuals and organizations can make more informed and fairer evaluations of decisions, fostering a culture of continuous improvement and innovation.

Understanding outcome bias

Outcome bias is common in humans because we tend to be self-evaluative.

We tend to look back at what we’ve done and use any lessons learned to measure our future performance.

This can be a useful trait in some circumstances, but it can also be a problem when something bad happens.

When a decision results in a poor outcome, we tend to place more importance on the outcome of a decision.

We may be overly self-critical or indeed critical of others when compared to instances where a decision resulted in a positive outcome.

It does not matter if the decision-making process was well considered or if the likelihood of success was down to chance.

This is not to say that outcome bias does not occur when there is a favorable outcome.

Consider an individual who decides to invest in real estate after learning that a friend made a significant capital gain.

Outcome bias causes the individual to become preoccupied with how much money was made and in the process, ignore the mechanisms behind their friend’s success.

Perhaps a government stimulus package for new home builders was a contributing factor, or maybe a combination of low-interest rates and a knack for identifying undervalued property was the cause.

The outcome bias in business

In business, an overemphasis on performance is creating an outcome-centric culture in which someone must lose in order for someone else to win.

As a result, outcome bias is present in many performance-related situations including:


A hiring manager is only considered successful if the employee they recruit performs well.

With less emphasis on the reasoned and fair recruitment process, employees are led to believe that they are either good at their job or bad at their job.

When evaluations are based on a binary result and not on the quality of an employee’s decision-making, good luck is rewarded over competence or expertise.

Product development

Product management has become a key role within most organizations and startups as it combines product development with experimentation to create a successful product in the market. Product management requires a combination of strategic thinking, problem-solving skills, and a relentless focus on customer needs and delivering the right product at the right time. Top product managers use a customer obsession approach to build and launch successful products.

Products are judged according to how well they were received in the market, rather than the product development-related processes and systems that made the product a reality in the first place.


Once an outcome is known, the outcome bias also hinders our ability to evaluate whether a leadership decision was good or bad.

Fearful of negative repercussions, outcome bias can make some leaders risk-averse.

Conversely, irresponsible leaders who make reckless decisions are rewarded if their decision results in a positive outcome.

In this case, the subordinates who doubted the leader’s ability may be subject to harsh treatment from others.

Avoiding outcome bias

Critical thinking is one way of avoiding outcome bias. Instead of focusing on outcomes, we need to focus on the process as a whole. 

Like many cognitive biases, however, outcome bias can be difficult to address on our own.

We may sabotage ourselves by quitting too early or ignoring certain information we don’t like.

In this situation, it can be helpful to collaborate with a colleague or superior to understand the underlying causes of the bias.

In any case, consider these questions:

  • What led us to make the decision?
  • Was there a better process we could have followed in making the decision?
  • Could we have liaised with other people?
  • What information did we have at our disposal? What information did we not have?
  • Could we have obtained more data?
  • Was it necessary to decide at the point the decision was made?
  • Were there previously unknown external factors that may have skewed the decision?

Outcome bias and hindsight bias

As we saw, outcome bias can be pretty tricky.

Indeed, in the current business world, where we all claim to be looking at results, it can be very easy to fall into the trap of overestimating the outcome toward understanding whether the process makes sense in the first place.

The combination of the outcome bias with other fallacies might lead to a complete misjudgment of business events.

Indeed, when judging for outcomes, it’s critical not to fall into the hindsight bias.

Hindsight bias is the tendency for people to perceive past events as more predictable than they actually were. The result of a presidential election, for example, seems more obvious when the winner is announced. The same can also be said for the avid sports fan who predicted the correct outcome of a match regardless of whether their team won or lost. Hindsight bias, therefore, is the tendency for an individual to convince themselves that they accurately predicted an event before it happened.

This can lead to underestimating, for instance, the outcome of business events by overestimating our own ability to predict the future based on the past.

In short, take the case of a classic example in business, where a product like the BlackBerry phone was overtaken by the iPhone.

While in hindsight, it’s very easy to perform all analyses and conclude that it was clear that the iPhone was on a path to disrupt the BlackBerry.

That is a huge fallacy as if you were living in the moment, the real world was way more ambiguous, opaque and noisy than we like to admit.

