It is no surprise that when you have a bowl of dog food in your hands, your dog becomes the best show dog on earth, effortlessly performing all the tricks it has learned. Sometimes you may even find your dog running through the list of tricks before you tell them which one to do. When you don’t have dog food in your hands, however, your furry friend will likely seem completely disinterested in performing. This behavior can be explained by behaviorism, sometimes referred to as behavioral psychology.

Behaviorism is a theory of learning; it’s based on the idea that our behavior is learned as a result of interaction with our external environment. Interaction with our external environment can include an interaction with a certain person, a certain object, or with certain surroundings.

Our behavior is learned through a process called conditioning. Conditioning is a learning process that can lead to habits and is the result of training ourselves to react a certain way in different scenarios.¹ Behaviorism presents two main types of conditioning:

• Classical conditioning: when a dog learns to get excited when we walk towards the bag of dog food because the dog has learned that it would mean they get to eat right away.
• Operant conditioning: when a trainer successfully teaches a dog how to sit on command with the help of incentives, such as a treat every time they do it correctly.

Strong believers of behaviorism argue that with the right conditioning, anyone can be trained to do any task within their capabilities, regardless of one’s personality.¹

In behavioral psychology, there are two types of behavior: overt behavior, which is what everyone sees publicly, and covert behavior, which is inner and private. Behaviorism as a field of study looks only at observable external behaviors rather than internal mental states. Behaviorists argue that since thoughts and emotions cannot be objectively measured, psychology should focus instead on stimulus-response relationships (like a dog’s response to food) that can be observed and analyzed. 

Behaviorism: A theory and school of thought in modern psychology stating that all types of human behavior can be learned through two key types of conditioning: classical conditioning and operant conditioning. 

Radical Behaviorism:  A theory developed by B.F. Skinner that extends traditional behaviorism. It includes not only observable behaviors but also internal events, such as thoughts and feelings, as behaviors subject to the same principles of conditioning. It views all behavior, external and internal, as shaped by the environment and past reinforcement.

Stimulus: Anything that occurs in the environment that elicits a response from an individual.

Response: Any observable action or behavior that an organism performs as a result of a stimulus. 

Classical Conditioning: A learning technique that unconsciously pairs a specific action, or stimulus, with the resulting automatic behavioral response. When the action or stimulus is repeated, the automatic behavioral response is eventually learned to be associated with the action.¹

Operant Conditioning: A learning technique that employs positive and negative reinforcements in the form of rewards or punishments to encourage an individual to pick up or stop a specific behavior. It’s sometimes referred to as instrumental conditioning.¹ There are two types of punishment: positive, where a negative stimulus is added to discourage behavior; and negative, where a pleasant stimulus is removed to decrease undesired behavior. 

Positive Reinforcement: A consequence that aims to strengthen or encourage certain behaviors, such as providing a reward for doing something well.

Grid Cells: Cells in the brain that help us to know where we are and where we’re going. They’re found in a part of the brain called the entorhinal cortex, and they fire in patterns that form a grid. As we move through space, different grid cells light up in a repeating pattern, helping our brains track our position, even without a map or landmarks.

Early work on behaviorism can be traced back to 1897, when Ivan Pavlov, a Russian physiologist, conducted experiments on the digestion in dogs. Pavlov’s now-famous experiments led him to discover what we call classical conditioning.²  It all started when Pavlov noticed the dogs would start salivating when presented with food. When presented with food, the lab assistant would also ring a bell (a neutral stimulus). Over time, the dogs would associate the bell with food. Eventually, the dogs associated the sight of the lab assistant’s white coat (another neutral stimulus) with food, which prompted a salivation response from the dogs even before the food was presented.^1,3,4

Behaviorism would not be introduced formally until 1913, when American psychologist John B. Watson presented his publication, Psychology as the Behaviorist Views It. In this paper, Watson mentioned that if he provided his own specified environment for a baby to grow up in, he would be able to train them to become a specialist in any profession. Watson claimed this could include law, medicine, art, or even theft.¹

