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Cognitive Traps: Heuristics, Bias, Misconceptions, Fallacies and Abstract Inferences Cognitive Traps: Heuristics, Bias, Misconceptions, Fallacies and Abstract Inferences
by Murray Hunter
2013-01-07 12:32:29
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To handle the enormous amounts of incoming information and perform the decisions that have to be made requires some form of mechanisms that can ‘short-cut’ the interpretive and decision processes (Finucane et.al 2000). Heuristics and biases are a means to achieving this and as a consequence have an influence on our perception and reasoning. Heuristics assist decision making under uncertainty because of insufficient information from the environment. Heuristics and other biases compensate and thus assist people in seeing potential opportunities that others don’t (Gaglio & Katz 2001). They also influence how strategies are developed (Busenitz & Barney 1997, Mitchell et al. 2002, Alvarez & Busenitz 2001).

Heuristics are ‘short-cuts’, ‘rules of thumb’, decision rules or templates that aid quick judgments and decisions. Heuristics become embedded within our belief system. They can also be influenced by our deep motivations and reflect our social conditioning. Heuristics and other biases become intertwined within our knowledge structures and become a factor of influence in the assessments, judgments and decisions we make involving opportunity evaluation (Mitchell et al. 2004). They are part of the decision making process (Wright et. al. 2000). In effect heuristics are our programmed system of ‘common sense’.

Heuristics have the potential to assist the decision making process by cutting down on the person’s information load (Gowda 1999). They allow a person to make quick decisions about opportunities without undertaking formal analysis which would tend to highlight problems, thus preventing its exploitation[1]. Heuristics are important when windows of opportunity are very short (Tversky & Kahneman 1974). They also help in making quick strategy choices, saving time and adding to flexibility. Heuristics make up for lack of experience (Alveraz & Busenitz 2001) and drive intuition, which is independent of inputs from the cognitive perception process (Gowda 1999). This will trigger off the creativity process by imposing an alternative reality to what is perceived through the senses.

On the negative side, heuristics can become cognitive biases. Cognitive biases are errors of judgment based on misconceptions of the facts, memory errors, probability errors, motivational factors, and/or social influences. These are the basis of irrational reasoning which can lead to all sorts of mistakes in judgment (Baron 1998). The general conditions that people work under, particularly if it an entrepreneurial environment will normally be characterized with information overload, uncertainty, strong emotions, time pressure, fatigue and the need to do unfamiliar things with little prior experience. This type of situation is a stressful one and a potential trigger for distortion in perception and reasoning. This usually occurs without a person’s conscious knowledge of the fact (Wilson et. al. 1996). Human reliance on heuristics and biases tends to increase in busy environments described above (Gilbert, et. al. 1988), especially when immediate answers are required (Gilbert & Osborne 1989). This is where lots of irrelevant information works its way into the reasoning process (Chapman & Johnson 2003) and leads to cognitive biases that contribute to irrational and less than optimal decisions.

Heuristics and cognitive biases are believed to be caused by the process of attribute substitution. Attribute substitution occurs when a person has to make a judgment (of an attribute target) that is very complex. As a consequence of the complexity, the mind substitutes a more easily calculated heuristic attribute to simplify complexity (Kahneman & Frederick 2002). This occurs when the target attribute is relatively unavailable through reasoning (answer cannot be easily retrieved through memory), so an associate attribute (heuristic) is substituted. This process occurs because the heuristic is easily available in memory (i.e., a neural perception or primed in memory[2]) and this process is not detectable through the person’s reflective system. The attribute substitution process combines available knowledge and experience into heuristics that drive a new idea forward.

It is very difficult to detect heuristics and biases. However they can sometimes be picked up in narrative, as phrases like ‘I think’, ‘I feel’, ‘I believe’, ‘I reckon’ or ‘it is unlikely that’, etc. It is also very difficult to split heuristics from cognitive biases. In pragmatic terms, heuristics and cognitive biases are built upon a person’s belief system. However the cognitive bias is tended to be founded on misconceptions. Table 1. is a list of some heuristics and Table 2. is a list of common cognitive biases.

