Discussion Of Biases And Heuristics In The Foresight Scenario Literature
Nestik has published a comprehensive discussion on the psychological mechanisms of collective foresight activities. He outlines a variety of cognitive biases and socio-psychological effects that occur during foresight sessions and hinder group reflection in the context of corporate foresight. The heuristics identified by Nestik overlap to some extent with the heuristics we identify as relevant in the context of a more specific process, the scenario approach.
Heuristics In Judgment And Decision
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Heuristics are simple strategies or mental processes that humans, animals, organizations and machines use to quickly form judgments, make decisions, and find solutions to complex problems. This happens when an individual focuses on the most relevant aspects of a problem or situation to formulate a solution.
Some heuristics are more applicable and useful than others depending on the situation. Heuristic processes are used to find the answers and solutions that are most likely to work or be correct. However, heuristics are not always right or the most accurate. While they can differ from answers given by logic and probability, judgments and decisions based on a heuristic can be good enough to satisfy a need. They are meant to serve as quick mental references for everyday experiences and decisions. In situations of uncertainty, where information is incomplete, heuristics allow for the less-is-more effect, in which less information leads to greater accuracy.
Heuristics And Shopper Behavior
In order to understand shopper behavior, its important to understand the and reach consumers at the moment that most influence their decisions. One of the key concepts to understand concerning the psychology of shopping is heuristics.
A heuristic is a mental shortcut that helps us make decisions and problem solve quickly. They allow us to shorten the decision-making time without always having to think about the next course of action. For example, over time we recognize if a website is trustworthy or not. Does it look well laid out and designed or does it have a lot of annoying banner ads and graphics? We then store and use this information the next time we go online to quickly decide if a website is trustworthy or not. Due to our previous learning, the second time the process doesnt require as much mental effort.
There are 4 types of heuristics that influence shopper behavior:
The availability heuristic can be used in marketing by giving examples of the results your product has brought forth in order to make it easier for potential customers to imagine an outcome they could likely achieve if they chose it. By giving potential customers a taste of what they could experience with your product, youre not only exciting the consumer imagination, but youre also imprinting a positive association in their memory between your product and the subsequent attractive outcome they have the power to achieve.
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When Do People Not Follow Recognition
The evidence just reviewed suggests that in particular environments people might exploit the fact that they have heard of one object but not another to infer further differences between the objects. Yet an adaptive use of the recognition heuristic also requires that people do not always follow recognition. We now consider characteristics of task environments that make them inappropriate for the application of the recognition heuristic and ask whether people tend to suspend the use of the heuristic in those cases.
Conclusive criterion knowledge
Peoples ability to construct a local mental model based on conclusive criterion knowledge is also likely an explanation for the results in Oppenheimer . He presented Stanford students with decision tasks comparing the population sizes of nearby cities that were highly recognized but rather small with fictitious cities . In deciding which city was larger, participants chose the recognized city in only 37% of the cases. Participants presumably knew that the nearby cities were very small and inferred that the unrecognized foreign cities may be larger.
Unknown reference class
Figure 2. Association between recognition validity in 11 different environments and the observed proportion of inferences following the recognition heuristic.
Discrediting source knowledge
How Do You Use Heuristic In A Sentence
Heuristic sentence example Doubtless what we have is in the main a reflex of the heuristic character of Aristotles own work as pioneer. heuristic evaluation was applied to a set of games. The feeling was that evolutionary algorithms should be better able to cope with noise than heuristic state merging methods.
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Why Heuristic Evaluation Is Used
A heuristic is a fast and practical way to solve problems or make decisions. In user experience design, professional evaluators use heuristic evaluation to systematically determine a designs/products usability. As experts, they go through a checklist of criteria to find flaws which design teams overlooked.
How The Availability Heuristic Works
When you are trying to make a decision, a number of related events or situations might immediately spring to the forefront of your thoughts. As a result, you might judge that those events are more frequent or probable than others. You give greater credence to this information and tend to overestimate the probability and likelihood of similar things happening in the future.
For example, after seeing several news reports about car thefts, you might make a judgment that vehicle theft is much more common than it really is in your area. This type of availability heuristic can be helpful and important in . When faced with a choice, we often lack the time or resources to investigate in greater depth.
Faced with the need for an immediate decision, the availability heuristic allows people to quickly arrive at a conclusion.