Watson’s formal contribution was so influential that in the following forty years, behaviorism became the dominant school of thought in psychology. Its popularity also reflected the desire to cement psychology as a measurable science, which behaviorism’s focus on observable behavior was able to provide.¹

Operant conditioning was introduced by American psychologist B. F. Skinner in the 1938 book, The Behavior of Organisms. Skinner derived his theory by studying rats. He set up a box with a lever, which when pressed would drop a pellet of food onto a tray. Skinner introduced a rat into the box and observed that initially, it would wander around before accidentally pressing the bar. After the first food pellet was released, Skinner noticed that the rat’s rate of bar pressing increased dramatically. Research on Skinner’s experiment eventually led to the principle of reinforcement,² a term used in operant conditioning to describe an action that increases the chances of certain behavior.^2,5

Towards the end of the 1900s, the cognitive psychology revolution resulted in the diminishing popularity of behaviorism as the mainstream school of thought. Psychologists started turning to cognitive science to study human behavior, due to behaviorism’s failure in considering important mental processes.⁶ However, many insights from behaviorism were not forgotten and are used regularly to this day.

The principles of reinforcement and punishment, for example, remain central to behavior change, influencing everything from parenting techniques to workplace motivation and educational strategies. Similarly, behavioral conditioning is still widely applied in therapy, particularly in treating phobias, anxiety, and addictions through techniques like systematic desensitization and exposure therapy.¹⁶ 

Marketing and advertising also rely on behaviorist principles, using rewards and associations to shape consumer behavior. Take loyalty programs, for example, which use positive reinforcement to keep people coming back time and again. Each time a customer buys something, they earn a point, eventually working their way up to a free drink or a considerable discount. This operant conditioning encourages repeat purchases by associating spending with a desirable reward. 

Ivan Pavlov

A Russian physiologist whose groundbreaking discovery of classical conditioning in the 1980s was influential in shaping behaviorism. Sometimes referred to as Pavlovian conditioning, classical conditioning was discovered accidentally while Pavlov studied salivation in dogs. Upon realizing the significance of his conditioning discovery, Pavlov spent the rest of his career studying this type of learning.⁷

John B. Watson

An American psychologist who was renowned for formally introducing and popularizing behaviorism. His work in this field was groundbreaking and incredibly influential, establishing behaviorism as the mainstream school of thought in psychology in the mid-1900s. Watson burned a significant amount of his letters and papers, except for some reprints of his academic work, which made it difficult to understand his earlier thoughts on behaviorism.⁸

Burrhus Frederic (B.F.) Skinner

An American psychologist and behaviorist who is commonly referred to as the father of operant conditioning. B.F. Skinner introduced this theory in his 1938 book, The Behavior of Organisms, which was influential in reinforcing behaviorism as a mainstream school of thought in psychology.⁹

Claude Shannon

An American mathematician and computer scientist who was dubbed the ‘father of information theory’ and played a pioneering role in the development of artificial intelligence. His most well-known work was his groundbreaking 1948 paper, A Mathematical Theory of Communication, which introduced the concept of binary digits (bits) as the fundamental unit of information. However, he’s also the creator of Theseus, the maze-solving mouse, which was an early experiment in artificial intelligence and machine learning. 

Joseph Wolpe

South African psychiatrist who was one of the most influential figures in behavioral therapy during the twentieth century. Wolpe’s main area of research was in reciprocal inhibition techniques, a behavioral therapy method based on opposites. The principle is simple: two opposing responses cannot occur at the same time, such as being relaxed and anxious simultaneously. The idea of reciprocal inhibition techniques is to weaken an undesired response (like anxiety) by pairing it with a response that is incompatible with it (like relaxation). 

Edward Tolman

An American psychologist who is best known for developing the concept of purposive behaviorism. His work rejected the stimulus-response model of behaviorism and paved the way for further developments in the field. 

Carl Rogers

Influential American psychologist best known for developing person-centered therapy, a humanistic approach that emphasizes empathy, unconditional positive regard, and the individual's capacity for self-healing. He believed that people thrive in supportive environments where they feel accepted and understood. Rogers’ work profoundly shaped counseling, education, and conflict resolution, and he remains one of the most cited figures in psychology.

