and problem solving the term rule of thumb refers to

Heuristics: Definition, Examples, And How They Work

Benjamin Frimodig

Science Expert

B.A., History and Science, Harvard University

Ben Frimodig is a 2021 graduate of Harvard College, where he studied the History of Science.

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Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Every day our brains must process and respond to thousands of problems, both large and small, at a moment’s notice. It might even be overwhelming to consider the sheer volume of complex problems we regularly face in need of a quick solution.

While one might wish there was time to methodically and thoughtfully evaluate the fine details of our everyday tasks, the cognitive demands of daily life often make such processing logistically impossible.

Therefore, the brain must develop reliable shortcuts to keep up with the stimulus-rich environments we inhabit. Psychologists refer to these efficient problem-solving techniques as heuristics.

Heuristics can be thought of as general cognitive frameworks humans rely on regularly to reach a solution quickly.

For example, if a student needs to decide what subject she will study at university, her intuition will likely be drawn toward the path that she envisions as most satisfying, practical, and interesting.

She may also think back on her strengths and weaknesses in secondary school or perhaps even write out a pros and cons list to facilitate her choice.

It’s important to note that these heuristics broadly apply to everyday problems, produce sound solutions, and helps simplify otherwise complicated mental tasks. These are the three defining features of a heuristic.

While the concept of heuristics dates back to Ancient Greece (the term is derived from the Greek word for “to discover”), most of the information known today on the subject comes from prominent twentieth-century social scientists.

Herbert Simon’s study of a notion he called “bounded rationality” focused on decision-making under restrictive cognitive conditions, such as limited time and information.

This concept of optimizing an inherently imperfect analysis frames the contemporary study of heuristics and leads many to credit Simon as a foundational figure in the field.

Kahneman’s Theory of Decision Making

The immense contributions of psychologist Daniel Kahneman to our understanding of cognitive problem-solving deserve special attention.

As context for his theory, Kahneman put forward the estimate that an individual makes around 35,000 decisions each day! To reach these resolutions, the mind relies on either “fast” or “slow” thinking.

The fast thinking pathway (system 1) operates mostly unconsciously and aims to reach reliable decisions with as minimal cognitive strain as possible.

While system 1 relies on broad observations and quick evaluative techniques (heuristics!), system 2 (slow thinking) requires conscious, continuous attention to carefully assess the details of a given problem and logically reach a solution.

Given the sheer volume of daily decisions, it’s no surprise that around 98% of problem-solving uses system 1.

Thus, it is crucial that the human mind develops a toolbox of effective, efficient heuristics to support this fast-thinking pathway.

Heuristics vs. Algorithms

Those who’ve studied the psychology of decision-making might notice similarities between heuristics and algorithms. However, remember that these are two distinct modes of cognition.

Heuristics are methods or strategies which often lead to problem solutions but are not guaranteed to succeed.

They can be distinguished from algorithms, which are methods or procedures that will always produce a solution sooner or later.

An algorithm is a step-by-step procedure that can be reliably used to solve a specific problem. While the concept of an algorithm is most commonly used in reference to technology and mathematics, our brains rely on algorithms every day to resolve issues (Kahneman, 2011).

The important thing to remember is that algorithms are a set of mental instructions unique to specific situations, while heuristics are general rules of thumb that can help the mind process and overcome various obstacles.

For example, if you are thoughtfully reading every line of this article, you are using an algorithm.

On the other hand, if you are quickly skimming each section for important information or perhaps focusing only on sections you don’t already understand, you are using a heuristic!

Why Heuristics Are Used

Heuristics usually occurs when one of five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind at the same moment

When studying heuristics, keep in mind both the benefits and unavoidable drawbacks of their application. The ubiquity of these techniques in human society makes such weaknesses especially worthy of evaluation.

More specifically, in expediting decision-making processes, heuristics also predispose us to a number of cognitive biases .

A cognitive bias is an incorrect but pervasive judgment derived from an illogical pattern of cognition. In simple terms, a cognitive bias occurs when one internalizes a subjective perception as a reliable and objective truth.

Heuristics are reliable but imperfect; In the application of broad decision-making “shortcuts” to guide one’s response to specific situations, occasional errors are both inevitable and have the potential to catalyze persistent mistakes.

For example, consider the risks of faulty applications of the representative heuristic discussed above. While the technique encourages one to assign situations into broad categories based on superficial characteristics and one’s past experiences for the sake of cognitive expediency, such thinking is also the basis of stereotypes and discrimination.

In practice, these errors result in the disproportionate favoring of one group and/or the oppression of other groups within a given society.

Indeed, the most impactful research relating to heuristics often centers on the connection between them and systematic discrimination.

The tradeoff between thoughtful rationality and cognitive efficiency encompasses both the benefits and pitfalls of heuristics and represents a foundational concept in psychological research.

When learning about heuristics, keep in mind their relevance to all areas of human interaction. After all, the study of social psychology is intrinsically interdisciplinary.

Many of the most important studies on heuristics relate to flawed decision-making processes in high-stakes fields like law, medicine, and politics.

Researchers often draw on a distinct set of already established heuristics in their analysis. While dozens of unique heuristics have been observed, brief descriptions of those most central to the field are included below:

Availability Heuristic

The availability heuristic describes the tendency to make choices based on information that comes to mind readily.

For example, children of divorced parents are more likely to have pessimistic views towards marriage as adults.

Of important note, this heuristic can also involve assigning more importance to more recently learned information, largely due to the easier recall of such information.

Representativeness Heuristic

This technique allows one to quickly assign probabilities to and predict the outcome of new scenarios using psychological prototypes derived from past experiences.

For example, juries are less likely to convict individuals who are well-groomed and wearing formal attire (under the assumption that stylish, well-kempt individuals typically do not commit crimes).

This is one of the most studied heuristics by social psychologists for its relevance to the development of stereotypes.

Scarcity Heuristic

This method of decision-making is predicated on the perception of less abundant, rarer items as inherently more valuable than more abundant items.

We rely on the scarcity heuristic when we must make a fast selection with incomplete information. For example, a student deciding between two universities may be drawn toward the option with the lower acceptance rate, assuming that this exclusivity indicates a more desirable experience.

The concept of scarcity is central to behavioral economists’ study of consumer behavior (a field that evaluates economics through the lens of human psychology).

Trial and Error

This is the most basic and perhaps frequently cited heuristic. Trial and error can be used to solve a problem that possesses a discrete number of possible solutions and involves simply attempting each possible option until the correct solution is identified.

For example, if an individual was putting together a jigsaw puzzle, he or she would try multiple pieces until locating a proper fit.

This technique is commonly taught in introductory psychology courses due to its simple representation of the central purpose of heuristics: the use of reliable problem-solving frameworks to reduce cognitive load.

Anchoring and Adjustment Heuristic

Anchoring refers to the tendency to formulate expectations relating to new scenarios relative to an already ingrained piece of information.

Put simply, this anchoring one to form reasonable estimations around uncertainties. For example, if asked to estimate the number of days in a year on Mars, many people would first call to mind the fact the Earth’s year is 365 days (the “anchor”) and adjust accordingly.

This tendency can also help explain the observation that ingrained information often hinders the learning of new information, a concept known as retroactive inhibition.

Familiarity Heuristic

This technique can be used to guide actions in cognitively demanding situations by simply reverting to previous behaviors successfully utilized under similar circumstances.

The familiarity heuristic is most useful in unfamiliar, stressful environments.

For example, a job seeker might recall behavioral standards in other high-stakes situations from her past (perhaps an important presentation at university) to guide her behavior in a job interview.

Many psychologists interpret this technique as a slightly more specific variation of the availability heuristic.

How to Make Better Decisions

Heuristics are ingrained cognitive processes utilized by all humans and can lead to various biases.

Both of these statements are established facts. However, this does not mean that the biases that heuristics produce are unavoidable. As the wide-ranging impacts of such biases on societal institutions have become a popular research topic, psychologists have emphasized techniques for reaching more sound, thoughtful and fair decisions in our daily lives.

Ironically, many of these techniques are themselves heuristics!

To focus on the key details of a given problem, one might create a mental list of explicit goals and values. To clearly identify the impacts of choice, one should imagine its impacts one year in the future and from the perspective of all parties involved.

Most importantly, one must gain a mindful understanding of the problem-solving techniques used by our minds and the common mistakes that result. Mindfulness of these flawed yet persistent pathways allows one to quickly identify and remedy the biases (or otherwise flawed thinking) they tend to create!

Further Information

• Shah, A. K., & Oppenheimer, D. M. (2008). Heuristics made easy: an effort-reduction framework. Psychological bulletin, 134(2), 207.
• Marewski, J. N., & Gigerenzer, G. (2012). Heuristic decision making in medicine. Dialogues in clinical neuroscience, 14(1), 77.
• Del Campo, C., Pauser, S., Steiner, E., & Vetschera, R. (2016). Decision making styles and the use of heuristics in decision making. Journal of Business Economics, 86(4), 389-412.

What is a heuristic in psychology?

A heuristic in psychology is a mental shortcut or rule of thumb that simplifies decision-making and problem-solving. Heuristics often speed up the process of finding a satisfactory solution, but they can also lead to cognitive biases.

