hickams-dictum

What is Hickam’s Dictum?

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Hickam’s dictum is the counterargument to Occam’s razor. Whereas Occam’s razor is a heuristic that tends to narrow down decision-making to the simplest variables, Hickam’s dictum believes a situation must be tackled by looking at multiple variables.

AspectExplanation
Concept Overview– Hickam’s Dictum, also known as the “Doctor’s Rule,” is a principle in the field of medicine and clinical reasoning that emphasizes the complexity of diagnosing medical conditions. Named after Dr. John Hickam, this dictum challenges the notion that there should be a single, straightforward explanation for a patient’s symptoms. Instead, it suggests that patients can present with a wide range of symptoms and that multiple potential diagnoses should be considered. In essence, it encourages physicians to avoid prematurely settling on a single diagnosis when assessing a patient’s health.
Key Principles– Hickam’s Dictum is based on several key principles: 1. Diagnostic Complexity: Acknowledges that medical diagnoses can be complex, with patients often having multiple symptoms and potential underlying conditions. 2. Avoiding Premature Conclusions: Encourages healthcare professionals to avoid the inclination to make hasty or overly simplistic diagnoses. 3. Open-Mindedness: Promotes open-mindedness in considering a range of possible diagnoses, rather than fixating on a single explanation. 4. Comprehensive Evaluation: Suggests that a thorough and comprehensive evaluation of the patient’s symptoms and medical history is essential. 5. Diagnostic Uncertainty: Recognizes that uncertainty is a part of medical practice, and multiple diagnostic possibilities should be explored.
Examples– Examples of Hickam’s Dictum in medical practice include: 1. Patient with Multiple Symptoms: A patient presents with a combination of symptoms, such as fatigue, joint pain, and skin rashes. Rather than immediately attributing these symptoms to a single condition, a physician considers various possible diagnoses, including autoimmune diseases or infections. 2. Diagnostic Dilemma: When a patient’s symptoms do not neatly fit a known medical condition, healthcare providers may explore a range of potential causes before arriving at a conclusive diagnosis.
Impact and Consequences– Hickam’s Dictum has several important impacts and consequences: 1. Enhanced Diagnostic Accuracy: By considering multiple diagnostic possibilities, healthcare professionals can improve their chances of accurately identifying the underlying condition. 2. Avoiding Misdiagnoses: It helps reduce the risk of misdiagnoses or premature conclusions, which can have serious consequences for patient health. 3. Patient-Centered Care: Encourages a patient-centered approach that takes into account the complexity of individual health conditions. 4. Humility in Medicine: Promotes humility among healthcare providers by acknowledging the limits of medical knowledge and diagnostic certainty.
Mitigation– To adhere to Hickam’s Dictum and mitigate diagnostic errors, healthcare professionals should: 1. Gather Comprehensive Data: Collect thorough patient histories, conduct detailed physical examinations, and order appropriate diagnostic tests. 2. Consider Differential Diagnoses: Generate a list of potential diagnoses (differential diagnoses) and systematically evaluate each possibility. 3. Seek Second Opinions: In cases of diagnostic uncertainty, seek input from colleagues or specialists for a fresh perspective. 4. Embrace Diagnostic Uncertainty: Accept that diagnostic uncertainty is a reality in medicine and communicate this with patients as part of informed decision-making.
Relevance– Hickam’s Dictum is highly relevant in the field of medicine, particularly in the context of clinical reasoning, differential diagnosis, and patient care. It underscores the importance of thorough evaluation, open-mindedness, and considering multiple possibilities in medical practice.

Understanding the Hickam’s dictum

Occam’s razor is used in the medical industry to imply that multiple symptoms in a patient can be attributed to a single disease.

Hickam’s dictum counters this argument, believing the patient’s multiple symptoms to be, in most cases, the result of several diseases.

Hickam’s dictum is based on an aphorism usually stated as “patients can have as many diseases as they damn well please.”

This line is attributed to John Hickam, an American physician who worked at Grady Memorial Hospital in Atlanta in his early career and then became chairman of medicine at Indiana University between 1958 and 1970.

Hickham’s dictum and diagnostic parsimony

In contemporary medicine, Occam’s razor is often discussed by doctors in the context of diagnostic parsimony.

