heuristic [hyoo-ris-tik] (Greek: ‘find’ or ‘discover’) is a practical way to solve a problem. It is better than chance, but does not always work. A person develops a heuristic by using intelligence, experience, and common sense. Trial and error is the simplest heuristic, but one of the weakest. ‘Rule of thumb’ and ‘educated guesses’ are other names for simple heuristics. Since a heuristic is not certain to get a result, there are always exceptions.

Sometimes heuristics are rather vague: ‘look before you leap’ is a guide to behavior, but ‘think about the consequences’ is a bit clearer. Sometimes a heuristic is a whole set of stages. When doctors examines a patient, they go through a series of tests and observations. They may not find out what is wrong, but they give themselves the best chance of succeeding. This is called a diagnosis. In computer science, a ‘heuristic’ is a kind of algorithm (a step-by-step list of directions that need to be followed to solve a problem).

Heuristics is the art of finding an adequate solution to a problem, using limited knowledge and little time. More formally, heuristics are based on experience; they can speed up the search for a solution using simple rules. A complete search may take too long, or may be too difficult to do. In more precise terms, heuristics are strategies using readily accessible, though loosely applicable, information to control problem solving in human beings and machines.

Heuristics can be used in some fields of science, but not in others: For economics, a solution that is one percent off is often acceptable; a telescope that has an error of one degree is probably unusable if aimed at a far-away object. The same telescope pointed to the window across the street will probably tolerate this error; missing by one degree will not have a big impact on a short distance.

Heuristics can be used to estimate an answer which is then made more clear by performing an exact solution at a very small scale, perhaps to save time, money or labor on a project – for example a heuristic guess as to how much weight a bridge is expected to carry can be used to determine whether the bridge should be made of wood, stone or steel, and appropriate quantities of the needed material can be purchased while the exact design of the bridge is being completed.

However, the use of heuristics in certain very technical fields may be damaging – computer science is one example. Programming a computer to perform more or less the desired actions may result in severe glitches. Therefore computer tasks generally must be fairly exact. However, there are certain areas in which computers can calculate heuristic solutions safely – for example Google’s search technology relies heavily on heuristics, producing ‘near-miss’ matches to a search query when an exact match cannot be found. This enables a user to correct for any mistakes the search produces. Example: Searching for the name ‘Peter Smith’ and unable to find that exact name, the search engine heuristically matches ‘Pete Smith’ instead, and the person using the search engine must decide whether Pete and Peter are the same person.

Here are some other commonly used heuristics, from Hungarian-American mathematician George Polya’s 1945 book, ‘How to Solve It’: If you are having difficulty understanding a problem, try drawing a picture. If you can’t find a solution, try assuming that you have a solution and seeing what you can derive from that (‘working backward’). If the problem is abstract, try examining a concrete example. Try solving a more general problem first (‘inventor’s paradox,’ to solve what you desire, you may have to solve more than what you actually want).

To sum up, heuristics are experience-based techniques for problem solving, learning, and discovery that give a solution which is not guaranteed to be optimal. Where the exhaustive search is impractical, heuristic methods are used to speed up the process of finding a satisfactory solution via mental shortcuts to ease the cognitive load of making a decision. Examples of this method include using a rule of thumb, an educated guess, an intuitive judgment, stereotyping, or common sense. In more precise terms, heuristics are strategies using readily accessible, though loosely applicable, information to control problem solving in human beings and machines.

In psychology, heuristics are simple, efficient rules, learned or hard-coded by evolutionary processes, that have been proposed to explain how people make decisions, come to judgments, and solve problems typically when facing complex problems or incomplete information. These rules work well under most circumstances, but in certain cases lead to systematic errors or cognitive biases.

Although much of the work of discovering heuristics in human decision-makers was done by the Israeli psychologists Amos Tversky and Daniel Kahneman, the concept was originally introduced by Nobel laureate Herbert A. Simon. Simon’s original, primary object of research was problem solving, showed that we operate within what he calls ‘bounded rationality’ (the idea that in decision-making, rationality of individuals is limited by information, intelligence, and time). He coined the term ‘satisficing,’ which denotes the situation where people seek solutions or accept choices or judgments that are ‘good enough’ for their purposes, but could be optimized.

