Examples of clustering illusion: 1. The Virgin Mary Bread 2. Here is a fast tip about Perspective lines made with the help of Cluster v2. More info: http://www.tniich.com/cluster. The 'Illusion of Asymmetric Insight' occurs where we believe we understand others better than they understand themselves.
Understanding people and events, collecting data and evidence, and formulating perspectives on events – investigation requires a considerable amount of reasoning on the part of individuals and teams. Investigators need to be aware of the cognitive biases that might impact their own decision-making process as well as their peers. If an investigator forms a theory behind an incident and is unwilling to change their view to account for new and contradictory evidence, this is an example of cognitive bias.
Cognitive biases are patterns of deviation from rational thinking. These can apply to any scenario, whether in daily interactions with peers or even when making decisions about what to purchase in a store. For investigators, however, cognitive biases can be quite dangerous when investigating a crime as they can lead to gathering the wrong type of evidence, or worse yet, identifying the wrong person responsible for the threat.
The following common cognitive biases are examples of the type of flawed reasoning that might impact an investigation
1. Outcome Bias: Judging a decision based on its outcome
Outcome bias is an error made in evaluating the quality of a decision when the outcome of that decision is already known. For example, an investigator might make use of outcome bias to compel someone to testify by indicating that other witnesses have come forward with similar information.
2. Confirmation Bias: Favoring information that confirms preconceptions
Confirmation bias is the tendency to bolster a hypothesis by seeking evidence consistent with beliefs and preconceptions while disregarding inconsistent evidence. In criminal investigations, preference for hypothesis-consistent information could contribute to false convictions by leading investigators to disregard evidence that challenges their theory of a case.
3. Automation Bias: Favoring automated decision-making
Automation bias is the preference for automated decision-making systems and ignoring contradictory conclusions made without automation, even if they are correct. This type of bias is increasingly relevant for investigators who rely on automated systems. For example, a cybersecurity professional may assume their system is not under threat given the lack of automated alerts, despite concerns from specific individuals who believe they are being targeted by hackers. Automation might also identify a threat that is not actually there. Automation bias would compel investigators to pursue the problem regardless of facts that contradict it, thereby wasting valuable resources that could be applied elsewhere.
4. Clustering Illusion: Seeing patterns in random events
Clustering illusion is the intuition that random events which occur in clusters are not really random events. An investigator might uncover information that has limited correlation but, given false assumptions about the statistical odds of that correlation, they might suffer from fallacious reasoning. For example, an investigation into a suspect's online footprint might uncover the person's name associated with multiple posts with a similar sentiment. However, by looking at additional information and conducting in-person interviews, they could eliminate this bias by determining the posts were made by two different persons.
5. Availability Heuristic: Overestimating the value of information readily available
The availability heuristic is a mental shortcut that relies on immediate examples that come to a given person's mind when evaluating a specific decision. Heavily publicized risks are easier to recall than a potentially more threatening risk. This impinges on individual perspectives but can also guide public policy.
6. Stereotyping: Expecting a group or person to have certain qualities without having real information about them
/math_figures/random.GIF "Clustering Illusion Example")
Stereotyping involves an over-generalized belief about a particular category of people. Stereotypes are generalized because one assumes that the stereotype is true for each individual person in the category. Stereotypes can be helpful in making quick decisions but they may be erroneous. Stereotypes are said to encourage prejudice. Stereotyping is the key driver behind racial profiling, whereby members of a specific race or ethnicity are associated with crimes typically believed to be perpetrated.
7. Law of the Instrument: Over-reliance on a familiar tool
Law of the instrument, or law of the hammer, is a bias that involves an over-reliance on a familiar tool. As Abraham Maslow said, 'I suppose it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.' This is especially important for investigators in the digital age. As old behaviors are replaced with new behaviors that intersect with the web, investigators must update their toolkit to be able to investigate crimes. For example, the thriving online drug trade requires narcotics investigators to reexamine the tools and tactics they use to solve a case to gain a better understanding of the people and events involved.
8. Blind-spot Bias: Failing to recognize one's own biases
Blind-spot bias, while last in our list, should always be top of mind. Investigators must continually assess possible biases that may impact their thinking unconsciously, and make conscious attempts to address them. People tend to attribute bias unevenly so that when people reach different conclusions, they often label one another as biased while viewing themselves as accurate and unbiased.