Behaviorism’s rise as the mainstream school of psychology in the 1950s enabled researchers to formulate clear predictions about human behavior. As a measurable field, behaviorism enabled researchers to study observable behavior in a scientific way. Because of this, behaviorism has made significant contributions by providing insights into language development, human learning, and moral and gender development, all of which can be explained by conditioning.¹

Education

In the field of education, behaviorism and conditioning have helped teachers better understand how to encourage learning in students. The school system, which rewards children for studying, doing well in tests, and learning new skills, is essentially based on behaviorism. Teachers use conditioning and repetition of observable behavior, in addition to positive reinforcement, to help a student make the association that certain behavior is desirable.¹⁰ For example, a teacher may praise and politely thank students who raise their hands, conditioning students to adopt this behavior.

One modern extension of this behavioral approach is gamified learning platforms, which use game-like elements to reinforce academic progress. Classcraft, an online education platform, blends classic behaviorist techniques with digital engagement approaches. First, students are invited to create digital avatars and earn points by completing various tasks. These might include completing a classroom exercise, collaborating with peers, or demonstrating positive behaviors like helping others or staying focused. These points then unlock in-game rewards or real-world privileges (like homework passes or choosing a class activity), functioning as operant conditioning tools.

Health and fitness 

Another area where behaviorism has arguably been put to good use is health and wellness. Behaviorist principles are widely applied to promote lasting lifestyle changes through structured reinforcement, habit-building, and feedback mechanisms. Wearable technology, such as Fitbits or fitness apps like Strava, incorporates gamified features such as streaks, badges, reminders, and rewards that encourage users to stay consistent and motivated. These apps reinforce desired behaviors, like eating healthy meals, completing a certain number of workouts, or reaching a target number of daily steps, by celebrating progress and providing immediate feedback. This positive reinforcement helps users form and maintain healthy habits through repetition and reward. 

These features can also be incorporated into tools that help users deal with more serious or long-term health challenges. However, as David Klonoff, an endocrinologist from the University of California, San Francisco, argues, behavioral theory is currently underused in the sector. He believes that designing health tools around behavioral science is one of the most promising approaches to increasing patient adherence to treatments for chronic diseases such as diabetes.²⁶ 

There is, however, a dark side to the world of digital health. Dr John Toner, a professor in sports coaching and performance at the University of Hull in the UK, argues that wearables and fitness apps can make us anxious. The apps and tools keep pushing us to meet numbers and metrics but don’t take into account that we’re humans who are susceptible to little niggles, injuries, or tiredness. If we don’t stick to the strict schedule they set for us, we can feel demotivated and like we’re failing. Equally, the social anxiety that comes with constantly comparing yourself to other athletes in your local area or on leaderboards can, over time, take the joy out of the process.²⁷

Marketing 

Modern marketing techniques exploit consumer behavior to drive sales and enhance brand loyalty. Thanks to big data and powerful AI, companies are now able to collect and analyze huge amounts of data about consumers’ purchasing habits, preferences, and daily routines. This information is then used to craft compelling and personalized marketing strategies that keep us engaged with their products and services. 

Emotional marketing, for instance, takes advantage of the fact that consumers tend to make purchasing decisions based not only on practical considerations, but also on emotional responses.²⁵ Brands can build stronger loyalty and engagement by creating emotional connections through storytelling, personalized messaging, and corporate social responsibility. 

A good example of this is Coca-Cola’s “Share a Coke” campaign, where the brand replaced its logo on bottles with popular names, encouraging people to find and share a Coke with friends or loved ones. The campaign tapped into feelings of connection, personalization, and joy, and at the same time created an emotional bond with the brand that went far beyond the product itself.²⁴ However, some argue that while emotional marketing is extremely powerful, there are ethical concerns that it’s manipulative and can lead people to impulse buy things they may not have ever thought about buying.²⁵ 

Finally, as we explore below, behaviorist ideas underpin reinforcement learning in the fields of artificial intelligence and machine learning, where algorithms adapt their responses based on rewards and penalties. 