Bobadilla-Suarez, S., & Love, B. C. (2017, May 29). Fast or Frugal, but Not Both: Decision Heuristics Under Time Pressure. Journal of Experimental Psychology: Learning, Memory, and Cognition .

Bowes, S. M., Ammirati, R. J., Costello, T. H., Basterfield, C., & Lilienfeld, S. O. (2020). Cognitive biases, heuristics, and logical fallacies in clinical practice: A brief field guide for practicing clinicians and supervisors. Professional Psychology: Research and Practice, 51 (5), 435–445.

Dietrich, C. (2010). “Decision Making: Factors that Influence Decision Making, Heuristics Used, and Decision Outcomes.” Inquiries Journal/Student Pulse, 2(02).

Groenewegen, A. (2021, September 1). Kahneman Fast and slow thinking: System 1 and 2 explained by Sue. SUE Behavioral Design. Retrieved March 26, 2022, from https://suebehaviouraldesign.com/kahneman-fast-slow-thinking/

Kahneman, D., Lovallo, D., & Sibony, O. (2011). Before you make that big decision .

Kahneman, D. (2011). Thinking, fast and slow . Macmillan.

Pratkanis, A. (1989). The cognitive representation of attitudes. In A. R. Pratkanis, S. J. Breckler, & A. G. Greenwald (Eds.), Attitude structure and function (pp. 71–98). Hillsdale, NJ: Erlbaum.

Simon, H.A., 1956. Rational choice and the structure of the environment. Psychological Review .

Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185 (4157), 1124–1131.

Heuristics: The Psychology of Mental Shortcuts

• Archaeology
• Ph.D., Materials Science and Engineering, Northwestern University
• B.A., Chemistry, Johns Hopkins University
• B.A., Cognitive Science, Johns Hopkins University

Heuristics (also called “mental shortcuts” or “rules of thumb") are efficient mental processes that help humans solve problems and learn new concepts. These processes make problems less complex by ignoring some of the information that’s coming into the brain, either consciously or unconsciously. Today, heuristics have become an influential concept in the areas of judgment and decision-making.

Key Takeaways: Heuristics

• Heuristics are efficient mental processes (or "mental shortcuts") that help humans solve problems or learn a new concept.
• In the 1970s, researchers Amos Tversky and Daniel Kahneman identified three key heuristics: representativeness, anchoring and adjustment, and availability.
• The work of Tversky and Kahneman led to the development of the heuristics and biases research program.

History and Origins

Gestalt psychologists postulated that humans solve problems and perceive objects based on heuristics. In the early 20th century, the psychologist Max Wertheimer identified laws by which humans group objects together into patterns (e.g. a cluster of dots in the shape of a rectangle).

The heuristics most commonly studied today are those that deal with decision-making. In the 1950s, economist and political scientist Herbert Simon published his A Behavioral Model of Rational Choice , which focused on the concept of on bounded rationality : the idea that people must make decisions with limited time, mental resources, and information.

In 1974, psychologists Amos Tversky and Daniel Kahneman pinpointed specific mental processes used to simplify decision-making. They showed that humans rely on a limited set of heuristics when making decisions with information about which they are uncertain—for example, when deciding whether to exchange money for a trip overseas now or a week from today. Tversky and Kahneman also showed that, although heuristics are useful, they can lead to errors in thinking that are both predictable and unpredictable.

In the 1990s, research on heuristics, as exemplified by the work of Gerd Gigerenzer’s research group, focused on how factors in the environment impact thinking–particularly, that the strategies the mind uses are influenced by the environment–rather than the idea that the mind uses mental shortcuts to save time and effort.

Significant Psychological Heuristics

Tversky and Kahneman’s 1974 work, Judgment under Uncertainty: Heuristics and Biases , introduced three key characteristics: representativeness, anchoring and adjustment, and availability. 

The  representativeness  heuristic allows people to judge the likelihood that an object belongs in a general category or class based on how similar the object is to members of that category.

To explain the representativeness heuristic, Tversky and Kahneman provided the example of an individual named Steve, who is “very shy and withdrawn, invariably helpful, but with little interest in people or reality. A meek and tidy soul, he has a need for order and structure, and a passion for detail.” What is the probability that Steve works in a specific occupation (e.g. librarian or doctor)? The researchers concluded that, when asked to judge this probability, individuals would make their judgment based on how similar Steve seemed to the stereotype of the given occupation.

The anchoring and adjustment heuristic allows people to estimate a number by starting at an initial value (the “anchor”) and adjusting that value up or down. However, different initial values lead to different estimates, which are in turn influenced by the initial value.

To demonstrate the anchoring and adjustment heuristic, Tversky and Kahneman asked participants to estimate the percentage of African countries in the UN. They found that, if participants were given an initial estimate as part of the question (for example, is the real percentage higher or lower than 65%?), their answers were rather close to the initial value, thus seeming to be "anchored" to the first value they heard.

The availability heuristic allows people to assess how often an event occurs or how likely it will occur, based on how easily that event can be brought to mind. For example, someone might estimate the percentage of middle-aged people at risk of a heart attack by thinking of the people they know who have had heart attacks.

Tversky and Kahneman's findings led to the development of the heuristics and biases research program. Subsequent works by researchers have introduced a number of other heuristics.

The Usefulness of Heuristics

There are several theories for the usefulness of heuristics. The  accuracy-effort trade-off   theory  states that humans and animals use heuristics because processing every piece of information that comes into the brain takes time and effort. With heuristics, the brain can make faster and more efficient decisions, albeit at the cost of accuracy. 

Some suggest that this theory works because not every decision is worth spending the time necessary to reach the best possible conclusion, and thus people use mental shortcuts to save time and energy. Another interpretation of this theory is that the brain simply does not have the capacity to process everything, and so we  must  use mental shortcuts.

Another explanation for the usefulness of heuristics is the  ecological rationality theory. This theory states that some heuristics are best used in specific environments, such as uncertainty and redundancy. Thus, heuristics are particularly relevant and useful in specific situations, rather than at all times.

• Gigerenzer, G., and Gaissmeier, W. “Heuristic decision making.” Annual Review of Psychology , vol. 62, 2011, pp. 451-482.
• Hertwig, R., and Pachur, T. “Heuristics, history of.” In International Encyclopedia of the Social & Behavioral Sciences, 2 Edition nd , Elsevier, 2007.
• “Heuristics representativeness.” Cognitive Consonance.
• Simon. H. A. “A behavioral model of rational choice.” The Quarterly Journal of Economics , vol. 69, no. 1, 1955, pp. 99-118.
• Tversky, A., and Kahneman, D. “Judgment under uncertainty: Heuristics and biases.” Science , vol. 185, no. 4157, pp. 1124-1131.
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What are heuristics and how do they help us make decisions?

Heuristics are simple rules of thumb that our brains use to make decisions. When you choose a work outfit that looks professional instead of sweatpants, you’re making a decision based on past information. That's not intuition; it’s heuristics. Instead of weighing all the information available to make a data-backed choice, heuristics enable us to move quickly into action—mostly without us even realizing it. In this article, you’ll learn what heuristics are, their common types, and how we use them in different scenarios.

Green means go. Most of us accept this as common knowledge, but it’s actually an example of a micro-decision—in this case, your brain is deciding to go when you see the color green.

You make countless of these subconscious decisions every day. Many things that you might think just come naturally to you are actually caused by heuristics—mental shortcuts that allow you to quickly process information and take action. Heuristics help you make smaller, almost unnoticeable decisions using past information, without much rational input from your brain.

Heuristics are helpful for getting things done more quickly, but they can also lead to biases and irrational choices if you’re not aware of them. Luckily, you can use heuristics to your advantage once you recognize them, and make better decisions in the workplace.

What is a heuristic?

Heuristics are mental shortcuts that your brain uses to make decisions. When we make rational choices, our brains weigh all the information, pros and cons, and any relevant data. But it’s not possible to do this for every single decision we make on a day-to-day basis. For the smaller ones, your brain uses heuristics to infer information and take almost-immediate action.

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How heuristics work

For example, if you’re making a larger decision about whether to accept a new job or stay with your current one, your brain will process this information slowly. For decisions like this, you collect data by referencing sources—chatting with mentors, reading company reviews, and comparing salaries. Then, you use that information to make your decision. Meanwhile, your brain is also using heuristics to help you speed along that track. In this example, you might use something called the “availability heuristic” to reference things you’ve recently seen about the new job. The availability heuristic makes it more likely that you’ll remember a news story about the company’s higher stock prices. Without realizing it, this can make you think the new job will be more lucrative.

On the flip side, you can recognize that the new job has had some great press recently, but that might be just a great PR team at work. Instead of “buying in” to what the availability heuristic is trying to tell you—that positive news means it’s the right job—you can acknowledge that this is a bias at work. In this case, comparing compensation and work-life balance between the two companies is a much more effective way to choose which job is right for you.

History of heuristics

The term "heuristics," originating from the Greek word meaning “to discover,” has ancient roots, but much of today's understanding comes from twentieth-century social scientists. Herbert Simon's research into "bounded rationality" highlighted the use of heuristics in decision-making, particularly under constraints like limited time and information.

