Negative feedback and positive feedback are fundamental concepts in control systems and regulatory processes across various fields, including biology, engineering, and economics. These mechanisms play crucial roles in maintaining stability, amplifying responses, and achieving desired outcomes.
Feedback systems are mechanisms that allow a system to regulate its behavior by using information about its output to modify its input. These systems are employed in a wide range of applications to maintain stability, achieve desired states, and respond to changes in the environment or input conditions.
There are two primary types of feedback systems: negative feedback and positive feedback. Each type has distinct characteristics and effects on system behavior.
Negative feedback is a regulatory mechanism in which the system responds to a change in its output by producing an effect that opposes the change. In other words, negative feedback acts to reduce deviations from the desired setpoint or reference value. This process helps maintain stability and keep a system within a specific range or around a particular target.
Key Characteristics of Negative Feedback:
Stabilizing Effect: Negative feedback systems work to stabilize the system and minimize deviations from the desired state. They resist and counteract any changes in the system’s output.
Setpoint or Reference Value: Negative feedback systems typically have a setpoint or reference value that represents the desired output. The system continuously compares the actual output to this reference value.
Error Signal: The difference between the actual output and the setpoint is known as the error signal. Negative feedback systems use this error signal to drive corrective actions.
Counteraction: Negative feedback mechanisms respond to the error signal by producing an effect that counteracts the deviation from the setpoint. This effect reduces the error and brings the system back to the desired state.
Examples of Negative Feedback:
a. Thermostat Control
A thermostat in a heating or cooling system is an example of negative feedback. When the temperature deviates from the setpoint (e.g., becomes too cold), the thermostat activates the heating system to warm the environment. As the temperature approaches the setpoint, the thermostat reduces the heating until the temperature stabilizes around the desired level.
b. Human Body Temperature Regulation
The human body maintains a relatively constant core temperature through negative feedback. If the body temperature rises (e.g., due to exercise), sweat production increases, and blood vessels dilate to release heat, bringing the temperature back to the setpoint. If the body temperature falls, shivering and vasoconstriction help raise the temperature.
Positive Feedback
Positive feedback is a regulatory mechanism in which the system responds to a change in its output by amplifying or reinforcing the change. Unlike negative feedback, positive feedback systems tend to push the system further away from its initial state or equilibrium, often leading to exponential growth or dramatic shifts in behavior.
Key Characteristics of Positive Feedback:
Amplifying Effect: Positive feedback systems amplify deviations from the initial state, intensifying the change in the output.
No Setpoint: Unlike negative feedback, positive feedback systems may not have a setpoint or reference value to maintain. They focus on reinforcing and increasing the deviation.
Self-Perpetuating: Positive feedback mechanisms can be self-perpetuating, as the amplified output further increases the input, leading to continuous growth or a significant shift in behavior.
Examples of Positive Feedback:
a. Avalanche Formation
In the case of an avalanche, positive feedback is at play. A small disturbance, such as the movement of a single snowflake, can trigger a cascade effect. As more snow accumulates and starts moving downhill, it picks up additional snow, increasing the force and speed of the avalanche. This process continues until the system reaches a new equilibrium.
b. Childbirth
Positive feedback also occurs during childbirth. As contractions intensify, they stimulate the release of the hormone oxytocin, which, in turn, causes stronger contractions. This cycle continues until the baby is delivered, after which the positive feedback loop is interrupted.
Contrasting Negative and Positive Feedback
To better understand the differences between negative and positive feedback, let’s compare and contrast these two mechanisms:
1. Goal and Effect on Output:
Negative Feedback: The goal of negative feedback is to maintain stability and keep the system’s output close to a specific setpoint or reference value. The effect is to counteract and reduce deviations from this desired state.
Positive Feedback: Positive feedback does not aim to maintain stability or a specific setpoint. Instead, it amplifies deviations from the initial state, pushing the system further away from equilibrium.