Great investigators will understand and reflect on these cognitive biases continually during an investigation. Mental noise, wishful thinking – these things happen to the best of us. So remember always: Check your bias.
Backfire Effect, Base Rate Fallacy, Clustering Illusion, Conjunction Fallacy & False Dilemma
In the fourth article of the Cognitive Biases and Fallacies, How Are They Exploited series, you will learn about examples of cognitive biases and fallacies, and how they are used against you by the media, politicians, social engineers and more.
For more articles on the topic, check out my cognitive biases and fallacies category.
Cognitive biases are systematic patterns of deviation of the norm, while a fallacy is a mistaken belief. The inputs our senses feed us become distorted via biases and fallacies, which is why it is essential to learn them, study them and identify them, so we can learn to make better decisions in the future.
In this article the following Cognitive Biases and Fallacies will be discussed:
- Backfire Effect.
- Base Rate Fallacy.
- Clustering Illusion.
- Conjunction Fallacy.
- False Dilemma.
Business Clustering Examples
Previous instalments of the Cognitive Biases & Fallacies, How Are They Exploited series: article 1, article 2 & article 3.
Examples Of Clustering
Cognitive Biases & Fallacies #16: Backfire Effect
In the face of contradictory evidence, established beliefs do not change but actuallyget stronger.
Backfire Effect Definition. Source: Rationalwiki
People display this bias when they gatheror remember information selectively, or when they interpret it in a biased way.The effect is stronger for emotionally charged issues and for deeply entrenchedbeliefs.
How is theBackfire Effectexploited
This can be exploited by feigning interest in removing someone from a belief position you have put them in. Losing the argument will have the added effect of them being able to remember winning.
Corporations know that they are doing something that is harmful but nonetheless promote denialism, even publicly admitting their product is harmful while simultaneously covertly funding astroturf groups that promote the denialist message.
Small pause: if you're enjoying this essay, make sure to join the Newsletter to never miss any!
Cognitive Biases & Fallacies #17: Base Rate Fallacy
It is both a logical fallacy and a cognitive bias.
Base rate fallacy, also known as base rate neglect or base rate bias, is an error in thinking. If presented with related base rate information and specific information, the mind tends to ignore the former and focus on the latter.
Base Rate Definition. Source: Wikipedia.Base Rate FallacyExamples
'One death is a tragedy; one million is a statistic.' -Joseph Stalin.
How the Base Rate Fallacy exploited
The media exploits it every day, finding a story that appeals to a demographic and showing it non-stop.
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There is always and agenda behind whenever one tragedy, one death or one instance is made out to seem more important than another of statistically equal relevance. People trying to use emotion to conjure a reaction always have an agenda.
Cognitive Biases & Fallacies #18: Clustering Illusion
Examples of clustering illusion: 1. The Virgin Mary Bread 2. Here is a fast tip about Perspective lines made with the help of Cluster v2. More info: http://www.tniich.com/cluster. The 'Illusion of Asymmetric Insight' occurs where we believe we understand others better than they understand themselves.
Understanding people and events, collecting data and evidence, and formulating perspectives on events – investigation requires a considerable amount of reasoning on the part of individuals and teams. Investigators need to be aware of the cognitive biases that might impact their own decision-making process as well as their peers. If an investigator forms a theory behind an incident and is unwilling to change their view to account for new and contradictory evidence, this is an example of cognitive bias.
Cognitive biases are patterns of deviation from rational thinking. These can apply to any scenario, whether in daily interactions with peers or even when making decisions about what to purchase in a store. For investigators, however, cognitive biases can be quite dangerous when investigating a crime as they can lead to gathering the wrong type of evidence, or worse yet, identifying the wrong person responsible for the threat.
The following common cognitive biases are examples of the type of flawed reasoning that might impact an investigation
1. Outcome Bias: Judging a decision based on its outcome
Outcome bias is an error made in evaluating the quality of a decision when the outcome of that decision is already known. For example, an investigator might make use of outcome bias to compel someone to testify by indicating that other witnesses have come forward with similar information.
2. Confirmation Bias: Favoring information that confirms preconceptions
Confirmation bias is the tendency to bolster a hypothesis by seeking evidence consistent with beliefs and preconceptions while disregarding inconsistent evidence. In criminal investigations, preference for hypothesis-consistent information could contribute to false convictions by leading investigators to disregard evidence that challenges their theory of a case.
