# data[].attributes.body
“Humans are pattern-seeking animals and we are adept at finding patterns whether they exist or not” (adapted from Michael Shermer). Discuss knowledge questions raised by this idea in two areas of knowledge.
TOK Essay Title 6
Avatar of Laura Thomson
Laura Thomson
 +  10
●
2yr

# data[].attributes.body
two areas of knowledge.
TOK Essay Title 6
Avatar of Laura Thomson
Laura Thomson
 + 1
●
1mo

# data[].attributes.attachment_link.readable_text
Noun. The tendency to find meaningful patterns in meaningless noise

Why do people see faces in nature, interpret window stains as human figures, hear voices in random sounds generated by electronic devices or find conspiracies in the daily news? A proximate cause is the priming effect, in which our brain and senses are prepared to interpret stimuli according to an expected model. UFOlogists see a face on Mars. Religionists see the Virgin Mary on the side of a building. Paranormalists hear dead people speaking to them through a radio receiver. Conspiracy theorists think 9/11 was an inside job by the Bush administration. Is there a deeper ultimate cause for why people believe such weird things? There is. I call it "patternicity," or the tendency to find meaningful patterns in meaningless noise.

Traditionally, scientists have treated patternicity as an error in cognition. A type I error, or a false positive, is believing something is real when it is not (finding a nonexistent pattern). A type II error, or a false negative, is not believing something is real when it is (not recognizing a real pattern - call it "apatternicity"). In my 2000 book How We Believe, I argue that our brains are belief engines: evolved patternrecognition machines that connect the dots and create meaning out of the patterns that we think we see in nature. Sometimes A really is connected to B; sometimes it is not. When it is, we have learned something valuable about the environment from which we can make predictions that aid in survival and reproduction. We are the descendants of those most successful at finding patterns. This process is called association learning and it is fundamental to all animal behavior, from the humble worm C. elegans to H. sapiens.

Unfortunately, we did not evolve a Baloney Detection Network in the brain to distinguish between true and false patterns. We have no error-detection governor to modulate the pattern-recognition engine. (Thus, the need for science with its self-correcting mechanisms of replication and peer review.) But such erroneous cognition is not likely to remove us from the gene pool and would therefore not have been selected against by evolution.

In a September 2008 paper in the Proceedings of the Royal Society B, "The Evolution of Superstitious and Superstition-like Behaviour," Harvard University biologist Kevin R. Foster and University of Helsinki biologist Hanna Kokko test my theory through evolutionary modeling and demonstrate that whenever the cost of believing a false pattern is real is less than the cost of not believing a real pattern, natural selection will favor patternicity. They begin with the formula pb > c, where a belief may be held when the cost ( c) of doing so is less than the probability ( p) of the benefit ( b). For example, believing that the rustle in the grass is a dangerous predator when it is only the wind doesn't cost much, but believing that a dangerous predator is the wind may cost an animal its life.

The problem is that we are very poor at estimating such probabilities, so the cost of believing that the rustle in the grass is a dangerous predator when it is just the wind is relatively low compared with the opposite. Thus, there would have been a beneficial selection for believing that most patterns are real. Through a series of complex formulas that include additional stimuli (wind in the trees) and prior events (past experience with predators and wind) the authors conclude that "the inability of individuals - human or otherwise - to assign causal probabilities to all sets of events that occur around them will often force them to lump causal associations with non-causal ones. From here, the evolutionary rationale for superstition is clear: natural selection will favour strategies that make many incorrect causal associations in order to establish those that are essential for survival and reproduction."

In support of a genetic selection model, Foster and Kokko note that "predators only avoid nonpoisonous snakes that mimic a poisonous species in areas where the poisonous species is common," and that even such simple organisms as " Escherichia coli cells will swim towards physiologically inert methylated aspartate presumably owing to an adaptation to favour true aspartate."

Such patternicities, then, mean that people believe weird things because of our evolved need to believe nonweird things.