In this specific case, we fall into the trap of overestimating our ability to analyze the past and underestimate the ability of BlackBerry’s management team (of the time) to respond to the threat of the iPhone!

We might want to call it also “the analyst bias” or the belief that you can look at past events with today’s understanding of them.

That, in turn, might lead to overestimating one’s ability to predict the future while underestimating other people’s ability to do the same.

Thus, it’s critical to balance out this bias by looking at the past and understanding that, while things could have been done differently, it’s also hard to predict future events based on what’s happening now.

As the real world is extremely noisy, opaque, and non-linear.

In the case of the iPhone, for instance, it might be that BlackBerry’s management did understand the threat but could not move fast enough, as the iPhone took off so quickly that, like with a snowball, BlackBerry found it swept up, in a very short time range.

Outcome bias and attribution error

The other side of the coin is represented by the so-called fundamental attribution error.

Fundamental attribution error is a bias people display when judging the behavior of others. The tendency is to over-emphasize personal characteristics and under-emphasize environmental and situational factors.

Whereas we overstate the behavior of an individual and his characteristics while understating the context and environment in which this individual acted.

A classic example is in all the self-improvement literature, which looks at individual success as if it was a predictable path, yet as usual, in hindsight.

For instance, books that focus on the features of successful individuals are often skewed toward over-emphasizing the personal habits of those people, as those have a direct relationship with the outcome.

Take the case of the classic self-improvement book which looks at the habits of successful people.

Yet, this doesn’t tell you that many unsuccessful people might also carry the same habits.

In other words, these habits are selected in hindsight based on the outcome rather than considering that those might be random traits shared by many individuals.

And yet, most of those individuals who carry those habits don’t turn successful.

Take the case of statements like “successful people wake up early.”

As if all the people that wake up very early are successful.

This leads to many more people following false patterns, believing that those are what creates success rather than focusing on building their own way of doing things.

Outcome bias and survivorship bias

Another huge risk when falling into the outcome bias is to look at successful people and try to make a pattern of it.

In those cases, it’s easy to fall into the survivorship bias.

Survivorship bias is a pervasive fallacy that exists in business, where people focus on the few survived players, in any given market, without realizing that most initial players in that given market are dead, or went into oblivion. In short, survivorship bias transforms the past into a linear story, by removing uncertainty from it.

Going back to the self-improvement literature, which studies successful people, often their habits and features are overstated to make the case and sell more of these books.

But in reality, this literature only studies what’s visible now without considering what’s not visible anymore.

For instance, take the case of the book, which shows you what great companies do by looking at the list of dominant/leading companies in the marketplace.

It’s easy to extrapolate successful processes from these companies as if you can also build a successful company by copying them.

Yet, this falls into the outcome bias, where many other companies which followed the same procedures didn’t make it at all!

Case Studies

  • Sports:
    • Decision: A soccer coach decides to substitute a key player during a crucial game.
    • Outcome: The substitute player scores the winning goal.
    • Bias: Everyone praises the coach’s decision as brilliant, even if the substitution was due to the key player being injured and not a strategic move.
  • Investments:
    • Decision: An investor decides to put a significant portion of their portfolio into a relatively unknown start-up.
    • Outcome: The start-up becomes the next big tech giant.
    • Bias: Everyone considers the investor a genius, ignoring the countless other similar bets that didn’t pan out.
  • Medical:
    • Decision: A doctor decides to try an experimental treatment on a critically ill patient.
    • Outcome: The patient recovers fully.
    • Bias: The doctor is hailed as innovative and brilliant, even though the decision had a high risk of not succeeding.
  • Entertainment:
    • Decision: A movie director decides to cast an unknown actor in the lead role of a big-budget film.
    • Outcome: The movie becomes a blockbuster, and the actor becomes an overnight sensation.
    • Bias: The director’s decision is labeled as visionary, even though many factors could have contributed to the movie’s success.
  • Business Strategy:
    • Decision: A CEO decides to pivot the company into a completely new product line.
    • Outcome: The new product line becomes a market leader.
    • Bias: The CEO’s decision is seen as a masterstroke, even if the decision was more of a desperate move due to failing existing products.
  • Research & Development:
    • Decision: A research team decides to abandon a project they’ve been working on for years to pursue a new idea.
    • Outcome: The new idea leads to a revolutionary discovery.
    • Bias: The team’s decision is seen as a stroke of genius, overlooking the resources and time spent on the abandoned project.
  • Marketing:
    • Decision: A marketing manager decides to invest heavily in an unconventional advertising campaign.
    • Outcome: The campaign goes viral, leading to record sales.
    • Bias: The manager’s risky decision is celebrated, even though many similar campaigns fail to make an impact.
  • Politics:
    • Decision: A leader decides to take a controversial stand on a divisive issue.
    • Outcome: Public opinion shifts in their favor, and they win the next election.
    • Bias: The leader’s decision is seen as bold and visionary, ignoring the myriad of other factors that influence elections.
  • Education:
    • Decision: A teacher decides to implement a new teaching method in the classroom.
    • Outcome: Students’ grades improve significantly.
    • Bias: The teacher’s method is hailed as revolutionary, even though other external factors (like smaller class sizes or additional resources) might have contributed.
  • Real Estate:
    • Decision: A property developer decides to invest in a dilapidated area of the city.
    • Outcome: The area becomes a trendy hotspot, and property values soar.
    • Bias: The developer’s decision is seen as a masterful understanding of market trends, even if other macro factors (like improved public transport or city-wide development initiatives) played a part.

