Heuristic
It is often said, "Understanding comes from Experience ". This is same as Heuristics.
Heuristic can de defined as encouraging a person to learn, discover, understand, or solve problems on his or her own, as by experimenting, evaluating possible answers or solutions, or by trial and error. (a heuristic teaching method)
Heuristic methods are used to speed up the process of finding a good enough solution, where an exhaustive search is impractical. Examples of this method include using a "rule of thumb", an educated guess, an intuitive judgment, or common sense.
Heuristic are strategies using readily accessible, though loosely applicable, information to control problem solving in human beings and machines.
Heuristics
The principal feature of heuristics is the formulation of a hypothetical solution to a problem at the beginning of an investigation of the problem. This working hypothesis serves to direct the course of the investigation, and is modified and refined as relevant facts are discovered and analyzed.
During the course of the investigation, the heuristic method reduces the range, and increases the plausibility, of possible solutions of the problem.
Unlike an algorithm, however, which is a methodical procedure that necessarily produces the solution of a problem, heuristics does not necessarily lead to the solution of a problem.
Heuristics has been fundamental in the acquisition of scientific knowledge, and, in fact, is an essential component of many forms of complex human behavior.
Common Examples :
The most fundamental heuristic is trial and error, which can be used in everything from matching bolts to bicycles to finding the values of variables in algebra problems.
Here are a few other commonly used heuristics, from 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 (the "inventor's paradox": the more ambitious plan may have more chances of success).
A view from Psychology
Heuristics are simple, efficient rules, hard-coded by evolutionary processes or learned, which 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 Amos Tversky and Daniel Kahneman, the concept was originally introduced by Nobel laureate Herbert Simon.
Gerd Gigerenzer focuses on how heuristics can be used to make judgments that are in principle accurate, rather than producing cognitive biases – heuristics that are "fast and frugal".
In 2002, Daniel Kahneman and 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) which 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. Heuristics can be considered to reduce the complexity of clinical judgements in healthcare.
Theorized psychological heuristics :
Anchoring and adjustment
Availability heuristic
Representativeness heuristic
Naïve diversification
Escalation of commitment
Affect heuristic
Contagion heuristic
Effort heuristic
Familiarity heuristic
Fluency heuristic
Gaze heuristic
Peak-end rule
Recognition heuristic
Scarcity heuristic
Similarity heuristic
Simulation heuristic
Social proof
Take-the-best heuristic
Most Practised Heuristics :
Availability Heuristic
Availability heuristic, refers to “the tendency to judge the frequency or likelihood of an event by the ease with which relevant instances come to mind” (Baumeister & Bushman, 2008).
Life-long experience has shown us that instances of large classes are remembered better and quicker than instances of less common classes, that likely occurrences are easier to imagine than unlikely ones, and that associate connections are strengthened when two event repeatedly co-occur.
Thus, a person may perhaps estimate the size of a class, the likelihood of an event, or the regularity of co-occurences by evaluating the ease with which the relevant mental operation of “retrieval, construction, or association” can be carried out
Nevertheless, overreliance on availability leads to predictable biases, some of which are illustrated below:
Biases due to the retrievability of instances :
When the size of a class is judged by the availability of its instances, a class whose instances are effortlessly retrieved will seem more numerous than a class of equal frequency whose instances are not as easily retrievable.
Biases due to the effectiveness of a search set:
In a well-known study by Tversky and Kahneman (1973, Experiment 3), subjects were asked, “If a random word is taken from an English text, is it more likely that the word starts with a K, or that K is the third letter?”
The results showed that participantsoverestimated the number of words that began with the letter “k”, but underestimated the number of words that had “k” as the third letter.
Biases of imaginability:
A hypothetical real-life instance that Tversky and Kahneman (1974) reference is the risk involved in an adventurous expedition. The psychologists suggest that the risk involved in an adventurous expedition, for example, is weighed by imagining contingencies with which the expedition is not suited to cope.
If many of these difficult contingencies are heavily imagined, the expedition can be made to appear much more dangerous than actual facts suggest is likely. Contrastingly, the risk involved in the expedition may be largely underestimated if some possible dangers are either difficult imagine, or simply do not come to mind.