This principle advocates that doctors look for the fewest possible causes to account for all symptoms when diagnosing an injury, illness, or disease. 

This approach has limited use in modern medical practice, however, with the actual process of patient diagnosis consisting of multiple hypotheses that must be tested and modified as necessary.

Hickam’s dictum asserts that as doctors carry out this process, no potential diagnosis should be excluded on the basis that it does not appear to satisfy the principle of Occam’s razor. 

Note that Occam’s razor does not require that the doctor necessarily choose the simplest diagnosis.

Instead, it encourages the practitioner to find an explanation that accounts for all evidence without making undue assumptions.

With the above in mind, Occam’s razor can be a useful diagnostic tool – but it is by no means infallible. In medicine, the simplest answer – or the one with the fewest number of diagnoses – is not always the correct answer. 

Hickam’s dictum and statistical analysis

That Hickam’s dictum can serve as a counterargument to Occam’s razor is down to statistical analysis.

Stats show that patients are more likely to have multiple diseases and less likely to have one, rarer disease that accounts for all their symptoms. 

Some patients with multiple diseases may also receive a diagnosis that each disease has an independent cause rather than all diseases being attributable to a single source.

That is, each disease is derived from separate events (or a combination of events) to which the patient has been exposed. 

When doctors diagnose a patient with one rare disease, they make a critical assumption that is often unrelated to the patient’s symptoms and is statistically unlikely in any case.

Conversely, when the patient is diagnosed with three common conditions to which they may already be predisposed, the doctor minimizes the introduction of new assumptions that can lead to an incorrect diagnosis.

Relevance in Healthcare:

Hickam’s Dictum is highly relevant in healthcare settings, especially in clinical practice and medical decision-making:

  1. Complex Patients: In modern medicine, patients often have comorbidities or overlapping symptoms that require careful consideration and a comprehensive diagnostic approach.
  2. Avoiding Misdiagnosis: The principle helps prevent the misdiagnosis of patients who may have multiple medical conditions, ensuring they receive appropriate treatment.
  3. Diagnostic Challenges: In cases where symptoms are not typical or do not fit a single diagnostic pattern, Hickam’s Dictum encourages healthcare providers to explore a broader range of possibilities.
  4. Holistic Care: It promotes a holistic approach to patient care, taking into account the diverse factors that may contribute to a patient’s health.

Impact on Medical Decision-Making:

Hickam’s Dictum has several implications for medical decision-making:

  1. Broad Differential Diagnosis: Healthcare providers should maintain a broad differential diagnosis, considering multiple potential conditions when evaluating a patient.
  2. Thorough Evaluation: Patients with complex presentations may require more extensive diagnostic testing and evaluation to identify all relevant conditions.
  3. Collaboration: Interdisciplinary collaboration among healthcare professionals is essential to ensure all possible conditions are considered and evaluated.
  4. Individualized Treatment: Recognizing multiple coexisting conditions allows for individualized treatment plans that address the specific needs of each patient.

Potential Implications for Patient Care:

Adhering to Hickam’s Dictum can lead to several positive implications for patient care:

  1. Accurate Diagnosis: Patients are more likely to receive accurate and timely diagnoses, leading to appropriate treatment.
  2. Improved Outcomes: Addressing all relevant medical conditions can lead to better patient outcomes and overall health.
  3. Patient Satisfaction: Patients may experience increased satisfaction with their healthcare when their concerns and symptoms are thoroughly evaluated and addressed.
  4. Preventing Harm: Avoiding misdiagnosis or underdiagnosis of serious conditions helps prevent patient harm.

Hickam’s dictum in business

As the volume, variety, and velocity of modern datasets increases, the probability that a business will encounter Hickam’s dictum increases in turn.

Data can now be combined to diagnose and solve problems in a way that was once unimaginable, so the relative simplicity of Occam’s razor may be less useful in some instances.

With that said, most businesses will benefit from a combination of advanced data analytics (Hickam’s dictum) and Occam’s razor where they default to the simplest explanation possible.

McDonald’s

Take McDonald’s, for example, where almost every process has been recorded and standardized to increase efficiency and profits.