Daniel Kahneman was one of the first researchers to study heuristics in his behavioral economics work in the 1970’s, along with fellow psychologist Amos Tversky. They theorized that many of the decisions and judgments we make aren’t rational—meaning we don’t move through a series of decision-making steps to come to a solution. Instead, the human brain uses mental shortcuts to form seemingly irrational, “fast and frugal” decisions—quick choices that don’t require a lot of mental energy.

Kahneman’s work showed that heuristics lead to systematic errors (or biases), which act as the driving force for our decisions. He was able to apply this research to economic theory, leading to the formation of behavioral economics and a Nobel Prize for Kahneman in 2002.

In the years since, the study of heuristics has grown in popularity with economists and in cognitive psychology. Gerd Gigerenzer’s research , for example, challenges the idea that heuristics lead to errors or flawed thinking. He argues that heuristics are actually indicators that human beings are able to make decisions more effectively without following the traditional rules of logic. His research seems to indicate that heuristics lead us to the right answer most of the time.

Types of heuristics

Heuristics are everywhere, whether we notice them or not. There are hundreds of heuristics at play in the human brain, and they interact with one another constantly. To understand how these heuristics can help you, start by learning some of the more common types of heuristics.

Recognition heuristic

The recognition heuristic uses what we already know (or recognize) as a criterion for decisions. The concept is simple: When faced with two choices, you’re more likely to choose the item you recognize versus the one you don’t.

This is the very base-level concept behind branding your business, and we see it in all well-known companies. Businesses develop a brand messaging strategy in the hopes that when you’re faced with buying their product or buying someone else's, you recognize their product, have a positive association with it, and choose that one. For example, if you’re going to grab a soda and there are two different cans in the fridge, one a Coca-Cola, and the other a soda you’ve never heard of, you are more likely to choose the Coca-Cola simply because you know the name.

Familiarity heuristic

The familiarity heuristic is a mental shortcut where individuals prefer options or information that is familiar to them. This heuristic is based on the notion that familiar items are seen as safer or superior. It differs from the recognition heuristic, which relies solely on whether an item is recognized. The familiarity heuristic involves a deeper sense of comfort and understanding, as opposed to just recognizing something.

An example of this heuristic is seen in investment decisions. Investors might favor well-known companies over lesser-known ones, influenced more by brand familiarity than by an objective assessment of the investment's potential. This tendency showcases how the familiarity heuristic can lead to suboptimal choices, as it prioritizes comfort and recognition over a thorough evaluation of all available options.

Availability heuristic

The availability heuristic is a cognitive bias where people judge the frequency or likelihood of events based on how easily similar instances come to mind. This mental shortcut depends on the most immediate examples that pop into one's mind when considering a topic or decision. The ease of recalling these instances often leads to a distorted perception of their actual frequency, as recent, dramatic, or emotionally charged memories tend to be more memorable.

A notable example of the availability heuristic is the public's reaction to shark attacks. When the media reports on shark attacks, these incidents become highly memorable due to their dramatic nature, leading people to overestimate the risk of such events. This heightened perception is despite statistical evidence showing the rarity of shark attacks. The result is an exaggerated fear and a skewed perception of the actual danger of swimming in the ocean.

Representativeness heuristic

The representativeness heuristic is when we try to assign an object to a specific category or idea based on past experiences. Oftentimes, this comes up when we meet people—our first impression. We expect certain things (such as clothing and credentials) to indicate that a person behaves or lives a certain way.

Without proper awareness, this heuristic can lead to discrimination in the workplace. For example, representativeness heuristics might lead us to believe that a job candidate from an Ivy League school is more qualified than one from a state university, even if their qualifications show us otherwise. This is because we expect Ivy League graduates to act a certain way, such as by being more hard-working or intelligent. Of course, in our rational brains, we know this isn’t the case. That’s why it’s important to be aware of this heuristic, so you can use logical thinking to combat potential biases.

Anchoring and adjustment heuristic

Used in finance for economic forecasting, anchoring and adjustment is when you start with an initial piece of information (the anchor) and continue adjusting until you reach an acceptable decision. The challenge is that sometimes the anchor ends up not being a good enough value to begin with. In other words, you choose the anchor based on unknown biases and then make further decisions based on this faulty assumption.

Anchoring and adjustment are often used in pricing, especially with SaaS companies. For example, a displayed, three-tiered pricing model shows you how much you get for each price point. The layout is designed to make it look like you won’t get much for the lower price, and you don’t necessarily need the highest price, so you choose the mid-level option (the original target). The anchors are the low price (suggesting there’s not much value here) and the high price (which shows that you’re getting a "discount" if you choose another option). Thanks to those two anchors, you feel like you’re getting a lot of value, no matter what you spend.

Affect heuristic

You know the advice; think with your heart. That’s the affect heuristic in action, where you make a decision based on what you’re feeling. Emotions are important ways to understand the world around us, but using them to make decisions is irrational and can impact your work.

For example, let’s say you’re about to ask your boss for a promotion. As a product marketer, you’ve made a huge impact on the company by helping to build a community of enthusiastic, loyal customers. But the day before you have your performance review , you find out that a small project you led for a new product feature failed. You decide to skip the conversation asking for a raise and instead double down on how you can improve.

In this example, you’re using the affect heuristic to base your entire performance on the failure of one small project—even though the rest of your performance (building that profitable community) is much more impactful than a new product feature. If you weighed the options rationally, you would see that asking for a raise is still a logical choice. But instead, the fear of asking for a raise after a failure felt like too big a trade-off.

Satisficing

Satisficing is when you accept an available option that’s satisfactory (i.e., just fine) instead of trying to find the best possible solution. In other words, you’re settling. This creates a “bounded rationality,” where you’re constrained by the choices that are good-enough, instead of pushing past the limits to discover more. This isn’t always negative—for lower-impact scenarios, it might not make sense to invest time and energy into finding the optimal choice. But there are also times when this heuristic kicks in and you end up settling for less than what’s possible.

For example, let’s say you’re a project manager planning the budget for the next fiscal year. Instead of looking at previous spend and revenue, you satisfice and base the budget off projections, assuming that will be good enough. But without factoring in historical data, your budget isn’t going to be as equipped to manage hiccups or unexpected changes. In this case, you can mitigate satisficing with a logically-based data review that, while longer, will produce a more accurate and thoughtful budget plan.

Trial and error heuristic

The trial and error heuristic is a problem-solving method where solutions are found through repeated experimentation. It's used when a clear path to the solution isn't known, relying on iterative learning from failures and adjustments.

For example, a chef might experiment with various ingredient combinations and techniques to perfect a new recipe. Each attempt informs the next, demonstrating how trial and error facilitates discovery in situations without formal guidelines.

Pros and cons of heuristics

Heuristics are effective at helping you get more done quickly, but they also have downsides. Psychologists don’t necessarily agree on whether heuristics and biases are positive or negative. But the argument seems to boil down to these two pros and cons:

Heuristics pros:

Simple heuristics reduce cognitive load, allowing you to accomplish more in less time with fast and frugal decisions. For example, the satisficing heuristic helps you find a "good enough" choice. So if you’re making a complex decision between whether to cut costs or invest in employee well-being , you can use satisficing to find a solution that’s a compromise. The result might not be perfect, but it allows you to take action and get started—you can always adjust later on.

Heuristics cons:

Heuristics create biases. While these cognitive biases enable us to make rapid-fire decisions, they can also lead to rigid, unhelpful beliefs. For example, confirmation bias makes it more likely that you’ll seek out other opinions that agree with your own. This makes it harder to keep an open mind, hear from the other side, and ultimately change your mind—which doesn’t help you build the flexibility and adaptability so important for succeeding in the workplace.

Heuristics and psychology

Heuristics play a pivotal role in psychology, especially in understanding how people make decisions within their cognitive limitations. These mental shortcuts allow for quicker decisions, often necessary in a fast-paced world, but they can sometimes lead to errors in judgment.

The study of heuristics bridges various aspects of psychology, from cognitive processes to behavioral outcomes, and highlights the balance between efficient decision-making and the potential for bias.

Stereotypes and heuristic thinking

Stereotypes are a form of heuristic where individuals make assumptions based on group characteristics, a process analyzed in both English and American psychology.

While these generalizations can lead to rapid conclusions and rational decisions under certain circumstances, they can also oversimplify complex human behaviors and contribute to prejudiced attitudes. Understanding stereotypes as a heuristic offers insight into the cognitive limitations of the human mind and their impact on social perceptions and interactions.

How heuristics lead to bias

Because heuristics rely on shortcuts and stereotypes, they can often lead to bias. This is especially true in scenarios where cognitive limitations restrict the processing of all relevant information. So how do you combat bias? If you acknowledge your biases, you can usually undo them and maybe even use them to your advantage. There are ways you can hack heuristics, so that they work for you (not against you):

Be aware. Heuristics often operate like a knee-jerk reaction—they’re automatic. The more aware you are, the more you can identify and acknowledge the heuristic at play. From there, you can decide if it’s useful for the current situation, or if a logical decision-making process is best.