German psychologist Gerd Gigerenzer focused on the ‘fast and frugal’ properties of heuristics, i.e., using heuristics in a way that is principally accurate and thus eliminating most cognitive bias. From one particular batch of research, Gigerenzer and Wolfgang Gaissmaier found that both individuals and organizations rely on heuristics in an adaptive way. They also found that ignoring part of the information [with a decision], rather than weighing all the options, can actually lead to more accurate decisions.

Heuristics, through greater refinement and research, have begun to be applied to other theories, or be explained by them. For example: the ‘Cognitive-Experiential Self-Theory’ (CEST) also an adaptive view of heuristic processing. CEST breaks down two systems that process information. At some times, roughly speaking, individuals consider issues rationally, systematically, logically, deliberately, effortfully, and verbally. On other occasions, individuals consider issues intuitively, effortlessly, globally, and emotionally. From this perspective, heuristics are part of a larger experiential processing system that is often adaptive, but vulnerable to error in situations that require logical analysis.

In 2002, Daniel Kahneman and Yale School of Management professor Shane Frederick proposed that cognitive heuristics work by a process called ‘attribute substitution,’ which happens without conscious awareness. According to this theory, when somebody makes a judgment (of a ‘target attribute’) that is computationally complex, a rather easier calculated ‘heuristic attribute’ is substituted. In effect, a cognitively difficult problem is dealt with by answering a rather simpler problem, without being aware of this happening. This theory explains cases where judgments fail to show regression toward the mean.

There are several theorized psychological heuristics: Anchoring and adjustment (the common human tendency to rely too heavily on the first piece of information offered, the ‘anchor,’ when making decisions); Availability heuristic (a mental shortcut that occurs when people make judgments about the probability of events by the ease with which examples come to mind); Representativeness heuristic (a mental shortcut used when making judgments about the probability of an event under uncertainty); Naïve diversification (when asked to make several choices at once, people tend to diversify more than when making the same type of decision sequentially); Escalation of commitment (justifying increased investment in a decision, based on the cumulative prior investment, despite new evidence suggesting that the cost, starting today, of continuing the decision outweighs the expected benefit); and Familiarity heuristic (the assumption that the circumstances underlying the past behavior still hold true for the present situation and that the past behavior thus can be correctly applied to the new situation – especially prevalent when the individual experiences a high cognitive load).

Heuristics were also found to be used in the manipulation and creation of cognitive maps. Cognitive maps are internal representations of our physical environment, particularly associated with spacial relationships. These internal representations of our environment are used as memory as a guide in our external environment. It was found that when questioned about maps imaging, distancing, and etc., people commonly made distortions to images. These distortions took shape in the regularization of images (i.e., images are represented as more like pure abstract geometric images, though they are irregular in shape).

There are several ways that humans form and use cognitive maps. Visual intake is a key part of mapping. The first is by using landmarks. This is where a person uses a mental image to estimate a relationship, usually distance, between two objects. Second, is route-road knowledge, and this is generally developed after a person has performed a task and is relaying the information of that task to another person. Third, is survey. A person estimates a distance based on a mental image that, to them, might appear like an actual map. This image is generally created when a person’s brain begins making image corrections.

These are presented in five ways: ‘Right-angle bias’ (when a person straightens out an image, like mapping an intersection, and begins to give everything 90-degree angles, when in reality it may not be that way); ‘Symmetry heuristic’ (when people tend to think of shapes, or buildings, as being more symmetrical than they really are); ‘Rotation heuristic’ (when a person takes a naturally [realistically] distorted image and straightens it out for their mental image); ‘Alignment heuristic’ (similar to the pervious, where people align objects mentally to make them straighter than they really are); and ‘Relative-position heuristic’ (people do not accurately distance landmarks in their mental image based on how well they remember that particular item). Another method of creating cognitive maps is by means of auditory intake based on verbal descriptions. Using the mapping based from a person’s visual intake, another person can create a mental image, such as directions to a certain location.