Illusory correlation :
Chapman and Chapman (1967) demonstration showed that the co-occurrence of paired distinctive stimuli resulted in an overestimation of the frequency of such pairings.
To test this idea, naïve judges were presented with information concerning several hypothetical mental patients. The data for each patient consisted of a clinical diagnosis and a drawing made by the patient.
Later, the judges estimated the frequency with which each diagnosis, such as paranoia or suspiciousness, had been accompanied by various features of the drawing, such as peculiar eyes.
The subjects markedly overestimated the frequency of co-occurrence of natural associates, such as suspiciousness and peculiar eyes. This effect was labeled illusory correlation.
In their erroneous judgments of the data to which they had been exposed, naïve subjects “rediscovered” much of the common, but unfounded, clinical lore concerning the interpretation of the draw-a-person test.
The Qualitative Heuristic Approach By Gerhard Kleining & Harald Witt :
Qualitative heuristics developed at the University of Hamburg, Germany, try to bring back the qualities of systematic exploration and discovery into psychological and sociological research.
This contribution discusses the historical background, the four basic rules to optimize the chance for discovery, the research process as dialogue, the testing processes, and as an example the methodology to investigate and reevaluate the classical method of introspection.
1. Meaning
Heuristic research using qualitative methods is based on a methodology which has been developed at the University of Hamburg (KLEINING 1982) and has been widely applied .
Our methodology aims at discovery and uses the variables of research design in a certain way to serve this purpose. It suggests to the research person to follow four basic rules, which are specified below.
Qualitative heuristics try to bring back the qualities of exploration and discovery into psychological and sociological academic research.
2. Optimize the Chance for Discovery :
The first two rules refer to the interaction of the research person and research topic; the second pair to the relationship of the data collection and data analysis. All rules are mutually dependent on each other.
Rule 1 :
The research person should be open to new concepts and change his/her preconceptions if the data are not in agreement with them.
The rule suggests a reconsideration of the researcher's scientific position if the data consistently are not in agreement with information taken for granted. In science such "paradoxes" have become prominent starting points for exploration.
Rule 2 : The topic of research is preliminary and may change during the research process. It is only fully known after being successfully explored.
There are famous examples of findings despite opposing definitions—i. e. the discovery of America instead of the sea route to India or of porcelain instead of gold and many discoveries made "by chance".
Rule 3 :
Data should be collected under the paradigm of maximum structural variation of perspectives. If researchers assume that a variable may influence the data they should implement variations.
Structural variations mean sampling of positions in reference to the topic, i. e. when studying an emotion, the collection of data past and present, before and after its occurrence, in different situations, from different respondents, if possible from different times and cultures, by different methods, etc.
The kind of variation will always depend on the theme under study.
Rule 4 :
The analysis is directed toward discovery of similarities. It locates similarities, accordance, analogies or homologies within these most diverse and varied data. It tries to overcome differences.
The rule follows SIMMEL's famous chapter on method saying that "out of complex phenomena the homogeneous will be extracted ... and the dissimilar paralysed" .
3. The Research Process as Dialogue
Research procedures are not linear but dialectical. Material "questions"are asked in a similar way one may ask a person, receiving "answers" and questioning again. Preferably "open" questions are used.
Reading a protocol will suggest which questions to ask. The text should be interrogated from as many different perspectives as possible and the answers analyzed as mentioned above.
The dialogic procedure is a means to adjust the epistemic structure of the researcher to the structure of the phenomenon and brings it in line with itself .
4. Testing the Results
An analysis which has been performed successfully will test itself ("inner validity"). It is valid in case new variations of data and perspectives will not bring new results but confirm the existing ones.
It is reliable if all data can be imputed to the same categories (100%-rule). In addition "testing the limits" of the analysis will show the range within which results are valid.
All research findings as all phenomena in the Humanities are historical which means they are subject to change, whether referring to individuals, groups or societal organizations.
5. Rediscovering the Method of Introspection as an Example
The rules for qualitative heuristic research were guidelines to investigate the method of introspection. Our question was whether methodological changes or variations were able to save the formerly classical later defamed method from damnation. Criteria for a successful procedure were richness of results and inter-subjective ('objective') validity.