This can be helpful when you are trying to make a decision or judgment about the world around you. For example, would you say that there are more words in the English language that begin with the letter t or with the letter k?
You might try to answer this question by thinking of as many words as you can that begin with each letter. Since you can think of more words that begin with t, you might then believe that more words begin with this letter than with k. In this instance, the availability heuristic has let you to a correct answer.
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Relevance Of Heuristics And Biases When Thinking About The Future
When moving through the world, individuals constantly draw conclusions, make decisions or infer judgments. Some of these judgments seem insignificant and unintentional, like which parts of the environment to pay attention to, for example which road to choose on a stroll through the city. Others appear to be more deliberate and consciously derived like deciding on a career or buying an apartment. The amount of information an individual is confronted with is infinite. All of this information could be processed, evaluated, integrated, and used in decision-making.
The Use Of Heuristics
A heuristic is a rule-of-thumb, or a guide toward what behavior is appropriate for a certain situation. Heuristics are also known as mental shortcuts . Such shortcuts can aid us when we face time pressure to decide, or when conditions are complex and our attention is divided. A heuristic is a well-learned adaptation that allows us to decide quickly and with low effort. Employing heuristics will yield an outcome that is positive or at least satisfactory much of the time. When Daniel Kahneman and Amos Tversky set up experiments to test whether people followed rational models of decision making, they frequently discovered that people deviated from the rational model, but they did so for good reasons. Participants in these cases appeared to be using heuristics in order to make a rapid decision with less effort that could be relied upon to yield a positive outcome much of the time. Kahneman and Tversky, along with numerous other behavioral scientists, have characterized a wide array of heuristics that occur when people make decisions. In this section, we will review some of the most well-established and interesting heuristics that people use and how these occur in our everyday lives.
S. Dhami, A. al-Nowaihi, in, 2012
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Heuristics And Biases In Psychological Research
The study of cognitive mechanisms involved in human decision-making has been a central research topic for psychologists for the better part of the last century and remains in the research focus to date. In the foresight community, these cognitive mechanisms have also started to receive some attention . The term most often associated with this field of study is âbiases and heuristics.â Cognitive biases in general describe systematic errors or deviations from norms or rationality in perception, memory, cognition, and judgment . Biases are in substantial parts unconscious and often result from the use of heuristics. The term heuristics describes mental shortcuts or simple rules that enable an individual to engage with its surroundings in an efficient way . But they can also lead to the construction of highly subjective images of those surroundings/reality.
Inferences About The Truth Of A Statement
A common inference problem in the real world is to judge whether a statement encountered is correct or false. What is the role of recognition, or more generally memory traces created by previous encounters with a statement, when making such inferences? Hasher et al. presented participants, over a period of 3 weeks, with statements that were either true or false . Most of the statements appeared only once, but some were presented repeatedly across the three sessions. Hasher et al. found that when participants subsequently indicated their confidence that a statement was true, they expressed an increasing confidence in the veracity of a statement the more frequently it was repeated. This reiteration effect can be taken to indicate that participants used the strength of the memory traces of the statements as an indication of how likely the statement was to be true.
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Adaptive Use Of The Recognition Heuristic
Gigerenzer et al. assumed that the recognition heuristic is one of a set of strategies the adaptive toolbox that decision makers have at their disposal. One of the conditions in which the recognition heuristic should be applied is when recognition is correlated with the criterion. Conversely, when recognition is only a poor cue, the recognition heuristic should not be used . To quantify the accuracy achievable by using the recognition heuristic to make criterion comparisons among a class of objects , Goldstein and Gigerenzer proposed the recognition validity. It is calculated as
where R and W equal the number of correct and incorrect inferences, respectively, that are made on all object pairs when one object is recognized and the other is not and the recognized object is judged to have the higher criterion value. The validity of object knowledge beyond recognition, which can be used to make a decision when both objects are recognized, knowledge validity, is defined as the proportion of correct inferences among the cases where both objects are recognized.
What Is Representativeness Heuristic
Representativeness heuristic bias occurs when the similarity of objects or events confuses peoples thinking regarding the probability of an outcome. People frequently make the mistake of believing that two similar things or events are more closely correlated than they actually are. This representativeness heuristic is a common information processing error in behavioral finance theoryBehavioral FinanceBehavioral finance is the study of the influence of psychology on the behavior of investors or financial practitioners. It also includes the subsequent effects on the markets. It focuses on the fact that investors are not always rational.