# data[].attributes.attachment_link.description
Dr. Michael Shermer is the Publisher of Skeptic magazine, a monthly columnist for Scientific American, and a Presidential Fellow at Chapman University where he teaches Skepticism 101. He is the author of Why People Believe Weird Things, Why Darwin Matters, The Science of Good and Evil, and The Moral Arc.

# data[].attributes.attachment_link.readable_text
(by Eileen Dombrowski, from OUP blog) Swift and powerful, the athletes burst across the finish line of the women's 800 metre in Rio. The Olympics gave the world another moment of glorious human achievement as 25-year-old Caster Semenya took the gold medal for South Africa. In the background of her performance, however, controversy swirled around claims that Semenya had an unfair advantage in a women's competition - that she didn't fit into the category "woman".

The issue contentious in the Rio competition is one we confront constantly as we construct our knowledge: how to classify things and whethe r we can do so in a way that delineates our world neatly into categories. Classifying is basic to observing, and to the naming that enables us to share our knowledge. But what a complex world it is, often eluding the systematizing we bring to it!

Even categories on which everyone seems to agree can grow more complex with further knowledge. Did you see that scientists discovered only a few days ago that there are actually four giraffe species, not just one? Have a look at this short video from Science Daily: Scientists Just Realized There's More Than One Kind Of Giraffe

Even the simplest and most familiar categories of things can erupt into debate on close examination. My favourite current examples is vegetables - a category that is not biological but culinary, with plenty of variability in what it includes. Even the law has become embroiled in knowledge claims over categorization of vegetables: "Do vegetables really exist?"

When even giraffes and vegetables can challenge our classification systems, should we be surprised when our categorization of human beings founders on application to the real world?

And so - back to Caster Semenya, who has submitted to extensive invasion of her sexual identity in order to be permitted to perform in elite sports. Why is her situation relevant to Theory of Knowledge? What are the knowledge questions it raises?

1.Classification: To what extent do the categories with which we describe the world reflect the world as it is, and to what extent concepts we have constructed ourselves?

Among the many questions we could raise about classification, this one does at least invite some evaluation and comparison - for instance, categorization based on observation of natural phenomena such as rocks, bacteria, or stars, as opposed to categorization based on conceptual groupings such as historical periods and genres of literature. It's a useful question, in this case, for considering the extent to which our biological classification of sexes is supplanted by the social categorization of gender.

Certainly, the sexual identity of Caster Semenya has been at the centre of controversy. "Could This Women's World Champ Be a Man?" questioned an article in Time in 2009 when Caster Semenya won a track and field championship in Berlin. Some of her competitors expressed strong views on her category. Italian Elisa Piccione, who came in 6 th, declared, "These kinds of people should not run with us. For me, she's not a woman. She's a man." The International Association of Athetics Federations (IAAF) confirmed that Semenya had agreed to testing to prove herself a woman, and thereafter cleared her to continue to compete as a woman.

But how does a person prove that she is a woman? In sports, sex-testing has centred on chromosome tests, testosterone levels, and medical examination of the reproductive system - all in order to draw the line between the sexes. Cheating is not the issue: Semenya's elevated level of testosterone is natural, not a matter of taking drugs. Nor is misrepresentation an issue here: Semenya has been raised as a woman and identifies as a woman. As she won gold in Rio, she was following all the rules! The contentious issue is neither cheating nor lying but the line itself.

The experts of the International Association of Athletics Federations (IAAF) have acknowledged, "We must find ways to take into account that sex is not neatly divided into only two categories in the real world." (Relevant article: "Science will never settle the question of sex and gender in sport", The Guardian)

As sporting organizations face the complexities of the real world, I can't help adding that well into the twentieth century the category "athlete" did not include women at all! (Relevant and fascinating article: "The Humiliating Practice of Sex-Testing Female Athletes", New York Times)

2. Ethics: What is meant by the ethical principle of "fairness" or "justice", and in what ways might we apply it to the world?

And why is it so important to many in elite sporting competitions to "draw the line" - and then to "hold the line"? The major argument centres on fairness, on a principle of justice. This principle could generate some good discussion in a TOK class - regarding where it comes from and how "fairness" is defined.