Flip the script. When you notice a negative bias, turn it around. For example, confirmation bias is when we look for things to be as we expect. So if we expect our boss to assign us more work than our colleagues, we might always experience our work tasks as unfair. Instead, turn this around by repeating that your boss has your team’s best interests at heart, and you know everyone is working hard. This will re-train your confirmation bias to look for all the ways that your boss is treating you just like everyone else.

Practice mindfulness. Mindfulness helps to build self-awareness, so you know when heuristics are impacting your decisions. For example, when we tap into the empathy gap heuristic, we’re unable to empathize with someone else or a specific situation. However, if we’re mindful, we can be aware of how we’re feeling before we engage. This helps us to see that the judgment stems from our own emotions and probably has nothing to do with the other person.

Examples of heuristics in business

This is all well and good in theory, but how do heuristic decision-making and thought processes show up in the real world? One reason researchers have invested so much time and energy into learning about heuristics is so that they can use them, like in these scenarios:

How heuristics are used in marketing

Effective marketing does so much for a business—it attracts new customers, makes a brand a household name, and converts interest into sales, to name a few. One way marketing teams are able to accomplish all this is by applying heuristics.

Let’s use ambiguity aversion as an example. Ambiguity aversion means you're less likely to choose an item you don’t know. Marketing teams combat this by working to become familiar to their customers. This could include the social media team engaging in a more empathetic or conversational way, or employing technology like chat-bots to show that there’s always someone available to help. Making the business feel more approachable helps the customer feel like they know the brand personally—which lessens ambiguity aversion.

How heuristics are used in business strategy

Have you ever noticed how your CEO seems to know things before they happen? Or that the CFO listens more than they speak? These are indications that they understand people in a deeper way, and are able to engage with their employees and predict outcomes because of it. C-suite level executives are often experts in behavioral science, even if they didn’t study it. They tend to get what makes people tick, and know how to communicate based on these biases. In short, they use heuristics for higher-level decision-making processes and execution. 

This includes business strategy . For example, a startup CEO might be aware of their representativeness bias towards investors—they always look for the person in the room with the  fancy suit or car. But after years in the field, they know logically that this isn’t always true—plenty of their investors have shown up in shorts and sandals. Now, because they’re aware of their bias, they can build it into their investment strategy. Instead of only attending expensive, luxury events, they also attend conferences with like-minded individuals and network among peers. This approach can lead them to a greater variety of investors and more potential opportunities.

Heuristics vs algorithms

Heuristics and algorithms are both used by the brain to reduce the mental effort of decision-making, but they operate a bit differently. Algorithms act as guidelines for specific scenarios. They have a structured process designed to solve that specific problem. Heuristics, on the other hand, are general rules of thumb that help the brain process information and may or may not reach a solution.

For example, let's say you’re cooking a well-loved family recipe. You know the steps inside and out, and you no longer need to reference the instructions. If you’re following a recipe step-by-step, you’re using an algorithm. If, however, you decide on a whim to sub in some of your fresh garden vegetables because you think it will taste better, you’re using a heuristic.

How to use heuristics to make better decisions

Heuristics can help us make decisions quickly and with less cognitive strain. While they can be efficient, they sometimes lead to errors in judgment. Understanding how to use heuristics effectively can improve decision-making, especially in complex or uncertain situations.

Take time to think

Rushing often leads to reliance on automatic heuristics, which might not always be suitable. To make better decisions, slow down your thinking process. Take a step back, breathe, and allow yourself a moment of distraction. This pause can provide a fresh perspective and help you notice details or angles you might have missed initially.

Clarify your objectives

When making a decision, it's important to understand the ultimate goal. Our automatic decision-making processes tend to favor immediate benefits, sometimes overlooking long-term impacts or the needs of others involved. Consider the broader implications of your decision. Who else is affected? Is there a common objective that benefits all parties? Such considerations can lead to more holistic and effective decisions.

Manage your emotional influences

Emotions significantly influence our decision-making, often without our awareness. Fast decisions are particularly prone to emotional biases. Acknowledge your feelings, but also separate them from the facts at hand. Are you making a decision based on solid information or emotional reactions? Distinguishing between the two can lead to more rational and balanced choices.

Beware of binary thinking

All-or-nothing thinking is a common heuristic trap, where we see decisions as black or white with no middle ground. However, real-life decisions often have multiple paths and possibilities. It's important to recognize this complexity. There might be compromises or alternative options that weren't initially considered. By acknowledging the spectrum of possibilities, you can make more nuanced and effective decisions.

Heuristic FAQs

What is heuristic thinking.

Heuristic thinking refers to a method of problem-solving, learning, or discovery that employs a practical approach—often termed a "rule of thumb"—to make decisions quickly. Heuristic thinking is a type of cognition that humans use subconsciously to make decisions and judgments with limited time.

What is a heuristic evaluation?

A heuristic evaluation is a usability inspection method used in the fields of user interface (UI) and user experience (UX) design. It involves evaluators examining the interface and judging its compliance with recognized usability principles, known as heuristics. These heuristics serve as guidelines to identify usability problems in a design, making the evaluation process more systematic and comprehensive.

What are computer heuristics?

Computer heuristics are algorithms used to solve complex problems or make decisions where an exhaustive search is impractical. In fields like artificial intelligence and cybersecurity, these heuristic methods allow for efficient problem-solving and decision-making, often based on trial and error or rule-of-thumb strategies.

What are heuristics in psychology?

In psychology, heuristics are quick mental rules for making decisions. They are important in social psychology for understanding how we think and decide. Figures like Kahneman and Tversky, particularly in their work "Judgment Under Uncertainty: Heuristics and Biases," have influenced the study of heuristics in psychology.

Learn heuristics, de-mystify your brain

Your brain doesn’t actually work in mysterious ways. In reality, researchers know why we do a lot of the things we do. Heuristics help us to understand the choices we make that don’t make much sense. Once you understand heuristics, you can also learn to use them to your advantage—both in business, and in life. 

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Why do we take mental shortcuts?

What are heuristics.

Heuristics are mental shortcuts that can facilitate problem-solving and probability judgments. These strategies are generalizations, or rules-of-thumb, that reduce cognitive load. They can be effective for making immediate judgments, however, they often result in irrational or inaccurate conclusions.

Where this bias occurs

Debias your organization.

Most of us work & live in environments that aren’t optimized for solid decision-making. We work with organizations of all kinds to identify sources of cognitive bias & develop tailored solutions.

We use heuristics in all sorts of situations. One type of heuristic, the availability heuristic , often happens when we’re attempting to judge the frequency with which a certain event occurs. Say, for example, someone asked you whether more tornadoes occur in Kansas or Nebraska. Most of us can easily call to mind an example of a tornado in Kansas: the tornado that whisked Dorothy Gale off to Oz in Frank L. Baum’s The Wizard of Oz . Although it’s fictional, this example comes to us easily. On the other hand, most people have a lot of trouble calling to mind an example of a tornado in Nebraska. This leads us to believe that tornadoes are more common in Kansas than in Nebraska. However, the states actually report similar levels. 1

Individual effects

The thing about heuristics is that they aren’t always wrong. As generalizations, there are many situations where they can yield accurate predictions or result in good decision-making. However, even if the outcome is favorable, it was not achieved through logical means. When we use heuristics, we risk ignoring important information and overvaluing what is less relevant. There’s no guarantee that using  heuristics will work out and, even if it does, we’ll be making the decision for the wrong reason. Instead of basing it on reason, our behavior is resulting from a mental shortcut with no real rationale to support it.

Systemic effects

Heuristics become more concerning when applied to politics, academia, and economics. We may all resort to heuristics from time to time, something that is true even of members of important institutions who are tasked with making large, influential decisions. It is necessary for these figures to have a comprehensive understanding of the biases and heuristics that can affect our behavior, so as to promote accuracy on their part.

How it affects product

Heuristics can be useful in product design. Specifically, because heuristics are intuitive to us, they can be applied to create a more user-friendly experience and one that is more valuable to the customer. For example, color psychology is a phenomenon explaining how our experiences with different colors and color families can prime certain emotions or behaviors. Taking advantage of the representativeness heuristic, one could choose to use passive colors (blue or green) or more active colors (red, yellow, orange) depending on the goals of the application or product. 18 For example, if a developer is trying to evoke a feeling of calm for their app that provides guided meditations, they may choose to make the primary colors of the program light blues and greens. Colors like red and orange are more emotionally energizing and may be useful in settings like gyms or crossfit programs. 

By integrating heuristics into products we can enhance the user experience. If an application, device, or item includes features that make it feel intuitive, easy to navigate and familiar, customers will be more inclined to continue to use it and recommend it to others. Appealing to those mental shortcuts we can minimize the chances of user error or frustration with a product that is overly complicated.

Heuristics and AI

Artificial intelligence and machine learning tools already use the power of heuristics to inform its output. In a nutshell, simple AI tools operate based on a set of built in rules and sometimes heuristics! These are encoded within the system thus aiding in decision-making and the presentation of learning material. Heuristic algorithms can be used to solve advanced computational problems, providing efficient and approximate solutions.  Like in humans, the use of heuristics can result in error, and thus must be used with caution. However, machine learning tools and AI can be useful in supporting human decision-making, especially when clouded by emotion, bias or irrationality due to our own susceptibility to heuristics. 