In fact, the company is a master of solving problems with simple solutions and then turning them into systems. 

Many restaurants contend with the problem of sourcing trained cooks and chefs, but McDonald’s solves this issue with simple menu items that can be quickly and easily prepared by anyone.

Indeed, the company could take a high school student off the street with zero experience and teach them to prepare a Big Mac in a matter of days. 

There are also systems in place to ensure the food is made to a consistent standard, such as those that dictate the correct temperature of the fryer.

The bathrooms in McDonald’s restaurants are also clean and functional and its systemized employee training program is respected around the world.

McDonald’s and data

While McDonald’s is a systemized company, it is not afraid to make decisions and solve problems based on data collected from its vast network of restaurants. Based on this data, for example, the company identified three areas of improvement:

  1. The design of the drive-thru itself.
  2. The information provided to customers in the drive-thru, and
  3. The nature of the people waiting in line to order. 

By analyzing the data, McDonald’s was able to determine what times of day customers were most likely to visit and add extra staff to reduce wait times.

But it has also introduced AI that analyzes local buying patterns based on factors such as events, celebrations, weekends, or even whether it is payday for employees in the area.

Based on these patterns, the AI recommends relevant food and drink suggestions on the drive-thru screen for that specific restaurant and time of day.

The point is there that to improve its drive-thru experience, McDonald’s did not default to the simplest or most likely solution (reducing wait times).

Instead, by analyzing data from its restaurants, the company determined that its inadequate drive-thru experience could be explained by multiple, less-common “diagnoses” that may have otherwise been overlooked.

Key takeaways:

  • Hickam’s dictum, used in the medical industry as a counterargument to Occam’s razor, believes multiple symptoms can be attributed to one disease.
  • In contemporary medicine, Occam’s razor is often discussed by doctors in the context of diagnostic parsimony. This principle advocates that doctors look for the fewest possible causes to account for all symptoms when diagnosing an injury, illness, or disease. 
  • Hickam’s dictum is a counterargument to Occam’s razor because it is based on statistical evidence. Stats show that patients are more likely to have multiple diseases or comorbidities and less likely to have one, rarer disease that accounts for all their symptoms.

Key Highlights

  • Introduction to Hickam’s Dictum: Hickam’s Dictum serves as a counterargument to Occam’s Razor. While Occam’s Razor simplifies decision-making by considering the simplest variables, Hickam’s Dictum suggests that situations should be analyzed by considering multiple variables.
  • Application in Medicine:
    • Occam’s Razor is often used in medicine to attribute multiple symptoms to a single disease.
    • Hickam’s Dictum counters this, asserting that patients can have multiple diseases causing their symptoms, rather than a single disease.
  • John Hickam and the Dictum:
    • John Hickam, an American physician, is attributed to the phrase “patients can have as many diseases as they damn well please,” forming the basis of Hickam’s Dictum.
  • Hickam’s Dictum and Diagnostic Parsimony:
    • Diagnostic parsimony involves seeking the fewest possible causes for all symptoms in medical diagnosis.
    • Hickam’s Dictum asserts that the process of diagnosis involves testing and modifying multiple hypotheses, without excluding potential diagnoses based on Occam’s Razor.
  • Counterargument in Medical Context:
    • Occam’s Razor encourages finding explanations that account for evidence without assumptions.
    • Hickam’s Dictum recognizes that the simplest explanation might not always be the correct one, and multiple diseases could contribute to symptoms.
  • Hickam’s Dictum in Statistical Analysis:
    • Statistical analysis supports Hickam’s Dictum, indicating patients are more likely to have multiple diseases than a single rare disease accounting for all symptoms.
    • Some patients might have comorbidities with independent causes for each disease, rather than a single source.
  • Application in Business and Data Analysis:
    • As data complexity increases, Hickam’s Dictum gains relevance.
    • Combining advanced data analytics with Occam’s Razor can be beneficial in business problem-solving.
  • McDonald’s Example:
    • McDonald’s employs data-driven decision-making alongside its systemized operations.
    • Analyzing data from its restaurants helped McDonald’s identify areas of improvement and tailor its drive-thru experience using AI.
  • Key Takeaways:
    • Hickam’s Dictum counters Occam’s Razor by emphasizing the consideration of multiple variables.
    • Medical diagnosis involves diagnostic parsimony and the testing of multiple hypotheses.
    • In business and data analysis, a combination of advanced analytics and simpler explanations can yield effective solutions.