Table 1. A List of Some Heuristics.

Type of Heuristic


Availability Heuristic

The tendency to recall or imagine frequently occurring and critical events more easily than less occurring events.

Hindsight Heuristic

Using the decisions made in similar events of the past as a guide to the decision.


Use of a similar decision made previously.

Input Biases

The reliance of selective data due to availability which leads to false perception of situations.

Misinterpretation of Principal of Sampling

Thinking there is a correlation between two variables when there really isn’t.

Operational Biases

A limited amount of information from the past forms the basis of a decision.

Output biases

Decision makers unconsciously influence the result.

Representativeness Heuristic

Generalization about a person or event that leads to the consideration of only a few variables.

Satisfying representativeness

The search for a solution that is acceptable to all rather than the optimal one.


Facts about a situation are ignored to reduce the complexity of the problem.

Table 2. A List of Common Cognitive Biases.

Type of Bias


Affect Infusion

Affected states produced by one source influence judgments and decisions about other unrelated sources.

Ambiguity Effect

Avoiding options where missing information make the probability appear ‘unknown’.


A tendency to over rely on past or irrelevant information or references in making a decision.

Attention Bias

A tendency to neglect relevant information when making decisions.

Authority Bias

A tendency to give extremely important weight to the opinions of people in authority.

Availability Cascade

A process where collective belief is strengthened through regular public discourse.

Bandwagon Effect

A tendency to do and/or believe things because many others do or believe it.

Belief Bias

Where someone’s evaluation of the logical strength of an argument is biased by the believability of the conclusion.

Black Swan Effect

A tendency to be blind to random events[3].

Clustering Illusion

The tendency to see patterns when patterns do not exist.

Confirmation Bias

A tendency to search of look for information that confirms one’s own preconceptions.

Congruence Bias

The tendency to test one hypothesis without considering possible alternative hypothesis.

Consistency Bias

Remembering previous attitudes and behaviour as present attitudes.

Contrasting Effect

Enhancing or diminishing the importance of a measurement when compared with another object.

Counterfactual Thinking

A tendency to imagine what might have been the case, given a particular situation.

Distinction Bias

A tendency to evaluate two options as more dissimilar when they are evaluated together than when they are evaluated separately.

Egocentric Bias

The desire of a positive image.

Endowment Effect

Where people demand much more for giving up an item than they would be willing to pay to acquire it.

Escalation of Commitment

A tendency to keep on investing time, effort and money in losing courses of action because of the initial commitment.

Expectation Bias

The tendency to believe data that agrees with a person’s expectations and discard data that is outside their expectations.

Exposure Effect

A tendency for people to express a liking for something only because they are familiar with it.

Framing Effect

Where presenting a problem in a different way (frames) will lead to a different conclusion.

Fundamental Attribution Bias

A tendency for people to over emphasize personality based explanations for behaviour observed in other people while under estimating situational influences.

Halo Effect

The tendency for people to make attributions about something based on past performance[4].

Hawthorne Effect

A tendency for people to perform or perceive differently when they know they are being observed.

Hindsight Bias

Seeing past events as being predictable .i.e., ‘I knew it all along’.

Hyperbolic Discounting

A tendency for people to have a preference for an immediate pay out rather than a delayed pay out.

Illusionary Correlation

A belief that there is a relationship between two factors (a correlation) when there isn’t.

Illusion of Control

A tendency for people to believe they control or have influence over certain outcomes where they do not.

Impact Bias

A tendency for people to overestimate the length or intensity of influence of some type of event, effect or happening.

Information Bias

The tendency to seek information although the extra information does not affect any decision.

Irrational Escalation

A tendency to make irrational decisions based upon past rational decisions or justify decisions already made.

Law of Small Numbers

Where a person uses a limited number of population data and generalizes it over a much larger population.

Loss Aversion

The disutility of giving up something that is greater than the utility associated with acquiring it.

Need for Closure

A need to reach a conclusion in a matter to reduce the feeling of doubt and uncertainty.

Neglect of Probability

A tendency to ignore probability when making a decision under uncertainty.