3. Automation Bias: Favoring automated decision-making
Automation bias is the preference for automated decision-making systems and ignoring contradictory conclusions made without automation, even if they are correct. This type of bias is increasingly relevant for investigators who rely on automated systems. For example, a cybersecurity professional may assume their system is not under threat given the lack of automated alerts, despite concerns from specific individuals who believe they are being targeted by hackers. Automation might also identify a threat that is not actually there. Automation bias would compel investigators to pursue the problem regardless of facts that contradict it, thereby wasting valuable resources that could be applied elsewhere.
4. Clustering Illusion: Seeing patterns in random events
Clustering illusion is the intuition that random events which occur in clusters are not really random events. An investigator might uncover information that has limited correlation but, given false assumptions about the statistical odds of that correlation, they might suffer from fallacious reasoning. For example, an investigation into a suspect's online footprint might uncover the person's name associated with multiple posts with a similar sentiment. However, by looking at additional information and conducting in-person interviews, they could eliminate this bias by determining the posts were made by two different persons.
5. Availability Heuristic: Overestimating the value of information readily available
The availability heuristic is a mental shortcut that relies on immediate examples that come to a given person's mind when evaluating a specific decision. Heavily publicized risks are easier to recall than a potentially more threatening risk. This impinges on individual perspectives but can also guide public policy.
6. Stereotyping: Expecting a group or person to have certain qualities without having real information about them
Stereotyping involves an over-generalized belief about a particular category of people. Stereotypes are generalized because one assumes that the stereotype is true for each individual person in the category. Stereotypes can be helpful in making quick decisions but they may be erroneous. Stereotypes are said to encourage prejudice. Stereotyping is the key driver behind racial profiling, whereby members of a specific race or ethnicity are associated with crimes typically believed to be perpetrated.
7. Law of the Instrument: Over-reliance on a familiar tool
Law of the instrument, or law of the hammer, is a bias that involves an over-reliance on a familiar tool. As Abraham Maslow said, 'I suppose it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.' This is especially important for investigators in the digital age. As old behaviors are replaced with new behaviors that intersect with the web, investigators must update their toolkit to be able to investigate crimes. For example, the thriving online drug trade requires narcotics investigators to reexamine the tools and tactics they use to solve a case to gain a better understanding of the people and events involved.
8. Blind-spot Bias: Failing to recognize one's own biases
Blind-spot bias, while last in our list, should always be top of mind. Investigators must continually assess possible biases that may impact their thinking unconsciously, and make conscious attempts to address them. People tend to attribute bias unevenly so that when people reach different conclusions, they often label one another as biased while viewing themselves as accurate and unbiased.
Great investigators will understand and reflect on these cognitive biases continually during an investigation. Mental noise, wishful thinking – these things happen to the best of us. So remember always: Check your bias.
Backfire Effect, Base Rate Fallacy, Clustering Illusion, Conjunction Fallacy & False Dilemma
In the fourth article of the Cognitive Biases and Fallacies, How Are They Exploited series, you will learn about examples of cognitive biases and fallacies, and how they are used against you by the media, politicians, social engineers and more.
For more articles on the topic, check out my cognitive biases and fallacies category.
Cognitive biases are systematic patterns of deviation of the norm, while a fallacy is a mistaken belief. The inputs our senses feed us become distorted via biases and fallacies, which is why it is essential to learn them, study them and identify them, so we can learn to make better decisions in the future.
In this article the following Cognitive Biases and Fallacies will be discussed:
- Backfire Effect.
- Base Rate Fallacy.
- Clustering Illusion.
- Conjunction Fallacy.
- False Dilemma.
Business Clustering Examples
Previous instalments of the Cognitive Biases & Fallacies, How Are They Exploited series: article 1, article 2 & article 3.
Examples Of Clustering
Cognitive Biases & Fallacies #16: Backfire Effect
In the face of contradictory evidence, established beliefs do not change but actuallyget stronger.
Backfire Effect Definition. Source: RationalwikiPeople display this bias when they gatheror remember information selectively, or when they interpret it in a biased way.The effect is stronger for emotionally charged issues and for deeply entrenchedbeliefs.
How is theBackfire Effectexploited
This can be exploited by feigning interest in removing someone from a belief position you have put them in. Losing the argument will have the added effect of them being able to remember winning.