Why it happens

In their paper “Judgment Under Uncertainty: Heuristics and Biases” 2 , Daniel Kahneman and Amos Tversky identified three different kinds of heuristics: availability, representativeness, as well as anchoring and adjustment. Each type of heuristic is used for the purpose of reducing the mental effort needed to make a decision, but they occur in different contexts.

Availability heuristic

The availability heuristic, as defined by Kahneman and Tversky, is the mental shortcut used for making frequency or probability judgments based on “the ease with which instances or occurrences can be brought to mind”. 3 This was touched upon in the previous example, judging the frequency with which tornadoes occur in Kansas relative to Nebraska. 3

The availability heuristic occurs because certain memories come to mind more easily than others. In Kahneman and Tversky’s example participants were asked if more words in the English language start with the letter K or have K as the third letter  Interestingly, most participants responded with the former when in actuality, it is the latter that is true. The idea being that it is much more difficult to think of words that have K as the third letter than it is to think of words that start with K. 4 In this case,  words that begin with K are more readily available to us than words with the K as the third letter.

Representativeness heuristic

Individuals tend to classify events into categories, which, as illustrated by Kahneman and Tversky, can result in our use of the representativeness heuristic. When we use this heuristic, we categorize events or objects based on how they relate to instances we are already familiar with.  Essentially, we have built our own categories, which we use to make predictions about novel situations or people. 5 For example, if someone we meet in one of our university lectures looks and acts like what we believe to be a stereotypical medical student, we may judge the probability that they are studying medicine as highly likely, even without any hard evidence to support that assumption.

The representativeness heuristic is associated with prototype theory. 6 This prominent theory in cognitive science, the prototype theory explains object and identity recognition. It suggests that we categorize different objects and identities in our memory. For example, we may have a category for chairs, a category for fish, a category for books, and so on. Prototype theory posits that we develop prototypical examples for these categories by averaging every example of a given category we encounter. As such, our prototype of a chair should be the most average example of a chair possible, based on our experience with that object. This process aids in object identification because we compare every object we encounter against the prototypes stored in our memory. The more the object resembles the prototype, the more confident we are that it belongs in that category. 

Prototype theory may give rise to the representativeness heuristic as it is in situations when a particular object or event is viewed as similar to the prototype stored in our memory, which leads us to classify the object or event into the category represented by that prototype. To go back to the previous example, if your peer closely resembles your prototypical example of a med student, you may place them into that category based on the prototype theory of object and identity recognition. This, however, causes you to commit the representativeness heuristic.

Anchoring and adjustment heuristic

Another heuristic put forth by Kahneman and Tversky in their initial paper is the anchoring and adjustment heuristic. 7 This heuristic describes how, when estimating a certain value, we tend to give an initial value, then adjust it by increasing or decreasing our estimation. However, we often get stuck on that initial value – which is referred to as anchoring – this results in us making insufficient adjustments. Thus, the adjusted value is biased in favor of the initial value we have anchored to.

In an example of the anchoring and adjustment heuristic, Kahneman and Tversky gave participants questions such as “estimate the number of African countries in the United Nations (UN).” A wheel labeled with numbers from 0-100 was spun, and participants were asked to say whether or not the number the wheel landed on was higher or lower than their answer to the question. Then, participants were asked to estimate the number of African countries in the UN, independent from the number they had spun. Regardless, Kahneman and Tversky found that participants tended to anchor onto the random number obtained by spinning the wheel. The results showed that  when the number obtained by spinning the wheel was 10, the median estimate given by participants was 25, while, when the number obtained from the wheel was 65, participants’ median estimate was 45.8.

A 2006 study by Epley and Gilovich, “The Anchoring and Adjustment Heuristic: Why the Adjustments are Insufficient” 9 investigated the causes of this heuristic. They illustrated that anchoring often occurs because the new information that we anchor to is more accessible than other information Furthermore, they provided empirical evidence to demonstrate that our adjustments tend to be insufficient because they require significant mental effort, which we are not always motivated to dedicate to the task. They also found that providing incentives for accuracy led participants to make more sufficient adjustments. So, this particular heuristic generally occurs when there is no real incentive to provide an accurate response.

Quick and easy

Though different in their explanations, these three types of heuristics allow us to respond automatically without much effortful thought. They provide an immediate response and do not use up much of our mental energy, which allows us to dedicate mental resources to other matters that may be more pressing. In that way, heuristics are efficient, which is a big reason why we continue to use them. That being said, we should be mindful of how much we rely on them because there is no guarantee of their accuracy.

Why it is important

As illustrated by Tversky and Kahneman, using heuristics can cause us to engage in various cognitive biases and commit certain fallacies. 10 As a result, we may make poor decisions, as well as inaccurate judgments and predictions. Awareness of heuristics can aid us in avoiding them, which will ultimately lead us to engage in more adaptive behaviors.

How to avoid it

Heuristics arise from automatic System 1 thinking. It is a common misconception that errors in judgment can be avoided by relying exclusively on System 2 thinking. However, as pointed out by Kahneman, neither System 2 nor System 1 are infallible. 11   While System 1 can result in relying on heuristics leading to certain biases, System 2 can give rise to other biases, such as the confirmation bias . 12 In truth, Systems 1 and 2 complement each other, and using them together can lead to more rational decision-making. That is, we shouldn’t make judgments automatically, without a second thought, but we shouldn’t overthink things to the point where we’re looking for specific evidence to support our stance. Thus, heuristics can be avoided by making judgments more effortfully, but in doing so, we should attempt not to overanalyze the situation.

How it all started

The first three heuristics – availability, representativeness, as well as anchoring and adjustment – were identified by Tverksy and Kahneman in their 1974 paper, “Judgment Under Uncertainty: Heuristics and Biases”. 13 In addition to presenting these heuristics and their relevant experiments, they listed the respective biases each can lead to.

For instance, upon defining the availability heuristic, they demonstrated how it may lead to illusory correlation , which is the erroneous belief that two events frequently co-occur. Kahneman and Tversky made the connection by illustrating how the availability heuristic can cause us to over- or under-estimate the frequency with which certain events occur. This may result in drawing correlations between variables when in reality there are none.  

Referring to our tendency to overestimate our accuracy making probability judgments, Kahneman and Tversky also discussed how the illusion of validity is facilitated by the representativeness heuristic. The more representative an object or event is, the more confident we feel in predicting certain outcomes. The illusion of validity, as it works with the representativeness heuristic, can be demonstrated by our assumptions of others based on past experiences. If you have only ever had good experiences with people from Canada, you will be inclined to judge most Canadians as pleasant. In reality, your small sample size cannot account for the whole population. Representativeness is not the only factor in determining the probability of an outcome or event, meaning we should not be as confident in our predictive abilities.

Example 1 – Advertising

Those in the field of advertising should have a working understanding of heuristics as consumers often rely on these shortcuts when making decisions about purchases. One heuristic that frequently comes into play in the realm of advertising is the scarcity heuristic . When assessing the value of something, we often fall back on this heuristic, leading us to believe that the rarity or exclusiveness of an object contributes to its value.

A 2011 study by Praveen Aggarwal, Sung Yul Jun, and Jong Ho Huh evaluated the impact of “scarcity messages” on consumer behavior. They found that both “limited quantity” and “limited time” advertisements influence consumers’ intentions to purchase, but “limited quantity” messages are more effective. This explains why people get so excited over the one-day-only Black Friday sales, and why the countdowns of units available on home shopping television frequently lead to impulse buys. 14

Knowledge of the scarcity heuristic can help businesses thrive, as “limited quantity” messages make potential consumers competitive and increase their intentions to purchase. 15 This marketing technique can be a useful tool for bolstering sales and bringing attention to your business.

Example 2 – Stereotypes

One of the downfalls of heuristics is that they have the potential to lead to stereotyping, which is often harmful. Kahneman and Tversky illustrated how the representativeness heuristic might result in the propagation of stereotypes. The researchers presented participants with a personality sketch of a fictional man named Steve followed by a list of possible occupations. Participants were tasked with ranking the likelihood of each occupation being Steve’s. Since the personality sketch described Steve as shy, helpful, introverted, and organized, participants tended to indicate that it was probable that he was a  librarian. 16 In this particular case the stereotype is less harmful than many others, however it accurately illustrates the link between heuristics and stereotypes.

Published in 1989, Patricia Devine’s paper “Stereotypes and Prejudice: Their Automatic and Controlled Components” illustrates how, even among people who are low in prejudice, rejecting stereotypes requires a certain level of motivation and cognitive capacity. 17 We typically use heuristics in order to avoid exerting too much mental energy, specifically when we are not sufficiently motivated to dedicate mental resources to the task at hand. Thus, when we lack the mental capacity to make a judgment or decision effortfully, we may rely upon automatic heuristic responses and, in doing so, risk propagating stereotypes.

Stereotypes are an example of how heuristics can go wrong. Broad generalizations do not always apply, and their continued use can have serious consequences. This underscores the importance of effortful judgment and decision-making, as opposed to automatic.