Observer Expectancy Effect

Where a researcher expects a given result and unconsciously manipulates or misinterprets the data to achieve that result.

Omission Bias

The tendency to judge effects as being more harmful than they actually are.

Optimism Bias

A tendency to be over optimistic about the outcomes of planned actions.

Ostrich Effect

Ignoring something obvious in a negative situation.

Overconfidence Bias

A tendency to overestimate one’s knowledge and ability to do a task.

Planning Fallacy Bias

A tendency to underestimate the time it will take to complete a project, to overestimate how much can be completed in a given time or underestimate the amount of funds required for the task.

Positive Outcome Bias

A tendency to believe that good things usually happen to them.

Post Purchase Rationality

A tendency to persuade oneself through rational argument that a previous purchase was the right decision.

Prediction Bias

When people place too much importance on one aspect causing error in making accurate predictions.

Primacy Effect

A tendency to weight initial events more than subsequent events.

Professional Bias

A tendency to look at things according to the ideas of one’s own profession without considering broader points of view.

Projection Bias

A tendency to unconsciously assume that others share the same or similar thoughts, beliefs, values or positions.

Recency Effect

A tendency to weight recent events more than earlier events.

Recollection Bias

A tendency to recall past decisions and events as more rational than they really were.

Restraint Bias

A tendency to overestimate one’s ability to show restraint in a matter or happening.

Rosy Retrospection

The tendency to rate past events more positively than they had actually rated them when the event occurred.

Self Serving bias

A tendency to claim responsibility for successes but not failures.

Selective Perception

A tendency for an expectation to influence perception.

Status quo Bias

A tendency for people to like things to stay relatively the same.


A tendency to see someone and assign them traits and characteristic based on either generalization or prejudice.

Von Restorff Effect

A tendency for something that ‘stands out’ to be remembered.

Wishful Thinking

Making decisions according to what the person wants to happen or imagines rather than according to evidence of alternative outcomes.

Zero-Risk Bias

A tendency to reduce a small risk to zero.

Heuristics and biases have developed through evolution and learning. Our everyday experience continually reinforces them. In healthy situations heuristics will slowly change over time as experience confirms or disproves their validity and application to life situations. This slowly evolves our mental map so it remains relevant with the demands of the environment, so that we perceive things differently over time[5]. Peter Drucker (1994) calls vision the ultimate heuristic, our theory of how we do business. Therefore to survive in times of rapid change, our vision must also continually change.


Misconceptions are false, flawed or mistaken views, opinions or attitudes. Errors and misconceptions are more likely to occur when knowledge about a specific area is inadequate and supports only partial understanding. Generalizations are needed to develop any understanding of a situation or event. This develops misconceptions which are taken as fact and used to grapple with new situations (Nesher 1987, Resnick et. al. 1989).

Misconceptions are wide through the community and form the basis of many heuristics and biases. They are particularly evident in the media. Tversky and Kahneman (1982) found that even professionals widely used the representativeness heuristic and law of small numbers in their work. Misconceptions can be strongly held and resistant to change (Clement 1987). Therefore misconceptions can retard and prejudice learning as new information coming in will tend to be rearranged to support existing misconceptions.


A normal argument consists of one or more premises and a conclusion. An argument can be either deductive where the premises provide complete support for the conclusion or inductive where the premises provide some degree of support for the conclusion. The stronger the premises, the stronger will be the case of the argument. A good deductive argument is therefore forms a valid argument. A good inductive argument is known as a strong inductive argument. A fallacy is an error in the premise or reasoning of the argument. It is not a factual error as the premises may be correct with the conclusion in error. A deductive fallacy is a deductive argument that is invalid. Fallacies therefore have poor premises, poor support for their conclusions, use irrelevant data, or analogies or make claims that are too wide and sweeping for their related premises.

Fallacies are very common in the way we think, reason, and argue cases to both ourselves and others. Fallacies are particularly common when one is very passionate about something. Fallacies can be very persuasive and difficult to detect unless one is continually alert. They are very common in newspapers and the media. Some common types of fallacies are listed in Table 3. below.