Corporations know that they are doing something that is harmful but nonetheless promote denialism, even publicly admitting their product is harmful while simultaneously covertly funding astroturf groups that promote the denialist message.
Small pause: if you're enjoying this essay, make sure to join the Newsletter to never miss any!
Cognitive Biases & Fallacies #17: Base Rate Fallacy
It is both a logical fallacy and a cognitive bias.
Base rate fallacy, also known as base rate neglect or base rate bias, is an error in thinking. If presented with related base rate information and specific information, the mind tends to ignore the former and focus on the latter.
Base Rate Definition. Source: Wikipedia.Base Rate FallacyExamples
'One death is a tragedy; one million is a statistic.' -Joseph Stalin.
How the Base Rate Fallacy exploited
The media exploits it every day, finding a story that appeals to a demographic and showing it non-stop.
Redeem$20 free chip for $100 deposited last week. Wagering is 40 times the bonus amount and max cash out is $300. Redeem $35 free chip for $150 deposited last week. Wagering is 40 times the bonus amount and max cash out is $300. Redeem $55 free chip for $250 deposited last week. Wagering is 35 times the bonus amount and max cash out is $550. The $75 free chip is a no deposit bonus code. However, you can also receive an array of deposit bonus free chips as well. They include: Vegas Rush Hour Bonus: A 100% No Play No Max Bonus. Use code VEGASRUSH100 Vegas City Special: 300% Match bonus + Match deposit Free Chip. Use code VEGASCITY300 Vegas Wonder: 350% on $50 or more deposit. TaKe Free Bonus to play $101 to $500, Crazy Luck Casino, Exclusive free chip codes on September 18, 2020. $75 FREE CHIP – Raging Bull 2020 - Casino Bonuses Claim up to $7,777 in Free Welcome Casino Bonuses + add 300 Free Spins on Top! €2020 No deposit bonus code.$300 FREE Chip. 300 free chip. Grande Vegas casino makes every moment Extra Grande. 2020 was a crazy year for everyone. That's why casino wants to end 2020 for all 2020 depositors with $300 FREE CHIP. How to get your $300 Extra for 2020: Everybody who made a deposit between January 1st and December 31st can use coupon code 2020-THX and redeem $300 totally for free.
There is always and agenda behind whenever one tragedy, one death or one instance is made out to seem more important than another of statistically equal relevance. People trying to use emotion to conjure a reaction always have an agenda.
Cognitive Biases & Fallacies #18: Clustering Illusion
The clustering illusion is the tendency to erroneously consider the inevitable 'streaks' or 'clusters' arising in small samples from random distributions to be statistically significant.
Clustering Illusion Definition. Source: Wikipedia.It is caused by the human tendency to under-predict the amount of variability likely to appear in a small sample of random or semi-random data.
Clustering Illusion Examples
Seeing patterns in stock market fluctuations.
Cognitive Biases & Fallacies #19: Conjunction Fallacy
Also known as the Linda problem, it is a formal fallacy that occurs when it is assumed that specific conditions are more probable than a single general one.
Conjunction Fallacy Definition. Source: WikipediaThe most often-cited example is the next.
Conjunction FallacyExamples
Linda is 31 years old, single, outspoken,and very bright. She majored in philosophy. As a student, she was deeply concernedwith issues of discrimination and social justice, and also participated inantinuclear demonstrations.
Which is more probable?
- Linda is a bank teller.
- Linda is a bank teller and is active in the feminist movement.
The majority of those asked chose option2. However the probability of two events occurring together (in'conjunction') is always less than or equal to the probability ofeither one occurring alone.
How is the Conjunction Fallacyexploited
Used as an example of how to convince someone of something without lying, telling them accurate information in advance about the questions target would think of as helpful, though it will influence their choice.
By perpetuating false information. Politicians do this all the time, by painting their opponents with a brush to undermine their side of the discussion.
Cognitive Biases & Fallacies #20: False Dilemma
Informal fallacy that involves a situation in which only limited alternatives are considered, when in fact there is at least one additional option.
False Dilemma Definition. Source: Wikipedia.False Dilemma Examples
Two alternative states are presented as the only possibilities, when in fact more possibilities exist.
'X spoke out against capitalism, therefore he/she must be a communist' (he/she may be neither capitalist nor communist).
How is theFalse Dilemma exploited
Politicians, while rallying support for their plans, will tell the people that they are either with him or against him.
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