A series of experiments were carried out—two on a sudden alarm, two on TV communication, two on acceptance of art movies, several on a number of different emotions, present and retrospective, one as a problem-solving experiment, several on free associations—a total of fourteen.
All experiments had the same design. A certain situation or an event was given as the topic of investigation which everybody participating in the experiments had experienced or was experiencing during the course of the experiment (all done at the Hamburg Workshop on Introspection, 5-8 research persons each).
The event was observed and reflected on by introspection, the experience recorded individually in writing and afterwards communicated verbally to the co-workers in the group for the purpose of stimulating the individual to complete and further differentiate his/her experience.
There was no discussion or argument about the validity of individual experience. Finally the protocols were analyzed by one or several researchers individually.
In part, the results confirmed common sense; in part however, they provided strikingly new insights. Overall, the results were a clear argument for re-establishing of the method of introspection.
Most of all, a way to observe the "inner space" of experience more directly was found than it seems possible when using other research methods, and a most promising way to study its structure and inner dynamics.
Application of heuristics to the method of introspection led to very differentiated and reliable results which clearly suggest reactivation and revitalization of the method of introspection as a research tool and should encourage researchers to reconsider the reservations and prejudices against introspection and to overcome at least some of them.
Representativeness Heuristic By Gillian Fournier
A common fallacy wherein people determine the probability or frequency of an event based on assumptions or past experience. This mindset is based in the idea that we as a people need to categorize our lives.
Sometimes when we cannot manage to fit a situation into a defined category, we continue to try to find meaning by assigning it to a secondary level of an already completed organizational system.
For instance, maybe we have only met people who were rich that lived in Connecticut. This knowledge will therefore make us generalize that most people in Connecticut are wealthy.
Another Example :
Many people erroneously support the so-called gambler’s fallacy, the belief that runs in good and bad luck can occur.
For example, if a coin toss turns up heads multiple times in a row, many people think that heads is a more likely occurrence in the next toss to “even things out”, even though each toss is an independent event not connected to the toss before or after it.
A view from Philosophy
Stories and metaphors can be termed heuristic in a 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 , if one would opt for certain principles and carry them through rigorously.
"Heuristic" is also often commonly used as a noun to describe a rule-of-thumb, procedure, or method. Philosophers of science have emphasized the importance of heuristics in creative thought and constructing scientific theories.
A view from Legal side
(1) Drinking Age :
In the United States the legal drinking age is 21, 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.
(2) Patent Laws :
Patents are justified on the grounds that inventors need to be protected in order to have incentive to invent. It is therefore argued that, in society's best interest, inventors should be issued with a temporary government-granted monopoly on their product, so that they can recoup their 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.
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.
A view from Computer science
In computer science, a heuristic is a technique designed to solve a problem that ignores whether the solution can be proven to be correct, but which usually produces a good solution or solves a simpler problem that contains or intersects with the solution of the more complex problem.
Most real-time, and even some on-demand, anti-virus scanners use heuristic signatures to look for specific attributes and characteristics for detecting viruses and other forms of malware.
Heuristics are intended to gain computational performance or conceptual simplicity, potentially at the cost of accuracy or precision.
A heuristic method can accomplish its task by using search trees. However, instead of generating all possible solution branches, a heuristic selects branches more likely to produce outcomes than other branches. It is selective at each decision point, picking branches that are more likely to produce solutions.
In human-computer interaction, heuristic evaluation is a usability-testing technique devised by expert usability consultants. In heuristic evaluation, the user interface is reviewed by experts and its compliance to usability heuristics is assessed, and any violating aspects are recorded.
A view from Software interface design
A proper Software Requirements Specification (SRS) models the heuristics of how a user will process the information being rendered on-screen.
An SRS is ideally shared with the end-user well before the actual Software Design Specification (SDS) is written and the application is developed, so users' feedback about their experience can be used to adapt the design of the application.
This saves much time in the Software Development Life Cycle (SDLC). Unless heuristics are adequately considered, the project will likely suffer many implementation problems and setbacks.
A view from Engineering
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 which are available to engineers 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.
Conclusion :
Heuristic, thus, provides a greater picture of solution to a problem. It not only narrows down the issue but provides us with relevant data to meet our needs.
- By Sunil R Yadav
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