Table 3. Some Common Types of Fallacies.



Ad hominen

An argument that attacks the person who holds a view rather than the view itself.

Appeal to Authority

Where something is deemed to be true just because of the position of the person asserting it.

Appeal to emotion

An argument made to appeal to the emotions of prejudice, what might be pleasing and desirable (i.e., utopian), bitterness and spitefulness or flattery to gain support.

Appeal to probability

An argument that assumes because it can happen, it will happen. Murphy’s law is an appeal to probability.

Appeal to Ridicule

An appeal through emotion where an opponent’s argument is made to look ridiculous.

Appeal to tradition

Where something is deemed correct because of the tradition behind it.

Argument by Repetition

When an argument has been discussed extensively and nobody wants to discuss it anymore.

Argumentum ad populum

Where something is claimed to be true just because many people believe it to be true.

Base Rate fallacy

An argument using weak evidence to make a probability judgment, often excluding empirical statistics about the probability.

Cherry Picking

Using selective cases to confirm a particular position while ignoring the bulk portion of the data.

Correlation does not imply causation

Where a correlation between two items does not imply causation.

Existential Fallacy

An argument has two universal premises and a specific conclusion, but the premises do not establish the truth of the conclusion.

False Compromise

An argument that a compromise between two different positions is the best course of action.

False Dichotomy

Where two options are given as the only two options, where there are clearly more.

Gambler’s fallacy

A belief that the outcome of a random event can be predicted from other independent events.

Historian’s fallacy

An assumption the decision makers of a past event viewed the situation from the same perspective and having the same information as those analyzing the decision.

Moving the Goalpost

When evidence is presented to rebuke a specific claim and is dismissed with demands for more evidence.

Naturalistic Fallacy

An argument that natural is good and right, when this may not be the case.

Negative Proof Fallacy

When an argument cannot be proven false, it is presented as being true or because a premise cannot be proven true, then it must be false.

Package-Deal Fallacy

This assumes that because things are grouped together by culture or tradition, then they must be grouped together in that way.

Poisoning the Well

Where adverse information is released about someone in order to discredit anything they say.

Proof by Example

When an argument is given credence through an example.

Psychologist’s Fallacy

When someone observing an event presupposes their own objectively.

Abstract Inferences

Due to our minds being saturated with information, it is impossible to remember detail. To cope with this volume of information our mind develops abstractions or generalizations, simplifying the massive information we have to deal with. Therefore throughout everyday situations inferences are made from specific things we see to help us make quick assessments and decisions. We are usually unaware of the generalizations and inferences we make.

Abstract inferences help us to unconsciously develop emotions for people, things and events. These emotions trigger thoughts that influence the quick decisions we make about these situations. For example, if we were a salesperson we probably wouldn’t wait extra time for a store owner to return if we believe that ‘he never orders anything anyway’. Likewise we won’t undertake extra study for an exam where we believe that ‘I’m not good at this subject anyway’. We regularly make generalizations that we rarely question. These abstractions become a type of schema that influences our decisions and behavior. This is the process that leads to stereotyping.


Figure 1. Informational and Cognitive Influences upon Decision Making.

Figure 1. summarizes our discussion on cognitive traps. The diagram shows the various informational and cognitive mechanisms that influence decision making. When humans face repetitive or similar decision making circumstances there is a tendency for heuristics to develop through attribute substitution. However heuristics are also influenced by misconception, fallacy and abstract inferences. Where these forces are overbearing on perception, cognitive biases will develop which that distort the reasoning process. Reasoning affects both the decision making process and the construction of fallacies and misconceptions as well. When reasoning is affected by biases, the decision making phase may produce less than optimal decisions. On the positive side, heuristics can block perception, replacing it with intuition which can trigger the creative process. The vertical axis shows the volumes of types of information available and the horizontal axis shows the increasing usefulness of information for decision making purposes.



[1] This is one area where entrepreneurial thinking may be very different from management thinking. An entrepreneur without perfect information will act on intuition and hunch. Any analysis will be mental rather than through the formal processes which managers in a company situation will tend to follow. Management analysis of new ideas will tend to frame the question; what is wrong with this idea?, why should it not be exploited?, what will be the potential problems?, etc. Thus analysis can become a very negative paradigm in management preventing new ideas emerging into new strategies.