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Protecting Against The Representativeness Heuristic
Lets look at strategies to protect against this heuristic as an investor. You may want to consider keeping an investment diary. Write down your reasoning and then match it to the outcomes, whether good or bad.
In financial markets, one example of this representative bias is when investors automatically assume that good companies make good investments. However, that is not necessarily the case. A company may be excellent at their own business, but a poor judge of other businesses.
Another example is that of analysts forecasting future results based on historical performance. Just because a company has seen high growth for the past five years doesnt necessarily mean that trend will continue indefinitely into the future.
When Is Recognition Not A Good Predictor
Despite the apparent breadth of domains in which recognition can be exploited to infer a criterion, recognition, of course, does not predict everything. In which kinds of environments does it fail? First, recognition will not be correlated with criteria where people or the media talk about everything along the criterion dimension equally often or talk primarily about both ends of the dimension . In such cases more mentions of an object does not imply a high criterion value. To illustrate, Pohl found that the population of Swiss cities, but not their distance from the city Interlaken, is correlated with recognition. Correspondingly, he reported high reliance on the recognition heuristic when people were asked to judge which of two cities is larger, while when asked to judge which was closer to Interlaken, the reliance on recognition dropped to chance level.
Figure 1. Hypothetical plot for a task environment in which the recognition heuristic is not ecologically rational: predicting the frequency of diseases. Here, the number of mentions of a disease in the media increases toward both extremes of the criterion dimension, for negatively correlated reasons . As a consequence, recognition is uncorrelated with the criterion, and is around 0.5.
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The Pitfalls Of Heuristics
Heuristic algorithms are often employed because they may be seen to “work” without having been mathematically proven to meet a given set of requirements.
Great care must be given when employing a heuristic algorithm. One common pitfall in implementing a heuristic method to meet a requirement comes when the engineer or designer fails to realize that the current data set doesn’t necessarily represent future system states.
While the existing data can be pored over and an algorithm can be devised to successfully handle the current data, it is imperative to ensure that the heuristic method employed is capable of handling future data sets. This means that the engineer or designer must fully understand the rules that generate the data and develop the algorithm to meet those requirements and not just address the current data sets.
A simple example of how heuristics can fail is to answer the question “What is the next number in this sequence: 1, 2, 4?”.One heuristic algorithm might say that the next number is 8 because the numbers are doubling; leading to a sequence like 1, 2, 4, 8, 16, 32… Another, equally valid, heuristic would say that the next number is 7 because each number is being raised by one higher interval than the one before; leading to a series that looks like 1, 2, 4, 7, 11, 16.
Statistical analyses should be conducted when employing heuristics to estimate the probability of incorrect outcomes.
When Do Peoples Decisions Follow Recognition
The recognition heuristic in inference tasks
In general, in domains where recognition is a good predictor , a large proportion of peoples judgments in laboratory experiments are in line with the recognition heuristics predicted choices . Goldstein and Gigerenzer observed that when American students were asked which of two German cities is larger and they recognized one city but not the other, they picked the recognized one in 89% of the cases . Similarly high rates of decisions in line with recognition were found for Swiss, Belgian, Italian , and British cities , all of which are domains where the recognition validity is high. Pohl found evidence for a frequent use of the recognition heuristic for other geographic materials, such as mountains, rivers, and islands.
In their application of the recognition heuristic to the sports domain, Snook and Cullen asked their participants to judge the relative number of career points achieved by different NHL players. As mentioned above, recognition is a highly useful piece of information for this task, and accordingly, a recognized player was chosen over an unrecognized one 95% of the time, even when participants had no further knowledge about the recognized player. This also led them to correct inferences 87% of the time.
The recognition heuristic in forecasting tasks
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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 heuristics, which lead to certain biases, System 2 can give rise to other biases, such as the confirmation bias.12 Systems 1 and 2 complement each other, and using them together can lead to more rational decision-making. That is, we shouldnt make judgments automatically, without a second thought, but we also shouldnt overthink things to the point where were 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.
The Elimination By Aspects Model
The elimination by aspects model was first proposed by psychologist Amos Tversky in 1972. In this approach, you evaluate each option one characteristic at a time beginning with whatever feature you believe is the most important. When an item fails to meet the criteria you have established, you cross the item off your list of options. Your list of possible choices gets smaller and smaller as you cross items off the list until you eventually arrive at just one alternative.