2. Response to Deviations:
Negative Feedback: Negative feedback responds to deviations by producing an effect that opposes and reduces the deviation. It works to restore the system to its desired state.
Positive Feedback: Positive feedback responds to deviations by amplifying and reinforcing the deviation. It intensifies the change and drives the system away from its initial state.
3. Stability:
Negative Feedback: Negative feedback promotes stability and helps systems remain within a certain range or around a particular setpoint.
Positive Feedback: Positive feedback can lead to instability and dramatic shifts in behavior or conditions. It tends to drive systems toward new equilibria or extremes.
4. Commonality:
Negative Feedback: Negative feedback is more common and prevalent in systems where stability and regulation are critical, such as homeostasis in living organisms.
Positive Feedback: Positive feedback is less common in everyday systems but can play a significant role in situations where rapid, exponential growth or change is required.
Applications of Negative and Positive Feedback
Both negative and positive feedback mechanisms have applications across various fields:
Applications of Negative Feedback:
a. Temperature Regulation
Negative feedback is used in heating and cooling systems, thermostats, and climate control to maintain stable temperatures.
b. Biological Homeostasis
Negative feedback is crucial in biology for maintaining stable conditions within living organisms, including temperature, blood pressure, and glucose levels.
c. Economic Stabilization
In economics, monetary policy and fiscal policy are examples of negative feedback systems used to stabilize economies and control inflation.
Applications of Positive Feedback:
a. Amplification
Positive feedback is employed in amplifiers, where it is used to increase the amplitude of electrical signals in electronics and telecommunications.
b. Chemical Reactions
Positive feedback can occur in certain chemical reactions, where a small reaction initiates a chain reaction that continues to amplify the process.
c. Oscillations
Positive feedback is used in devices like oscillators, which generate repetitive waveforms and signals in electronics and engineering.
Significance and Conclusion
Understanding the concepts of negative feedback and positive feedback is essential in various fields, including engineering, biology, economics, and environmental science. These feedback mechanisms play critical roles in maintaining stability, regulating systems, and driving change. While negative feedback is more common and often associated with stability and homeostasis, positive feedback can lead to rapid and dramatic transformations in systems. The ability to recognize and utilize these feedback mechanisms is essential for designing effective control systems, addressing dynamic challenges, and achieving desired outcomes in diverse applications.
Key Points:
Feedback Systems Overview: Feedback systems are mechanisms used in various fields to regulate behavior by modifying input based on output information. There are two primary types: negative feedback and positive feedback.
Negative Feedback Characteristics:
Stabilizing Effect: Reduces deviations from the desired state.
Setpoint or Reference Value: Compares actual output to a reference value.
Error Signal: The difference between actual output and the reference value.
Examples: Thermostat control, human body temperature regulation.
Positive Feedback Characteristics:
Amplifying Effect: Intensifies deviations from the initial state.
No Setpoint: Focuses on reinforcing and increasing the deviation.
Self-Perpetuating: Can lead to continuous growth or significant shifts.
Examples: Avalanche formation, childbirth.
Contrasting Negative and Positive Feedback:
Goal and Effect on Output: Negative feedback aims for stability; positive feedback amplifies deviations.
Stability: Negative feedback promotes stability; positive feedback can lead to instability.
Commonality: Negative feedback is more common; positive feedback is less common but can lead to rapid change.
Applications:
Negative Feedback: Used in temperature regulation, biological homeostasis, and economic stabilization.
Positive Feedback: Applied in amplification, certain chemical reactions, and oscillators.
Significance and Conclusion: Understanding negative and positive feedback is crucial in various fields for maintaining stability, regulating systems, and driving change. Recognizing and utilizing these mechanisms are essential for designing effective control systems and achieving desired outcomes.
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.
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 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 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 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.
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 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.
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 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, 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, 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).
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.
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.
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.
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.
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.
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.
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.
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 – 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.
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 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.
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.
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.
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 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 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 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.
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 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.”
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 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 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 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.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