Key Takeaways

  • Outcome bias occurs when a decision is based on the outcome of previous events without regard for how those events developed.
  • Outcome bias in business tends to occur in the recruitment process, product development, and leadership. Most conspire to create an outcome-centric culture in organizations where one person has to lose for another to win.
  • Outcome bias can be avoided with critical thinking and a commitment to focusing on processes. Discussing the bias with a trusted colleague or supervisor can be a good way to uncover its underlying causes.

Key Highlights

  • Outcome Bias: Outcome bias is the tendency to evaluate a decision based on its outcome rather than considering the process by which the decision was made.
  • Self-Evaluative Nature: Humans are self-evaluative beings, often using the outcome of decisions to measure future performance.
  • Positive and Negative Outcomes: Outcome bias can occur when a decision results in either a positive or negative outcome.
  • Business Application: Outcome bias can be present in various business situations, such as recruitment, product development, and leadership decisions.
  • Avoiding Outcome Bias: To avoid outcome bias, critical thinking is essential, focusing on the decision-making process rather than just the outcome.
  • Hindsight Bias: Be cautious not to fall into hindsight bias, perceiving past events as more predictable than they actually were.
  • Attribution Error: Avoid fundamental attribution error by considering environmental and situational factors, not just personal characteristics, when judging the behavior of others.
  • Survivorship Bias: Be aware of survivorship bias, which focuses on successful individuals or companies without considering the failures that may have occurred in the same context.

Connected Thinking Frameworks

Convergent vs. Divergent Thinking

Convergent thinking occurs when the solution to a problem can be found by applying established rules and logical reasoning. Whereas divergent thinking is an unstructured problem-solving method where participants are encouraged to develop many innovative ideas or solutions to a given problem. Where convergent thinking might work for larger, mature organizations where divergent thinking is more suited for startups and innovative companies.

Critical Thinking

Critical thinking involves analyzing observations, facts, evidence, and arguments to form a judgment about what someone reads, hears, says, or writes.


The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman in 1972. Biases are seen as systematic errors and flaws that make humans deviate from the standards of rationality, thus making us inept at making good decisions under uncertainty.

Second-Order Thinking

Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.

Lateral Thinking

Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.

Bounded Rationality

Bounded rationality is a concept attributed to Herbert Simon, an economist and political scientist interested in decision-making and how we make decisions in the real world. In fact, he believed that rather than optimizing (which was the mainstream view in the past decades) humans follow what he called satisficing.

Dunning-Kruger Effect

The Dunning-Kruger effect describes a cognitive bias where people with low ability in a task overestimate their ability to perform that task well. Consumers or businesses that do not possess the requisite knowledge make bad decisions. What’s more, knowledge gaps prevent the person or business from seeing their mistakes.

Occam’s Razor

Occam’s Razor states that one should not increase (beyond reason) the number of entities required to explain anything. All things being equal, the simplest solution is often the best one. The principle is attributed to 14th-century English theologian William of Ockham.

Lindy Effect

The Lindy Effect is a theory about the ageing of non-perishable things, like technology or ideas. Popularized by author Nicholas Nassim Taleb, the Lindy Effect states that non-perishable things like technology age – linearly – in reverse. Therefore, the older an idea or a technology, the same will be its life expectancy.