In philosophy, a ‘heuristic device’ is used when an entity X exists to enable understanding of, or knowledge concerning, some other entity Y. A good example is a model that, as it is never identical with what it models, is a heuristic device to enable understanding of what it models. Stories, metaphors, etc., can also be termed heuristic in that sense. A classic example is the notion of utopia as described in Plato’s best-known work, ‘The Republic.’ This means that the ‘ideal city’ as depicted in ‘The Republic’ is not given as something to be pursued, or to present an orientation-point for development; rather, it shows how things would have to be connected, and how one thing would lead to another (often with highly problematic results), if one would opt for certain principles and carry them through rigorously.

In legal theory, especially in the theory of law and economics, heuristics are used when case-by-case analysis would be impractical, insofar as ‘practicality’ is defined by the interests of a governing body. For instance, in all states in the United States the legal drinking age for unsupervised persons is 21 years, because it is argued that people need to be mature enough to make decisions involving the risks of alcohol consumption. However, assuming people mature at different rates, the specific age of 21 would be too late for some and too early for others. In this case, the somewhat arbitrary deadline is used because it is impossible or impractical to tell whether an individual is sufficiently mature for society to trust them with that kind of responsibility. Some proposed changes, however, have included the completion of an alcohol education course rather than the attainment of 21 years of age as the criterion for legal alcohol possession. This would put youth alcohol policy more on a case-by-case basis and less on a heuristic one, since the completion of such a course would presumably be voluntary and not uniform across the population.

The same reasoning applies to patent law. Patents are justified on the grounds that inventors must be protected so they have incentive to invent. It is therefore argued that it is in society’s best interest that inventors receive a temporary government-granted monopoly on their idea, so that they can recoup investment costs and make economic profit for a limited period. In the United States, the length of this temporary monopoly is 20 years from the date the application for patent was filed, though the monopoly does not actually begin until the application has matured into a patent. However, like the drinking-age problem above, the specific length of time would need to be different for every product to be efficient. A 20-year term is used because it is difficult to tell what the number should be for any individual patent. More recently, some, including University of North Dakota law professor Eric E. Johnson, have argued that patents in different kinds of industries–such as software patents–should be protected for different lengths of time.

Research has shown that humans are cognitive misers who use low-information rationalities to make decisions. Because we are presented with an overwhelming amount of information every day, we take in only the necessary information to make decisions and rely on heuristics and informational shortcuts the majority of the time. Heuristics are created to aid people in decision making, helping them put as little effort as needed to make a quick decision on various topics.

In the study of media effects, judgmental heuristics have been shown to play an active role in the simplifying of news and political communication. Use of these cues and other signals from elites allows average people the opportunity to achieve a modest level of rationality in reaching a decision. This can be accomplished without having to devote any significant measure of cognitive effort normally required to arrive at thoughtful and considered choices. Equatable to a filing cabinet, when people are introduced to new information, they automatically search within their brain to associate it with something familiar. Once associated, they ‘file’ it away in that ‘drawer’ where it can be referenced later. Once filed, that association is hard to change. Advertisers know this well, implementing it in almost every aspect of advertisement.

This method of processing expands beyond the bounds of social media and advertisements as well, often used as a key tool in political agendas. The limited capacity theory model and other information processing models have been influential in the study of how people encode, store and retrieve political information. Most people maintain a minimum level of interest in public affairs, and therefore employ simplifying shortcuts to arrive at political judgments. Common examples include referring to the complex military and intelligence activities by NATO forces in the Middle East simply as ‘the war on terror,’ a reversal of a specific policy or position as a ‘flip-flop,’ and the homogenization of any type of broad government assistance program as ‘socialism.’