Connected Thinking Frameworks

Convergent vs. Divergent Thinking

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

Biases

biases
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
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
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
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

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

occams-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

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

antifragility
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).

Ergodicity

ergodicity
Ergodicity is one of the most important concepts in statistics. Ergodicity is a mathematical concept suggesting that a point of a moving system will eventually visit all parts of the space the system moves in. On the opposite side, non-ergodic means that a system doesn’t visit all the possible parts, as there are absorbing barriers

Systems Thinking

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
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.

Metaphorical Thinking

metaphorical-thinking
Metaphorical thinking describes a mental process in which comparisons are made between qualities of objects usually considered to be separate classifications.  Metaphorical thinking is a mental process connecting two different universes of meaning and is the result of the mind looking for similarities.

Maslow’s Hammer

einstellung-effect
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

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

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.

Google Effect

google-effect
The Google effect is a tendency for individuals to forget information that is readily available through search engines. During the Google effect – sometimes called digital amnesia – individuals have an excessive reliance on digital information as a form of memory recall.

Streisand Effect

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.

Compromise Effect

compromise-effect
Single-attribute choices – such as choosing the apartment with the lowest rent – are relatively simple. However, most of the decisions consumers make are based on multiple attributes which complicate the decision-making process. The compromise effect states that a consumer is more likely to choose the middle option of a set of products over more extreme options.

Butterfly Effect

butterfly-effect
In business, the butterfly effect describes the phenomenon where the simplest actions yield the largest rewards. The butterfly effect was coined by meteorologist Edward Lorenz in 1960 and as a result, it is most often associated with weather in pop culture. Lorenz noted that the small action of a butterfly fluttering its wings had the potential to cause progressively larger actions resulting in a typhoon.

IKEA Effect

ikea-effect
The IKEA effect is a cognitive bias that describes consumers’ tendency to value something more if they have made it themselves. That is why brands often use the IKEA effect to have customizations for final products, as they help the consumer relate to it more and therefore appending to it more value.

Ringelmann Effect 

Ringelmann Effect
The Ringelmann effect describes the tendency for individuals within a group to become less productive as the group size increases.

The Overview Effect

overview-effect
The overview effect is a cognitive shift reported by some astronauts when they look back at the Earth from space. The shift occurs because of the impressive visual spectacle of the Earth and tends to be characterized by a state of awe and increased self-transcendence.

House Money Effect

house-money-effect
The house money effect was first described by researchers Richard Thaler and Eric Johnson in a 1990 study entitled Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice. The house money effect is a cognitive bias where investors take higher risks on reinvested capital than they would on an initial investment.

Heuristic

heuristic
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

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

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

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

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

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.

Anchoring Effect

anchoring-effect
The anchoring effect describes the human tendency to rely on an initial piece of information (the “anchor”) to make subsequent judgments or decisions. Price anchoring, then, is the process of establishing a price point that customers can reference when making a buying decision.

Decoy Effect

decoy-effect
The decoy effect is a psychological phenomenon where inferior – or decoy – options influence consumer preferences. Businesses use the decoy effect to nudge potential customers toward the desired target product. The decoy effect is staged by placing a competitor product and a decoy product, which is primarily used to nudge the customer toward the target product.

Commitment Bias

commitment-bias
Commitment bias describes the tendency of an individual to remain committed to past behaviors – even if they result in undesirable outcomes. The bias is particularly pronounced when such behaviors are performed publicly. Commitment bias is also known as escalation of commitment.

First-Principles Thinking

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

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

goodharts-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

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

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

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

Bandwagon Effect

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

moores-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
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
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

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

groupthink
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.

Stereotyping

stereotyping
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

murphys-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

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
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
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
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: Biases, Bounded Rationality, Mandela Effect, Dunning-Kruger Effect, Lindy Effect, Crowding Out Effect, Bandwagon Effect.

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