Heuristics are mental shortcuts that allow us to make quick judgment calls based on generalizations or rules of thumb.

Heuristics, in general, occur because they are efficient ways of responding when we are faced with problems or decisions. They come about automatically, allowing us to allocate our mental energy elsewhere. Specific heuristics occur in different contexts; the availability heuristic happens because we remember certain memories better than others, the representativeness heuristic can be explained by prototype theory, and the anchoring and adjustment heuristic occurs due to lack of incentive to put in the effort required for sufficient adjustment.

The scarcity heuristic, which refers to how we value items more when they are limited, can be used to the advantage of businesses looking to increase sales. Research has shown that advertising objects as “limited quantity” increases consumers' competitiveness and their intentions to buy the item.

While heuristics can be useful, we should exert caution, as they are generalizations that may lead us to propagate stereotypes ranging from inaccurate to harmful.

Putting more effort into decision-making instead of making decisions automatically can help us avoid heuristics. Doing so requires more mental resources, but it will lead to more rational choices.

Related TDL articles

What are heuristics.

This interview with The Decision Lab’s Managing Director Sekoul Krastev delves into the history of heuristics, their applications in the real world, and their consequences, both positive and negative.

10 Decision-Making Errors that Hold Us Back at Work

In this article, Dr. Melina Moleskis examines the common decision-making errors that occur in the workplace. Everything from taking in feedback provided by customers to cracking the problems of on-the-fly decision-making, Dr. Moleskis delivers workable solutions that anyone can implement. 

• Gilovich, T., Keltner, D., Chen. S, and Nisbett, R. (2015).  Social Psychology  (4th edition). W.W. Norton and Co. Inc.
• Tversky, A. and Kahneman, D. (1974). Judgment Under Uncertainty: Heuristics and Biases.  Science . 185(4157), 1124-1131.
• Mervis, C. B., & Rosch, E. (1981). Categorization of natural objects.  Annual Review of Psychology ,  32 (1), 89–115. https://doi.org/10.1146/annurev.ps.32.020181.000513
• Epley, N., & Gilovich, T. (2006). The anchoring-and-adjustment heuristic.  Psychological Science -Cambridge- ,  17 (4), 311–318.
• System 1 and System 2 Thinking.  The Marketing Society.  https://www.marketingsociety.com/think-piece/system-1-and-system-2-thinking
• Aggarwal, P., Jun, S. Y., & Huh, J. H. (2011). Scarcity messages.  Journal of Advertising ,  40 (3), 19–30.
• Devine, P. G. (1989). Stereotypes and prejudice: their automatic and controlled components.  Journal of Personality and Social Psychology ,  56 (1), 5–18. https://doi.org/10.1037/0022-3514.56.1.5
• Kuo, L., Chang, T., & Lai, C.-C. (2022). Research on product design modeling image and color psychological test. Displays, 71, 102108. https://doi.org/10.1016/j.displa.2021.102108

About the Authors

Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.

Dr. Sekoul Krastev

Sekoul is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. A decision scientist with a PhD in Decision Neuroscience from McGill University, Sekoul's work has been featured in peer-reviewed journals and has been presented at conferences around the world. Sekoul previously advised management on innovation and engagement strategy at The Boston Consulting Group as well as on online media strategy at Google. He has a deep interest in the applications of behavioral science to new technology and has published on these topics in places such as the Huffington Post and Strategy & Business.

Hindsight Bias

Why do unpredictable events only seem predictable after they occur, hot hand fallacy, why do we expect previous success to lead to future success, hyperbolic discounting, why do we value immediate rewards more than long-term rewards.

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7.3 Problem-Solving

Learning objectives.

By the end of this section, you will be able to:

• Describe problem solving strategies
• Define algorithm and heuristic
• Explain some common roadblocks to effective problem solving

   People face problems every day—usually, multiple problems throughout the day. Sometimes these problems are straightforward: To double a recipe for pizza dough, for example, all that is required is that each ingredient in the recipe be doubled. Sometimes, however, the problems we encounter are more complex. For example, say you have a work deadline, and you must mail a printed copy of a report to your supervisor by the end of the business day. The report is time-sensitive and must be sent overnight. You finished the report last night, but your printer will not work today. What should you do? First, you need to identify the problem and then apply a strategy for solving the problem.

The study of human and animal problem solving processes has provided much insight toward the understanding of our conscious experience and led to advancements in computer science and artificial intelligence. Essentially much of cognitive science today represents studies of how we consciously and unconsciously make decisions and solve problems. For instance, when encountered with a large amount of information, how do we go about making decisions about the most efficient way of sorting and analyzing all the information in order to find what you are looking for as in visual search paradigms in cognitive psychology. Or in a situation where a piece of machinery is not working properly, how do we go about organizing how to address the issue and understand what the cause of the problem might be. How do we sort the procedures that will be needed and focus attention on what is important in order to solve problems efficiently. Within this section we will discuss some of these issues and examine processes related to human, animal and computer problem solving.

PROBLEM-SOLVING STRATEGIES

   When people are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

Problems themselves can be classified into two different categories known as ill-defined and well-defined problems (Schacter, 2009). Ill-defined problems represent issues that do not have clear goals, solution paths, or expected solutions whereas well-defined problems have specific goals, clearly defined solutions, and clear expected solutions. Problem solving often incorporates pragmatics (logical reasoning) and semantics (interpretation of meanings behind the problem), and also in many cases require abstract thinking and creativity in order to find novel solutions. Within psychology, problem solving refers to a motivational drive for reading a definite “goal” from a present situation or condition that is either not moving toward that goal, is distant from it, or requires more complex logical analysis for finding a missing description of conditions or steps toward that goal. Processes relating to problem solving include problem finding also known as problem analysis, problem shaping where the organization of the problem occurs, generating alternative strategies, implementation of attempted solutions, and verification of the selected solution. Various methods of studying problem solving exist within the field of psychology including introspection, behavior analysis and behaviorism, simulation, computer modeling, and experimentation.

A problem-solving strategy is a plan of action used to find a solution. Different strategies have different action plans associated with them (table below). For example, a well-known strategy is trial and error. The old adage, “If at first you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

   Another type of strategy is an algorithm. An algorithm is a problem-solving formula that provides you with step-by-step instructions used to achieve a desired outcome (Kahneman, 2011). You can think of an algorithm as a recipe with highly detailed instructions that produce the same result every time they are performed. Algorithms are used frequently in our everyday lives, especially in computer science. When you run a search on the Internet, search engines like Google use algorithms to decide which entries will appear first in your list of results. Facebook also uses algorithms to decide which posts to display on your newsfeed. Can you identify other situations in which algorithms are used?

A heuristic is another type of problem solving strategy. While an algorithm must be followed exactly to produce a correct result, a heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. A “rule of thumb” is an example of a heuristic. Such a rule saves the person time and energy when making a decision, but despite its time-saving characteristics, it is not always the best method for making a rational decision. Different types of heuristics are used in different types of situations, but the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind in the same moment

Working backwards is a useful heuristic in which you begin solving the problem by focusing on the end result. Consider this example: You live in Washington, D.C. and have been invited to a wedding at 4 PM on Saturday in Philadelphia. Knowing that Interstate 95 tends to back up any day of the week, you need to plan your route and time your departure accordingly. If you want to be at the wedding service by 3:30 PM, and it takes 2.5 hours to get to Philadelphia without traffic, what time should you leave your house? You use the working backwards heuristic to plan the events of your day on a regular basis, probably without even thinking about it.

Another useful heuristic is the practice of accomplishing a large goal or task by breaking it into a series of smaller steps. Students often use this common method to complete a large research project or long essay for school. For example, students typically brainstorm, develop a thesis or main topic, research the chosen topic, organize their information into an outline, write a rough draft, revise and edit the rough draft, develop a final draft, organize the references list, and proofread their work before turning in the project. The large task becomes less overwhelming when it is broken down into a series of small steps.

Further problem solving strategies have been identified (listed below) that incorporate flexible and creative thinking in order to reach solutions efficiently.

Additional Problem Solving Strategies :

• Abstraction – refers to solving the problem within a model of the situation before applying it to reality.
• Analogy – is using a solution that solves a similar problem.
• Brainstorming – refers to collecting an analyzing a large amount of solutions, especially within a group of people, to combine the solutions and developing them until an optimal solution is reached.
• Divide and conquer – breaking down large complex problems into smaller more manageable problems.
• Hypothesis testing – method used in experimentation where an assumption about what would happen in response to manipulating an independent variable is made, and analysis of the affects of the manipulation are made and compared to the original hypothesis.
• Lateral thinking – approaching problems indirectly and creatively by viewing the problem in a new and unusual light.
• Means-ends analysis – choosing and analyzing an action at a series of smaller steps to move closer to the goal.
• Method of focal objects – putting seemingly non-matching characteristics of different procedures together to make something new that will get you closer to the goal.
• Morphological analysis – analyzing the outputs of and interactions of many pieces that together make up a whole system.
• Proof – trying to prove that a problem cannot be solved. Where the proof fails becomes the starting point or solving the problem.
• Reduction – adapting the problem to be as similar problems where a solution exists.
• Research – using existing knowledge or solutions to similar problems to solve the problem.
• Root cause analysis – trying to identify the cause of the problem.