Antifragility was first coined as a term by author, and options trader Nassim Nicholas Taleb. Antifragility is a characteristic of systems that thrive as a result of stressors, volatility, and randomness. Therefore, Antifragile is the opposite of fragile. Where a fragile thing breaks up to volatility; a robust thing resists volatility. An antifragile thing gets stronger from volatility (provided the level of stressors and randomness doesn’t pass a certain threshold).

Systems Thinking

Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. It is about thinking non-linearly, and understanding the second-order consequences of actions and input into the system.

Vertical Thinking

Vertical thinking, on the other hand, is a problem-solving approach that favors a selective, analytical, structured, and sequential mindset. The focus of vertical thinking is to arrive at a reasoned, defined solution.

Maslow’s Hammer

Maslow’s Hammer, otherwise known as the law of the instrument or the Einstellung effect, is a cognitive bias causing an over-reliance on a familiar tool. This can be expressed as the tendency to overuse a known tool (perhaps a hammer) to solve issues that might require a different tool. This problem is persistent in the business world where perhaps known tools or frameworks might be used in the wrong context (like business plans used as planning tools instead of only investors’ pitches).

Peter Principle

The Peter Principle was first described by Canadian sociologist Lawrence J. Peter in his 1969 book The Peter Principle. The Peter Principle states that people are continually promoted within an organization until they reach their level of incompetence.

Straw Man Fallacy

The straw man fallacy describes an argument that misrepresents an opponent’s stance to make rebuttal more convenient. The straw man fallacy is a type of informal logical fallacy, defined as a flaw in the structure of an argument that renders it invalid.

Streisand Effect

The Streisand Effect is a paradoxical phenomenon where the act of suppressing information to reduce visibility causes it to become more visible. In 2003, Streisand attempted to suppress aerial photographs of her Californian home by suing photographer Kenneth Adelman for an invasion of privacy. Adelman, who Streisand assumed was paparazzi, was instead taking photographs to document and study coastal erosion. In her quest for more privacy, Streisand’s efforts had the opposite effect.


As highlighted by German psychologist Gerd Gigerenzer in the paper “Heuristic Decision Making,” the term heuristic is of Greek origin, meaning “serving to find out or discover.” More precisely, a heuristic is a fast and accurate way to make decisions in the real world, which is driven by uncertainty.

Recognition Heuristic

The recognition heuristic is a psychological model of judgment and decision making. It is part of a suite of simple and economical heuristics proposed by psychologists Daniel Goldstein and Gerd Gigerenzer. The recognition heuristic argues that inferences are made about an object based on whether it is recognized or not.

Representativeness Heuristic

The representativeness heuristic was first described by psychologists Daniel Kahneman and Amos Tversky. The representativeness heuristic judges the probability of an event according to the degree to which that event resembles a broader class. When queried, most will choose the first option because the description of John matches the stereotype we may hold for an archaeologist.

Take-The-Best Heuristic

The take-the-best heuristic is a decision-making shortcut that helps an individual choose between several alternatives. The take-the-best (TTB) heuristic decides between two or more alternatives based on a single good attribute, otherwise known as a cue. In the process, less desirable attributes are ignored.

Bundling Bias

The bundling bias is a cognitive bias in e-commerce where a consumer tends not to use all of the products bought as a group, or bundle. Bundling occurs when individual products or services are sold together as a bundle. Common examples are tickets and experiences. The bundling bias dictates that consumers are less likely to use each item in the bundle. This means that the value of the bundle and indeed the value of each item in the bundle is decreased.

Barnum Effect

The Barnum Effect is a cognitive bias where individuals believe that generic information – which applies to most people – is specifically tailored for themselves.

First-Principles Thinking

First-principles thinking – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.

Ladder Of Inference

The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.

Goodhart’s Law

Goodhart’s Law is named after British monetary policy theorist and economist Charles Goodhart. Speaking at a conference in Sydney in 1975, Goodhart said that “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Goodhart’s Law states that when a measure becomes a target, it ceases to be a good measure.

Six Thinking Hats Model

The Six Thinking Hats model was created by psychologist Edward de Bono in 1986, who noted that personality type was a key driver of how people approached problem-solving. For example, optimists view situations differently from pessimists. Analytical individuals may generate ideas that a more emotional person would not, and vice versa.

