What Is The Uncertainty Reduction Theory? Uncertainty Reduction Theory In A Nutshell

Uncertainty reduction theory was first proposed in 1975 by American communication theorists Charles R. Berger and Richard J. Calabrese. Uncertainty reduction theory suggests people are uncomfortable with uncertainty and seek ways of predicting the trajectory of social interactions.

Theory OverviewUncertainty Reduction Theory is a social psychological theory developed by Charles Berger and Richard Calabrese in 1975. This theory focuses on how people communicate to reduce uncertainty when they meet for the first time. It suggests that when individuals encounter someone new, they experience uncertainty about the other person’s attitudes, beliefs, and behaviors. To manage this uncertainty, they engage in communication strategies to gather information and reduce uncertainty. The theory is particularly relevant in the context of initial interactions, such as first dates, job interviews, or new social acquaintances.
Key Concepts– Uncertainty Reduction Theory is based on several key concepts: 1. Uncertainty: The lack of knowledge about the other person’s characteristics or behavior. 2. Initial Interaction: The theory applies to initial encounters where individuals have limited prior knowledge of each other. 3. Axioms: The theory includes three axioms that describe how people respond to uncertainty, including the Axiom of Verbal Communication, Axiom of Nonverbal Warmth, and Axiom of Information Seeking. 4. Strategies: People use communication strategies, such as asking questions, disclosing information, and interpreting nonverbal cues, to reduce uncertainty. 5. Reduction Goals: The ultimate goal of these strategies is to reduce uncertainty and increase predictability in the interaction.
Axioms– The three axioms of Uncertainty Reduction Theory are: 1. Axiom of Verbal Communication: When uncertainty is high, people tend to engage in more verbal communication, including asking questions and seeking information. 2. Axiom of Nonverbal Warmth: When uncertainty is reduced, individuals tend to display warmer nonverbal behaviors, such as smiling or maintaining eye contact. 3. Axiom of Information Seeking: When uncertainty is high, people are more likely to seek information actively about the other person, often through indirect means.
Strategies– Individuals employ various strategies to reduce uncertainty during initial interactions: 1. Questioning: Asking questions to gather information about the other person’s background, interests, and preferences. 2. Self-Disclosure: Sharing personal information to reciprocate and encourage the other person to do the same. 3. Relational Questions: Inquiring about the other person’s relationship status or intentions. 4. Third Parties: Gathering information from mutual acquaintances or friends. 5. Direct Observation: Observing the other person’s behavior and reactions. 6. Online Research: Using online platforms and social media to learn more about the individual.
Applications– Uncertainty Reduction Theory is applied in various fields, including interpersonal communication, psychology, and healthcare. It is particularly relevant in understanding how healthcare providers and patients communicate during initial medical consultations, where reducing uncertainty about diagnoses and treatment options is crucial for building trust and rapport.
Critiques and Developments– The theory has faced critiques related to its applicability in diverse cultural contexts and the assumption that reducing uncertainty always leads to positive outcomes. Researchers have also extended the theory to explore issues of privacy, deception, and digital communication in the modern age.

Understanding the uncertainty reduction theory

In their research paper entitled Some Exploration in Initial Interaction and Beyond: Toward a Developmental Theory of Interpersonal Communication, Berger and Calabrese were able to predict and explain the degree of relational development between strangers.

To that end, the uncertainty reduction theory is based on a simple premise.

When two strangers meet, they each go through certain steps and checkpoints designed to reduce uncertainty about the other person.

The degree of uncertainty then determines whether one individual likes or dislikes the other, and vice versa.

Using the theory, individuals collect information about themselves, their relationships, and other people to reduce uncertainty or increase predictability.

As Berger more eloquently stated,

The acquisition, processing, retention, and retrieval of information is vital to the growth, maintenance, and decline of personal and social relationships. Relationships can be viewed as systems of information exchange that must reduce uncertainty in order to survive.

Today, uncertainty reduction theory remains a well-regarded tool to explain initial interaction events. In addition to new relationship formation, the theory has also found use in organizational socialization, intercultural interaction, and as a function of the media.

The three types of uncertainty

Uncertainty can be categorized in a few different ways:

Cognitive uncertainty

Which is typically related to the beliefs and attitudes of other people. Uncertainty results as the individual attempts to determine what the other is thinking.

Alternatively, they may be uncertain about their own thoughts.

Behavioral uncertainty

Or the behavior or actions of others in a particular situation.

Uncertainty is especially high when people ignore societal or cultural norms, which describe how one is expected to act in a social situation.

High behavioral uncertainty reduces the likelihood of future interactions.

Relational uncertainty

Which describes a lack of confidence an individual feels in predicting or explaining issues surrounding a particular relationship.

In essence, uncertainty is felt about the current or future status of the relationship – which may be platonic or romantic. 

The three stages of uncertainty reduction theory

Berger and Calabrese defined the initial interaction of strangers into three stages:


The first stage is characterized by the use of behavioral norms, which some may describe as small talk.