Critics of behaviorism argue that its one-dimensional approach to understanding human behavior ignores our internal influences. These internal influences are not necessarily observable and can include our feelings, thoughts, desires, motivations, moods, and expectations.¹¹ Sigmund Freud and Carl Rogers were just two notable psychologists who prominently voiced their concerns about behaviorism’s limitations and rigid nature arising from the way it rejects the role one’s personality can play in their behavior.¹²

Some argue that the evidence backing behaviorism in humans is flawed; early evidence supporting behaviorism came from studies involving animals. Applying these findings to humans overlooks the complexity of human behavior, as humans and animals differ physiologically and cognitively. Critics taking this point of view suggest that humans have important social norms and morals which cause us to interact differently with our environment, causing us to behave differently to animals.

Carl Rogers, a believer of humanistic psychology (which proposes humans have free will), rejected the notion that humans and animals can be compared. Rogers believed humans are unique and can make their own decisions, which cannot be compared to those of animals. The principles of behaviorism may be more suited to animals rather than humans.³

Another shortcoming of pure behaviorism is that while it’s sufficient for predicting and controlling behavior, it cannot tell us why that behavior occurred in the first place.²² For that, we need intentionality, which helps us to understand the personal nature and continuation of behaviors. Developed by Edward Tolman in the 1930s, purposive behaviorism rejected John Watson’s stimulus-response behaviorism by considering the purpose or goal of a behavior. 

Tolman conducted several experiments with rats in mazes to demonstrate that learning could occur without direct reinforcement.²³  He placed rats in a maze at point A, and over time, they learned to find food at point B, making fewer errors with each attempt. Tolman proposed that the rats developed cognitive maps—mental representations of the maze—rather than simply learning a pattern of responses. This idea was supported by further tests where, even when starting from a new location (point C), the rats still navigated correctly to the food. This further supported Tolman’s hypothesis that the rodents understood the layout of the maze rather than just reacting to external stimuli. This led to Tolman’s theory of latent learning, which suggests that learning can happen without immediate rewards and can be demonstrated later when needed.

A more contemporary application of cognitive map theory came in 2014 when Norwegian neuroscientists Edvard and May-Britt Moser from the Norwegian University of Science and Technology won the Nobel prize for their research on grid cells. Like Tolman, the scientists tracked the neural responses in rats’ brains while they navigated mazes and demonstrated that spatial information is encoded in our neural networks. Their findings provided strong evidence for an internal “map” of space in the brain.^30,31

Behavioral therapy

Aspects of behaviorism are still applied today in behavioral therapy. Two common types of behavioral therapy include applied behavior analysis (ABA) and cognitive behavioral therapy (CBT).¹³ Both approaches address problematic behaviors and thought practices that stem from learned patterns and environmental influences. 

ABA takes its influence from Skinner’s operant conditioning. That is, the technique uses positive reinforcement to encourage desirable behaviors and reduce harmful or disruptive ones.¹³ This approach is particularly effective when working with individuals with autism and developmental disorders to help develop communication, social, and daily living skills. 

Imagine a child who struggles with making eye contact or following simple instructions. Using positive reinforcement, a therapist will encourage desired behaviors—like saying “hello” or completing a task—by immediately rewarding them with something the child values, such as a favorite toy, praise, or a small treat. Over time, the child will learn to associate these behaviors with positive outcomes, increasing the likelihood that they’ll do them more frequently. 

CBT is a combination of two therapeutic approaches known as cognitive therapy and behavioral therapy. The latter is deeply rooted in behaviorism and assumes that human behavior is learned and can therefore be changed or learned differently.¹⁹ Therapists using CBT will focus on the thoughts behind an individual’s behavior. The goal of behavioral therapy, therefore, is to modify the actions or reactions that negatively impact an individual’s well-being or daily functioning.²⁰ 

A prime example of CBT is systematic desensitization, a treatment for phobias developed by South African psychiatrist Joseph Wolpe in the 1950s. Using the process of “counterconditioning”, the process aims to weaken the association between the stimulus (such as spiders or heights) and the anxiety experienced by the person.²¹ Similar to systematic desensitization, exposure therapy helps individuals confront their fears head-on by gradually increasing the intensity or duration of exposure over time. The goal is to reduce anxiety through repeated, controlled encounters with the feared object or situation, allowing the person to build tolerance and break the cycle of avoidance. CBT is considered by many to be the gold standard in treating disorders such as anxiety, anger issues, and substance abuse and relapse prevention.¹⁴