Mandela Effect

The Mandela effect is a phenomenon where a large group of people remembers an event differently from how it occurred. The Mandela effect was first described in relation to Fiona Broome, who believed that former South African President Nelson Mandela died in prison during the 1980s. While Mandela was released from prison in 1990 and died 23 years later, Broome remembered news coverage of his death in prison and even a speech from his widow. Of course, neither event occurred in reality. But Broome was later to discover that she was not the only one with the same recollection of events.

Crowding-Out Effect

The crowding-out effect occurs when public sector spending reduces spending in the private sector.

Bandwagon Effect

The bandwagon effect tells us that the more a belief or idea has been adopted by more people within a group, the more the individual adoption of that idea might increase within the same group. This is the psychological effect that leads to herd mentality. What in marketing can be associated with social proof.

Moore’s Law

Moore’s law states that the number of transistors on a microchip doubles approximately every two years. This observation was made by Intel co-founder Gordon Moore in 1965 and it become a guiding principle for the semiconductor industry and has had far-reaching implications for technology as a whole.

Disruptive Innovation

Disruptive innovation as a term was first described by Clayton M. Christensen, an American academic and business consultant whom The Economist called “the most influential management thinker of his time.” Disruptive innovation describes the process by which a product or service takes hold at the bottom of a market and eventually displaces established competitors, products, firms, or alliances.

Value Migration

Value migration was first described by author Adrian Slywotzky in his 1996 book Value Migration – How to Think Several Moves Ahead of the Competition. Value migration is the transferal of value-creating forces from outdated business models to something better able to satisfy consumer demands.

Bye-Now Effect

The bye-now effect describes the tendency for consumers to think of the word “buy” when they read the word “bye”. In a study that tracked diners at a name-your-own-price restaurant, each diner was asked to read one of two phrases before ordering their meal. The first phrase, “so long”, resulted in diners paying an average of $32 per meal. But when diners recited the phrase “bye bye” before ordering, the average price per meal rose to $45.


Groupthink occurs when well-intentioned individuals make non-optimal or irrational decisions based on a belief that dissent is impossible or on a motivation to conform. Groupthink occurs when members of a group reach a consensus without critical reasoning or evaluation of the alternatives and their consequences.


A stereotype is a fixed and over-generalized belief about a particular group or class of people. These beliefs are based on the false assumption that certain characteristics are common to every individual residing in that group. Many stereotypes have a long and sometimes controversial history and are a direct consequence of various political, social, or economic events. Stereotyping is the process of making assumptions about a person or group of people based on various attributes, including gender, race, religion, or physical traits.

Murphy’s Law

Murphy’s Law states that if anything can go wrong, it will go wrong. Murphy’s Law was named after aerospace engineer Edward A. Murphy. During his time working at Edwards Air Force Base in 1949, Murphy cursed a technician who had improperly wired an electrical component and said, “If there is any way to do it wrong, he’ll find it.”

Law of Unintended Consequences

The law of unintended consequences was first mentioned by British philosopher John Locke when writing to parliament about the unintended effects of interest rate rises. However, it was popularized in 1936 by American sociologist Robert K. Merton who looked at unexpected, unanticipated, and unintended consequences and their impact on society.

Fundamental Attribution Error

Fundamental attribution error is a bias people display when judging the behavior of others. The tendency is to over-emphasize personal characteristics and under-emphasize environmental and situational factors.

Outcome Bias

Outcome bias describes a tendency to evaluate a decision based on its outcome and not on the process by which the decision was reached. In other words, the quality of a decision is only determined once the outcome is known. Outcome bias occurs when a decision is based on the outcome of previous events without regard for how those events developed.

Hindsight Bias

Hindsight bias is the tendency for people to perceive past events as more predictable than they actually were. The result of a presidential election, for example, seems more obvious when the winner is announced. The same can also be said for the avid sports fan who predicted the correct outcome of a match regardless of whether their team won or lost. Hindsight bias, therefore, is the tendency for an individual to convince themselves that they accurately predicted an event before it happened.

Read Next: BiasesBounded RationalityMandela EffectDunning-Kruger EffectLindy EffectCrowding Out EffectBandwagon Effect.

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