As a result of such heuristic thinking, bias in belief tends to follow, further reinforcing disingenuous mechanisms for information processing. Such an example, according to Schneider, is the hindsight bias, which ‘refers to people’s tendency to believe, in retrospect, that an event was more predictable than it actually was.’ By employing heuristic thinking in decision making, one is not only reinforcing thoughts and opinions, but diminishes one’s openness to other solutions, or ideas. Heuristics is a positive quality when quick judgments need to be made, however in the long run are often detrimental for educational growth and attaining a knowledge-deficit approach to life.

Risk assessment of new technologies offers another example of how ordinary citizens seek shortcuts to expediently arrive at judgments. Most people maintain a low level of interest in issues that are not center to their daily lives, such as developments in the various fields of science and technology. Media frames can produce powerful heuristics that can have significant impact on public opinion about a given new technology. Research has shown media frames that suggest high risk often lead to strong negative perceptions and possible rejection of a technology. An example is the casting of genetically modified foods as ‘Frankenfoods’ and using illustrations containing visual cues to Frankenstein’s monster.

The public also relies on specific heuristics to form opinions about science and science news. Scientists and communicators often assume that the public objectively accumulates and evaluates scientific information to develop opinions, but research has shown heuristics have a larger effect than specific science knowledge. For example, a 2007 study examined how people in the United States developed opinions about agricultural biotechnology. Their results showed that the public used key heuristics to arrive at their opinions rather than specific knowledge of biotechnology. Specifically, the heuristics they used were deference to scientific authority, trust in scientific institutions, and whether they had seen media coverage of biotechnology. Different heuristics were used for different demographic groups, and actual knowledge of biotechnology played a small role in opinion formation.

This study also brings up the idea of using current media news as a heuristic. Whatever information has been most recently presented by the media is likely to be more accessible in an individual’s mind. This information can then be used as a shortcut in evaluating an issue, and is used heuristically in place of lengthier cognitive processing using past information. Opinions of trusted or elite individuals may themselves become a heuristic. When evaluating a decision or problem, individuals can turn to these trusted or elite individuals for their opinions. Rather than evaluating the information surrounding the decision, the individual uses these trusted opinions as informational shortcuts to make their decisions.

Heuristics used when forming opinions can also be ideologically based. A 2008 study looked at the relationship between religion and opinions about nanotechnology. This research found that the more religious the citizens of a country, the less likely they were to support nanotechnology. This suggests that people used religion as a shortcut or heuristic; they were not informed about nanotechnology, but because their religious beliefs cautioned them against some forms of technology, they used an ideological heuristic to form their opinions about an unknown technology.

Different individuals use different heuristics to process the information before them based on their available schema and the framing of the information. Issues may resonate with different schemata depending on the individual and the way the issue is framed. For example, ‘drilling for oil’ may activate schemata relating to corporate profits, environmental disasters, and exploitation of workers, while ‘exploring for energy’ may activate schemata related to protecting the environment, American pride, and American innovation. These two terms refer to the same activity, but when they are framed differently, different schemata are activated, which results in the use of different heuristics.

Stereotyping is a type of heuristic that all people use to make judgments about things they have never seen or experienced. They work as a mental shortcut to access everything from social status of a person from their actions to assumptions that a plant that is tall has a trunk and leaves, is a tree even though we have never seen that particular type of tree before. Stereotypes as described by Lippman as the picture we have in our heads which are built around or experiences as well as what we are told about the word. These ‘pictures in our heads’ allow us to make judgments without having first hand experience on the topics, which is what heuristics are all about.

In engineering, a heuristic is an experience-based method that can be used as an aid to solve process design problems, varying from size of equipment to operating conditions. By using heuristics, time can be reduced when solving problems. Several methods are available to engineers. These include Failure mode and effects analysis and Fault tree analysis. The former relies on a group of qualified engineers to evaluate problems, rank them in order of importance and then recommend solutions. The methods of forensic engineering are an important source of information for investigating problems, especially by elimination of unlikely causes and using the weakest link principle. Because heuristics are fallible, it is important to understand their limitations. They are aids that facilitate quick estimates and preliminary process designs.

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