However, behavioral therapy is not always sufficient for complex mental health conditions. Behavioral therapy can help cope with some aspects of complex conditions, such as severe depression, however, it cannot be used alone.¹⁵ Just like the shortcomings of behaviorism, behavioral therapy overlooks the bigger picture by failing to address the effects that unique situations, interpersonal relationships, and unobservable behaviors can have on a patient.¹⁵

Reinforcement learning in AI 

Behaviorists typically study how biological organisms (such as humans, animals, and plants) behave as a result of their interaction with the environment. Similarly, computer scientists and AI developers apply behaviorist principles to understand how artificial agents need to behave in specific environments to maximize cumulative rewards or minimize cumulative punishment.¹⁷ 

Prompt engineers, who are a bit like digital behaviorists, will use certain stimuli (or prompts) to elicit a desired response from an AI system. If the response aligns with the expected outcome, the system receives a reward or positive reinforcement, encouraging the AI to repeat the behavior or action in similar situations. If the response isn’t what the engineer was looking for, the AI system will receive negative reinforcement. Just like in the world of human education, this is known as reinforcement learning. 

Now, you may be forgiven for thinking that the application of behaviorist principles in AI is something relatively new and firmly in the realms of 21st-century innovation. However, trial-and-error learning (where an agent is either rewarded or punished for behavior) was suggested as a mechanism for developing AI right from the beginning when Alan Turing was exploring the possibility of mechanized, human-style intelligence.¹⁷ 

One of the first demonstrations of the application of behaviorist principles to AI was Theseus, a maze-running mouse. Developed by Claude Shannon in the early 1950s, Theseus was an electromechanical mouse (a 2-inch magnet with three wheels and copper whiskers) that could navigate a maze using a system of relays to "learn" the correct path through trial and error. This experiment mirrors operant conditioning, where behaviors are reinforced based on outcomes. 

Shannon designed the experiment by placing Theseus at the entrance of the maze with a piece of artificial cheese at the exit. Initially, the mouse moved around the maze erratically, colliding with walls and randomly exploring until it eventually stumbled upon the correct path. However, as it moved, sensors tracked every turn and stored the information for later. When Theseus was placed back at the start, it navigated the maze flawlessly, following the learned route without hesitation. While the mouse itself wasn’t truly learning, the underlying system of sensors and telephone relays acted as a memory unit, recording past movements and guiding Theseus by activating magnets beneath the maze to control its path. In other words, it was the environment itself that was learning how to successfully guide the mouse through the maze.¹⁸ 

Reinforcement learning in AI has come a long way since the days of Shannon and his mechanical mouse. Yet one thing has remained the same: our understanding of how humans interact with their environment continues to play a crucial role in shaping how we design and interpret modern AI’s responses to its own environment.

For decades, behavior scientists have carefully studied how organisms interact with their environment, how their actions lead to consequences, and how this cycle helps them adapt and survive over time. The detailed data and insights from these studies could help computer scientists develop artificial agents that can handle more complex tasks and adapt to long-term challenges, much like living organisms do.¹⁷

Phantom Cell Phone Buzzes: A Behavioral Perspective

Have you ever been sure that you felt your phone vibrate in your pocket, or heard your ringtone? But when you pull your phone out, you realize that no one tried to reach you? No, your phone was not acting up. It could be a sign of just how attached you have become to your device. This article investigates whether the excessive use of technology can be considered an addiction.

Why do we work harder when we are promised a reward?

Incentives can be a powerful tool to motivate people to take a certain action, but they can also backfire, resulting in a decrease in one’s motivation instead of increasing it. This article explores the implications of incentivization in our behavior.

Positive Reinforcement

This piece by The Decision Lab explores the consequences and controversies regarding positive reinforcement, a key tool in operant conditioning, which has significant effects on human learning.

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