[2] Priming occurs when an earlier stimulus influences a response to a later stimulus. For example, a person watches a television program the night before on conservation of forests. The next day someone asks the person for their views on conservation. It is likely that the person will give views and ideas that originated from the program on conservation the night before. This is assuming the person does not already have any strong views on the subject.

[3] See Nassim Nicholas Talab (2007), The Black Swan, New York, Random House Inc.

[4] See: Phil Rosenzweig (2007), The Halo Effect, London, Pocket Books, pp. 51-64.

[5] A mental map is a mental model made up of our schema, perceptions of things, people and events, our feelings and personal points of view.


Alvarez, S. A, and Busenitz, L. W, (2001). The Entrepreneurship of resource based theory, Journal of Management, Vol. 27, pp. 755-775.

Baron, R. A. (1998). Cognitive mechanisms in entrepreneurship: why and when entrepreneurs think differently than other people, Journal of Business Venturing, Vol. 13, No. 3, pp. 275-294.

Busenitz, L. W, and Barney, J. B, (1997). Differences between entrepreneurs and managers in large organizations, Journal of Business Venturing, Vol. 12, pp. 9-30.

Chapman, G. B, and Johnson, E. J, (2003). Incorporating the Irrelevant: Anchors in Judgments of Belief and Value, In: Gilovich, T, Griffin, D, and Kahneman, D, (Eds.), Heuristics and Biases: The Psychology of Intuitive Judgment, Cambridge, UK, Cambridge University Press.

Clement, J. (1987). The use of analogies and anchoring intuitions to remediate misconceptions in mechanics, Paper presented to the Annual Meeting of AERA, Washington, DC.

Drucker, P. (1994). Post-Capitalist Society, New York, HarperCollins Publishers.

Finucane, M. L., Alhakami, A., Slovic, P., and Johnson, S. M. (2000). The affect heuristic in judgments of risks and benefits, Journal of Behavioral Decision Making, Vol. 13, No. 1., pp. 1-17.

Gaglio, C. M, Katz, T. A. (2001). The psychological basis of opportunity identification: entrepreneurial alertness, Small Business Economics, Vol. 16, No. 2, pp. 95-111.

Gilbert, D. T., Pelham, B. W., and Krull, D. S., (1988), On cognitive busyness: When person perceivers meet persons perceived, Journal of Personality and Social Psychology, Vol. 54, pp. 733-740.

Gilbert, D. T. and Osborne, R. E. (1989). Thinking Backward: Some curable and incurable consequences of cognitive busyness, Journal of Personality and Social Psychology, Vol. 57, pp. 940-949.

Gowda, M. V. R., (1999). Heuristics, biases and the regulation of risk, Policy Science, Vol. 32, pp. 59-78.

Kahneman, D. and Frederick, S. (2002). Represetativeness Revisited: Attribute Substitution in Intuitive Judgment, In: Gilovich, T, Griffin, D., Kahneman, D., Heuristics and Biases: The Psychology of Intuitive Judgment, Cambridge, UK, Cambridge University press, pp. 49-81.

Mitchell, R. K, Smith, J. B, Morse, E. A, Seawright, H. W, Perero, A. M, and Mckenzie, B, (2002). Are entrepreneurial cognitions universal? Assessing entrepreneurial cognition across cultures, Entrepreneurial Theory and Practice, Vol. 26, No. 4, pp. 9-32.

Mitchell, R. K, Busenitz, L, Lant, J, McDougall, P. P, Morse, E. A, and Smith, B. (2004). The distinctive and inclusive domain of entrepreneurial cognition research, Entrepreneurship, Theory and Practice, Vol. 28, No. 6, pp. 505-518.

Nesher, P. (1987). Towards and instructional theory: The role of students’ misconceptions, For Learning of Mathematics, Vol. 7, No. 3, pp. 33-40.