These norms include a pleasant greeting or laughter in response to a joke.

Information is then exchanged regarding age, social status, economic status, or other demographical factors mainly influenced by culture.

Personal stage

The second stage describes individuals who exchange information about attitudes and beliefs, but it may take several entry stage interactions before this occurs.

As one individual probes the other about their values and morals, the increased disclosure of information leads to increased emotional investment.

The exit stage

In the last stage, both individuals decide whether they want to develop the relationship further.

If there is mutual acceptance, plans can be made to meet up in the future.

The seven axioms of uncertainty reduction theory

Berger also proposed seven axioms, or self-evident truths, which the individual uses during communication to reduce uncertainty about the other person’s behavior or actions:

  1. Verbal communication – uncertainty is high initially, but decreases once verbal communication commences. Communication is inversely proportional to uncertainty. 
  2. Nonverbal warmth – nonverbal forms of communication such as eye contact, smiling, and positive body language also decrease uncertainty.
  3. Information seeking – an individual’s need to seek information about the other person decreases as uncertainty decreases.
  4. Self-disclosure – as the level of uncertainty decreases, the individual feels more comfortable disclosing progressively more intimate information.
  5. Reciprocity – where similar information is reciprocated between the two strangers. In other words, an individual who asks for age and occupation information is more likely to offer their age and occupation in return. However, as uncertainty decreases, the need to share information in this way decreases.
  6. Similarity – uncertainty decreases when both individuals realize they share mutual interests.
  7. Liking – related to similarity, mutual interests cause feelings of approval to develop. This, as you may guess, reduces uncertainty.

Uncertainty Reduction Theory vs. Social Penetration Theory

Social penetration theory was developed by fellow psychologists Dalmas Taylor and Irwin Altman in their 1973 article Social Penetration: The Development of Interpersonal Relationships. Social penetration theory (SPT) posits that as a relationship develops, shallow and non-intimate communication evolves and becomes deeper and more intimate.

The Social Penetration Theory is a model which believes that relationships develop from shallow to deeper through four stages: orientation, exploratory affective, affective, and stable exchange.

Whereas the Uncertainty Reduction Theory is a framework to reduce uncertainty in communication by leveraging seven axioms.

Examples And Case Studies

Examples of Uncertainty Reduction in Social Interactions:

  • Cognitive Uncertainty: During a job interview, a candidate wonders what the interviewer thinks about their qualifications and suitability for the role.
  • Behavioral Uncertainty: When attending a formal dinner, someone may be unsure how to act and follow proper dining etiquette.
  • Relational Uncertainty: In a new romantic relationship, one partner may feel uncertain about the future status of the relationship and where it’s heading.

Examples of Entry-Stage in Uncertainty Reduction:

  • At a networking event, two strangers engage in small talk, exchanging information about their professions and hobbies.
  • During the first day of a college orientation program, students introduce themselves and share basic details like their names and majors.

Examples of Personal Stage in Uncertainty Reduction:

  • After a few friendly conversations, two colleagues at work start discussing their values and beliefs on certain social issues.
  • In a new friendship, individuals gradually share more personal experiences, leading to increased emotional closeness.

Examples of Exit Stage in Uncertainty Reduction:

  • After a series of successful dates, a couple decides to make plans for a weekend getaway together.
  • Two professionals who have collaborated well on a project decide to work on another project together in the future.

Examples of Axioms in Uncertainty Reduction Theory:

  • Verbal Communication: In a job interview, as the conversation progresses, the candidate feels more comfortable and speaks more openly about their skills and experiences.
  • Nonverbal Warmth: During a business meeting, a warm handshake and friendly smile from a potential client put the presenter at ease and reduce uncertainty.
  • Information Seeking: A new neighbor asks others in the neighborhood about local schools, safety, and nearby amenities to reduce uncertainty about their new environment.
  • Self-disclosure: As two friends spend more time together and build trust, they begin to share personal struggles and experiences with each other.
  • Reciprocity: When discussing their favorite movies, one person shares their preferences, and the other reciprocates by sharing their favorite films as well.
  • Similarity: Two colleagues realize they have similar hobbies and interests outside of work, leading to a stronger bond and reduced uncertainty.
  • Liking: As two individuals discover shared values and interests, they feel a growing sense of liking and connection with each other, reducing uncertainty in their relationship.

Key takeaways:

  • Uncertainty reduction theory suggests people are uncomfortable with uncertainty and seek ways of predicting the trajectory of social interactions. The theory was first proposed in 1975 by Charles R. Berger and Richard J. Calabrese.
  • Uncertainty reduction theory suggests uncertainty may stem from a lack of clarity around certain behaviors, beliefs, attitudes, or relationships.
  • Uncertainty reduction theory is defined by seven self-evident truths that describe the various ways individuals try to reduce uncertainty. These include verbal communication, nonverbal warmth, information seeking, self-disclosure, reciprocity, similarity, and liking.

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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