The strategies listed above outline a short summary of methods we use in working toward solutions and also demonstrate how the mind works when being faced with barriers preventing goals to be reached.

One example of means-end analysis can be found by using the Tower of Hanoi paradigm . This paradigm can be modeled as a word problems as demonstrated by the Missionary-Cannibal Problem :

Missionary-Cannibal Problem

Three missionaries and three cannibals are on one side of a river and need to cross to the other side. The only means of crossing is a boat, and the boat can only hold two people at a time. Your goal is to devise a set of moves that will transport all six of the people across the river, being in mind the following constraint: The number of cannibals can never exceed the number of missionaries in any location. Remember that someone will have to also row that boat back across each time.

Hint : At one point in your solution, you will have to send more people back to the original side than you just sent to the destination.

The actual Tower of Hanoi problem consists of three rods sitting vertically on a base with a number of disks of different sizes that can slide onto any rod. The puzzle starts with the disks in a neat stack in ascending order of size on one rod, the smallest at the top making a conical shape. The objective of the puzzle is to move the entire stack to another rod obeying the following rules:

• 1. Only one disk can be moved at a time.
• 2. Each move consists of taking the upper disk from one of the stacks and placing it on top of another stack or on an empty rod.
• 3. No disc may be placed on top of a smaller disk.

  Figure 7.02. Steps for solving the Tower of Hanoi in the minimum number of moves when there are 3 disks.

Figure 7.03. Graphical representation of nodes (circles) and moves (lines) of Tower of Hanoi.

The Tower of Hanoi is a frequently used psychological technique to study problem solving and procedure analysis. A variation of the Tower of Hanoi known as the Tower of London has been developed which has been an important tool in the neuropsychological diagnosis of executive function disorders and their treatment.

GESTALT PSYCHOLOGY AND PROBLEM SOLVING

As you may recall from the sensation and perception chapter, Gestalt psychology describes whole patterns, forms and configurations of perception and cognition such as closure, good continuation, and figure-ground. In addition to patterns of perception, Wolfgang Kohler, a German Gestalt psychologist traveled to the Spanish island of Tenerife in order to study animals behavior and problem solving in the anthropoid ape.

As an interesting side note to Kohler’s studies of chimp problem solving, Dr. Ronald Ley, professor of psychology at State University of New York provides evidence in his book A Whisper of Espionage  (1990) suggesting that while collecting data for what would later be his book  The Mentality of Apes (1925) on Tenerife in the Canary Islands between 1914 and 1920, Kohler was additionally an active spy for the German government alerting Germany to ships that were sailing around the Canary Islands. Ley suggests his investigations in England, Germany and elsewhere in Europe confirm that Kohler had served in the German military by building, maintaining and operating a concealed radio that contributed to Germany’s war effort acting as a strategic outpost in the Canary Islands that could monitor naval military activity approaching the north African coast.

While trapped on the island over the course of World War 1, Kohler applied Gestalt principles to animal perception in order to understand how they solve problems. He recognized that the apes on the islands also perceive relations between stimuli and the environment in Gestalt patterns and understand these patterns as wholes as opposed to pieces that make up a whole. Kohler based his theories of animal intelligence on the ability to understand relations between stimuli, and spent much of his time while trapped on the island investigation what he described as  insight , the sudden perception of useful or proper relations. In order to study insight in animals, Kohler would present problems to chimpanzee’s by hanging some banana’s or some kind of food so it was suspended higher than the apes could reach. Within the room, Kohler would arrange a variety of boxes, sticks or other tools the chimpanzees could use by combining in patterns or organizing in a way that would allow them to obtain the food (Kohler & Winter, 1925).

While viewing the chimpanzee’s, Kohler noticed one chimp that was more efficient at solving problems than some of the others. The chimp, named Sultan, was able to use long poles to reach through bars and organize objects in specific patterns to obtain food or other desirables that were originally out of reach. In order to study insight within these chimps, Kohler would remove objects from the room to systematically make the food more difficult to obtain. As the story goes, after removing many of the objects Sultan was used to using to obtain the food, he sat down ad sulked for a while, and then suddenly got up going over to two poles lying on the ground. Without hesitation Sultan put one pole inside the end of the other creating a longer pole that he could use to obtain the food demonstrating an ideal example of what Kohler described as insight. In another situation, Sultan discovered how to stand on a box to reach a banana that was suspended from the rafters illustrating Sultan’s perception of relations and the importance of insight in problem solving.

Grande (another chimp in the group studied by Kohler) builds a three-box structure to reach the bananas, while Sultan watches from the ground.  Insight , sometimes referred to as an “Ah-ha” experience, was the term Kohler used for the sudden perception of useful relations among objects during problem solving (Kohler, 1927; Radvansky & Ashcraft, 2013).

Solving puzzles.

   Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below (see figure) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

How long did it take you to solve this sudoku puzzle? (You can see the answer at the end of this section.)

   Here is another popular type of puzzle (figure below) that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Did you figure it out? (The answer is at the end of this section.) Once you understand how to crack this puzzle, you won’t forget.

   Take a look at the “Puzzling Scales” logic puzzle below (figure below). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

What steps did you take to solve this puzzle? You can read the solution at the end of this section.

Pitfalls to problem solving.

   Not all problems are successfully solved, however. What challenges stop us from successfully solving a problem? Albert Einstein once said, “Insanity is doing the same thing over and over again and expecting a different result.” Imagine a person in a room that has four doorways. One doorway that has always been open in the past is now locked. The person, accustomed to exiting the room by that particular doorway, keeps trying to get out through the same doorway even though the other three doorways are open. The person is stuck—but she just needs to go to another doorway, instead of trying to get out through the locked doorway. A mental set is where you persist in approaching a problem in a way that has worked in the past but is clearly not working now.

Functional fixedness is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. During the Apollo 13 mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

   Researchers have investigated whether functional fixedness is affected by culture. In one experiment, individuals from the Shuar group in Ecuador were asked to use an object for a purpose other than that for which the object was originally intended. For example, the participants were told a story about a bear and a rabbit that were separated by a river and asked to select among various objects, including a spoon, a cup, erasers, and so on, to help the animals. The spoon was the only object long enough to span the imaginary river, but if the spoon was presented in a way that reflected its normal usage, it took participants longer to choose the spoon to solve the problem. (German & Barrett, 2005). The researchers wanted to know if exposure to highly specialized tools, as occurs with individuals in industrialized nations, affects their ability to transcend functional fixedness. It was determined that functional fixedness is experienced in both industrialized and nonindustrialized cultures (German & Barrett, 2005).

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. Sometimes, however, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000 home? Why would the realtor show you the run-down houses and the nice house? The realtor may be challenging your anchoring bias. An anchoring bias occurs when you focus on one piece of information when making a decision or solving a problem. In this case, you’re so focused on the amount of money you are willing to spend that you may not recognize what kinds of houses are available at that price point.

The confirmation bias is the tendency to focus on information that confirms your existing beliefs. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Representative bias describes a faulty way of thinking, in which you unintentionally stereotype someone or something; for example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Finally, the availability heuristic is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision . Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in the table below.

Were you able to determine how many marbles are needed to balance the scales in the figure below? You need nine. Were you able to solve the problems in the figures above? Here are the answers.

   Many different strategies exist for solving problems. Typical strategies include trial and error, applying algorithms, and using heuristics. To solve a large, complicated problem, it often helps to break the problem into smaller steps that can be accomplished individually, leading to an overall solution. Roadblocks to problem solving include a mental set, functional fixedness, and various biases that can cloud decision making skills.

References:

Openstax Psychology text by Kathryn Dumper, William Jenkins, Arlene Lacombe, Marilyn Lovett and Marion Perlmutter licensed under CC BY v4.0. https://openstax.org/details/books/psychology

Review Questions:

1. A specific formula for solving a problem is called ________.

a. an algorithm

b. a heuristic

c. a mental set

d. trial and error

2. Solving the Tower of Hanoi problem tends to utilize a  ________ strategy of problem solving.

a. divide and conquer

b. means-end analysis

d. experiment

3. A mental shortcut in the form of a general problem-solving framework is called ________.

4. Which type of bias involves becoming fixated on a single trait of a problem?

a. anchoring bias

b. confirmation bias

c. representative bias

d. availability bias

5. Which type of bias involves relying on a false stereotype to make a decision?

6. Wolfgang Kohler analyzed behavior of chimpanzees by applying Gestalt principles to describe ________.

a. social adjustment

b. student load payment options

c. emotional learning

d. insight learning

7. ________ is a type of mental set where you cannot perceive an object being used for something other than what it was designed for.

a. functional fixedness

c. working memory

Critical Thinking Questions:

1. What is functional fixedness and how can overcoming it help you solve problems?

2. How does an algorithm save you time and energy when solving a problem?

Personal Application Question:

1. Which type of bias do you recognize in your own decision making processes? How has this bias affected how you’ve made decisions in the past and how can you use your awareness of it to improve your decisions making skills in the future?