Resnick, L. B., Nesher, P., Leonard, F., Magone, M., Omanson, S. and Peled, I. (1989). Conceptual basis of arithmetic errors: The case of decimal fractions, Journal of Research in Mathematics Education, Vol. 20, pp. 8-27.

Rosenzweig, P. (2007), The Halo Effect, London, Pocket Books.

Taleb, N. N., (2007). The Black Swan, New York, Random House Inc.

Tversky, A. and Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases, Science, Vol. 185, pp. 251-284.

Tversky, A. and Kahneman, D. (1982). Judgment under Uncertainty: Heuristics and Biases, In: Kahneman, D., Slovic, P., and Tversky, A., (Eds.), Judgment under uncertainty: Heuristics and Biases, Cambridge, Cambridge University Press, pp. 3-20.

Wilson, T. D., Houston, C., Etling, K. M. and Brekke, N., (1996). A new look at anchoring effects: Basic anchoring and its antecedents, Journal of Experimental Psychology: General, Vol. 4, pp. 387-402.

Wright, M., Hoskisson, R. E., Busenitiz, L. W. and Dial, J. (2000). Entrepreneurial Growth through Privatization: The Upside of Management Buyouts, Academy of Management Review, Vol. 25, No. 3, pp. 591-601.


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Emanuel Paparella2013-01-07 13:32:38
Had the title of the above piece been sent to Francis Bacon, the father of the scientific method, with a request that he guess what it is all about, he might have hesitated and might have asked for more information than the mere title. He might have received as a reply a nomenclature of some of the areas touched upon in the piece such as: belief system, opportunity evaluations, biases vs. certain knowledge, cognitive biases, mental map, vision as the ultimate heuristic, misconceptions, intuition, decision making purposes (which could be the summation of the title), ad hominem arguments, inductive arguments, existential fallacy, abstract inferences. Francis Bacon who knew the history of philosophy well, both ancient and modern, would have surmised at first that the article would be a philosophical article on logic and how it may help the existential situation of Man. Upon receiving the article he would enthusiastically have declared that it is a confirmation of his premise that KNOWLEDGE IS POWER.

Had the same been sent to Socrates however, some 24 centuries ago, he would have been struck by the listed “existential fallacy” and would have immediately critiqued it by elucidating the real existential fallacy in the piece; namely that KNOWLEDGE IS NOT POWER BUT VIRTUE. He would have elaborated that science focuses on the “how” and the manipulation of things in the phenomenon and the production of goods, and philosophy focuses on the “why” and the very meaning and purpose of man's life. Unlike the sophists of old who were teaching the young on how to win arguments via the power of persuasion and rhetoric, that is, how to sell the goods and gain power, he was teaching them why, within the human condition and the nature of man it was important to search for the truth and go beyond making a living by commerce and entrepreneurship. In other words, there is a higher purpose than the search for the making and distribution of the goods, and it is the search for the Good, the Beautiful and the True. He would have pointed out that the lack of dialogue between those two cultures, one affirming that knowledge is power and money, the other affirming that knowledge is virtue, is the real existential drama of the modern brave new world which thinks itself enlightened with nothing to learn from the ancients.

There was a man not too many years ago who pointed out in detail how those two cultures tragically bypass each other like two ships in the middle of the night. His name is C.P. Snow and he wrote a book about this existential problematic in 1959. Perhaps it is time to revisit the book?

Leah Sellers2013-01-07 20:48:10
Dear Mr. Murray and Brother Emanuel,
Gentlemen, y'all both put a wonderful smile of delight upon my Face and my Psyche.
Both of your Assertions are Correct, but I find Brother Emanuel's more POWERFUL.
Wouldn't it be marveloous if We All could connect our much Needed VIRTUE to our Need for much MOney and Power - ha !
Now, that would be a World Transformed !

Emanuel Paparella2013-01-09 08:35:21
Trouble is, Leah, that we'd have to contend with the Aristotelian principle of non contradiction: a thing cannot be and not be at the same time. It would seem that knowledge cannot be power and virtue at the same time. Perhaps it can be power at certain times and virtue at other times but that would be a paradox more than a violation of the principle of non contradiction.

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