anchoring bias

availability heuristic

confirmation bias

functional fixedness

hindsight bias

problem-solving strategy

representative bias

trial and error

working backwards

Answers to Exercises

algorithm:  problem-solving strategy characterized by a specific set of instructions

anchoring bias:  faulty heuristic in which you fixate on a single aspect of a problem to find a solution

availability heuristic:  faulty heuristic in which you make a decision based on information readily available to you

confirmation bias:  faulty heuristic in which you focus on information that confirms your beliefs

functional fixedness:  inability to see an object as useful for any other use other than the one for which it was intended

heuristic:  mental shortcut that saves time when solving a problem

hindsight bias:  belief that the event just experienced was predictable, even though it really wasn’t

mental set:  continually using an old solution to a problem without results

problem-solving strategy:  method for solving problems

representative bias:  faulty heuristic in which you stereotype someone or something without a valid basis for your judgment

trial and error:  problem-solving strategy in which multiple solutions are attempted until the correct one is found

working backwards:  heuristic in which you begin to solve a problem by focusing on the end result

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5 Simple Heuristics and Rules of Thumb: Where Psychologists and Behavioural Biologists Might Meet

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The Centre for Adaptive Behavior and Cognition (ABC) has hypothesized that much human decision making can be described by simple algorithmic process models (heuristics). This chapter explains this approach and relates it to research in biology on rules of thumb, which we also review. As an example of a simple heuristic, consider the lexicographic strategy of take-the-best for choosing between two alternatives: Cues are searched in turn until one discriminates, then search stops and all other cues are ignored. Heuristics consist of building blocks, and building blocks exploit evolved or learned abilities such as recognition memory; it is the complexity of these abilities that allows the heuristics to be simple. Simple heuristics have an advantage in making decisions fast and with little information, and in avoiding overfitting. Furthermore, humans are observed to use simple heuristics. Simulations show that the statistical structures of different environments affect which heuristics perform better, a relationship referred to as ecological rationality. We contrast ecological rationality with the stronger claim of adaptation. Rules of thumb from biology provide clearer examples of adaptation because animals can be studied in the environments in which they evolved. The range of examples is also much more diverse. To investigate them, biologists have sometimes used similar simulation techniques to ABC, but many examples depend on empirically driven approaches. ABC's theoretical framework can be useful in connecting some of these examples, particularly the scattered literature on how information from different cues is integrated. Optimality modeling is usually used to explain less detailed aspects of behavior but might more often be redirected to investigate rules of thumb.

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4 Rules of Thumb to Make Faster Decisions

Follow simple choice rules to reduce complexity and make decisions faster..

Posted October 23, 2018

Have you ever wasted precious energy on making minor decisions? If you're anything like me, you’ll find long periods of debate tiring, frustrating and plain unnecessary. I simply don’t have the time to agonize over every single decision life throws at me—especially if they amount to 35,000 decisions each day ! Often choices with many different options can be the hardest, and this holds particularly true for areas outside one’s comfort zone and expertise.

Example decisions I personally struggle with include identifying the best energy provider, picking items from an unknown restaurant menu, selecting a new phone model, or choosing a hotel when staying in a foreign city. None of these decisions are likely to have a life-changing, earth-shattering impact on me, and I thus cannot afford to mull them for hours. Yet, I obviously aim for a good outcome—be it a cheap electricity deal, a yummy meal, a multi-functional phone or comfortable accommodation. This begs the tricky question of efficiency: How can I make quick decisions without sacrificing a decent outcome?

Let’s discuss the task of booking a hotel as an example. Not only are there usually lots of different hotels to choose from, there are also a multitude of aspects to consider when making your decision. What is the price per night? Is the hotel in a central location? Does it have free WiFi access? Is breakfast included? Does the hotel have gym facilities? Is it close to public transport? Are pets allowed? Can they provide rooms for smokers? Are there any parking spaces? What are the hotel’s check-in times? And do they offer free booking cancellations?

With so many different criteria to weigh, simple decision guidelines are certainly appealing. Such guidelines—often referred to as “rules of thumb,” “ heuristics ,” or “mental shortcuts”—are easy-to-follow rules that aim to reduce choice complexity, speed up the process of comparison, and still deliver satisfactory results. Some rules of thumb are context-specific and target narrow areas of behavior such as healthy eating. A well-known example rule entails eating at least five portions of different fruit and vegetables per day to meet your needs of vitamins. However, with context-specific heuristics being comparatively rare, more general rules of thumb are necessary to guide decision making in a broader range of situations.

Take the best

This important heuristic takes a one-dimensional choice approach. It involves fixating on one choice criterion only and picking the best option for the chosen criterion. Returning to the example task of booking a hotel room, one priority might be a rich and varied breakfast buffet. With this in mind, the decision process can easily be simplified by focusing on breakfast deals only, and picking the hotel with the most appealing food offer.

Personally, I tend to judge a hotel room by its overall size and the amount of floor space. As a passionate hobby yogi, I always need enough room for my yoga mat! Unfortunately, this criterion is hard to assess in advance, and it’s best to come prepared. For all those travelers struggling with tiny box rooms, I have just the yoga sequence for you. Not only is this class great for small spaces, the instructor Katee also manages to squeeze a well-balanced practice into as little as 15 minutes. Now, that’s what I call efficiency!

Recognition heuristic

Another powerful rule of thumb—often used intuitively—is the recognition heuristic. As indicated by the name, this decision rule relies on mere recognition of a choice option based on personal memory . Easy recognition is often associated with the overall importance of a choice option. Recognition of a hotel brand, for example, typically indicates high popularity, a big market share and a well-established business. The recognition heuristic therefore involves choosing the hotel with the most recognizable name.

The tallying approach is an extension of the “Take-the-best” heuristic. However, rather than focusing on a single choice criterion, tallying involves considering a list of different criteria, counting the number of favorable criteria for each option, and making a choice based on the number of criteria fulfilled. When selecting your hotel, you might decide to extend your initial priorities (i.e. a hearty breakfast) and additionally consider the availability of parking spaces and gym facilities. Checking the hotel options against the items on your priority list, you’d simply choose the hotel that ticks the most boxes.

Imitate the successful

Human decision makers never act in isolation, and they can receive important decision cues from their social environment. Drawing on this social type of information, “Imitate the successful” describes a strategy of copying other, successful decision makers. In your quest for a suitable hotel, for example, you might ask experienced travelers for advice or choose the hotel with the highest online ratings from previous customers.

Despite the crude simplicity of many rules of thumb, they have been shown to yield surprisingly satisfactory results, often trumping the outcomes of much more sophisticated choice strategies. However, while using rules of thumb is a great way of minimizing cognitive effort, it also leaves you open to biases and subtle influences, which might sway your choices in unwanted directions. Recognition of a brand, for example, is frequently manipulated through strategic advertising campaigns. Similarly, customer ratings can easily be fixed to present a misleading result. Instead of blindly relying on those simple rules of thumb, we need to consciously recognize their potential downfalls and change decision rules if necessary. Let’s make efficient choices, not mindless ones!

Eva Krockow, Ph.D. , is a researcher in decision making at the University of Leicester.

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Decision Theory and Rules of Thumb

• First Online: 01 January 2013

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• Konstantinos V. Katsikopoulos 4  

Part of the book series: Studies in Computational Intelligence ((SCI,volume 502))

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This chapter presents a relatively new and rapidly developing interdisciplinary theory of decision making, the theory of fast and frugal heuristics. It is first shown how the theory complements most of the standard theories of decision making in the social sciences such as Bayesian expected utility theory and its variants: Fast and frugal heuristics are not derived from normatively compelling axioms but are inspired by the simple rules of thumb that people and animals have been empirically found to use. The theory is illustrated by presenting the basic concepts and mathematics of some fast and frugal heuristics such as the recognition heuristic, the take-the-best heuristic, and fast and frugal trees. Then, applications of fast and frugal heuristics in a number of problems are described (how do laypeople make investment decisions? how do military staff identify unexploded ordnance buried in the ground? how do doctors decide whether to admit a patient to the emergency care or not?) It is emphasized that there are no good or bad decision models per se but that all models can work well in some situations and not in others, and thus the goal is to find the right model for each situation. Accordingly, in all applications, the performance of fast and frugal heuristics is compared, by computer simulations and mathematical analyses, to the performance of standard models such as Bayesian networks, classification-and-regression trees and support-vector machines. Finally, ways of combining standard decision theory and rules of thumb are discussed.

Chapter for the book Human-Centric Decision-Making Models for Social Sciences, Edited by Peijun Guo and Witold Pedrycz.

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Katsikopoulos, K.V. (2014). Decision Theory and Rules of Thumb. In: Guo, P., Pedrycz, W. (eds) Human-Centric Decision-Making Models for Social Sciences. Studies in Computational Intelligence, vol 502. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39307-5_4

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‘Rule of thumb’ refers to _______.

Adopting a hit-and-trial approach to resolve management problems

Use of personal judgment in handling management issues

Both of the above

None of the above

The correct option is C Both of the above Answer (c) Both of the above Explanation: ‘Rule of thumb’ is an investigative rule that gives improved and simple answers or some fundamental standard set with respect to a specific subject or game-plan. It is a general rule that gives practical guidelines for achieving or approaching a specific task.

Write one application of each of the following :-