The testosterone level of some female athletes may be an advantage to them, though apparently not consistently or extensively. So is "advantage" unfair? Does fairness demand equality in competitors - or at least equality in opportunity? Several difficulties arise.

If we are making an ethical argument based on removing "advantage", for instance, don't we have to acknowledge the many forms of "advantage" that figure in Olympic competitions? What about advantages brought by wealth, such as access to training and facilities? As Sisonke Msimang comments ( "Caster Semenya is the one at a disadvantage"):

In developing countries all aspects of sports are under-resourced. School programmes barely exist. Even elite athletes struggle to find a track to practice on or a coach to work with - never mind the sophisticated nutritional, psychological and biomechanical performance enhancement available to those in the developed world. Forget marginal gains, these are massive ones.

The idea that testosterone levels could constitute an unfair advantage in this climate is laughable.

What about other physical "advantages", such as features of body structure? As Olga Khazan comments in a relevant article ( "Why Hyper-Masculine Women Are Scary, but Fish-Like Men Aren't", The Atlantic)

Sports must have rules, in other words, but the Olympics are already filled with social, cultural, and biological rule-breakers. The fact that people are alarmed about the masculinity of athletes like Semenya, but not the myriad other ways Olympians deviate from the norm, suggests that our anxieties about her might be rooted in something other than a love of fairness.

In trying to frame the case of Caster Semenya or any other "masculine" woman athlete with ethical argument, we again run right into the messiness and complexities of the world, in which certain "advantages" provoke protest, while others are built right into the system.

Again and again I am drawn back to comment on the topic of classification - so basic to knowledge, so significant in how we live together as human beings. If we achieve anything at all with our TOK course, I hope at least that we encourage our students to combine two central IB characteristics: critical thinking to question the categories into which the knowledge they have received has already been slotted, and openness to consider alternative ways that recognize (or even embrace!) the complexities and nuances of the real world. Caster Semenya is only one example among so many human beings who elude tidy categories. But the controversy to which others have subjected her does not nullify the category that brought her so much media attention: she is one of the finest athletes in the world.

# data[].attributes.attachment_link.title
Is that woman really a man? Tidy categories, messy world

# data[].attributes.attachment_link.description
https://www.youtube.com/watch?v=d6YT9N0AIsM (by Eileen Dombrowski, from OUP blog) Swift and powerful, the athletes burst across the finish line of the women's 800 metre in Rio. The Olympics gave the world another moment of glorious human achievement as 25-year-old Caster Semenya took the gold medal for South Africa.

# data[].attributes.attachment_link.readable_text
Noun. The tendency to find meaningful patterns in meaningless noise

Why do people see faces in nature, interpret window stains as human figures, hear voices in random sounds generated by electronic devices or find conspiracies in the daily news? A proximate cause is the priming effect, in which our brain and senses are prepared to interpret stimuli according to an expected model. UFOlogists see a face on Mars. Religionists see the Virgin Mary on the side of a building. Paranormalists hear dead people speaking to them through a radio receiver. Conspiracy theorists think 9/11 was an inside job by the Bush administration. Is there a deeper ultimate cause for why people believe such weird things? There is. I call it "patternicity," or the tendency to find meaningful patterns in meaningless noise.

Traditionally, scientists have treated patternicity as an error in cognition. A type I error, or a false positive, is believing something is real when it is not (finding a nonexistent pattern). A type II error, or a false negative, is not believing something is real when it is (not recognizing a real pattern - call it "apatternicity"). In my 2000 book How We Believe, I argue that our brains are belief engines: evolved patternrecognition machines that connect the dots and create meaning out of the patterns that we think we see in nature. Sometimes A really is connected to B; sometimes it is not. When it is, we have learned something valuable about the environment from which we can make predictions that aid in survival and reproduction. We are the descendants of those most successful at finding patterns. This process is called association learning and it is fundamental to all animal behavior, from the humble worm C. elegans to H. sapiens.

Unfortunately, we did not evolve a Baloney Detection Network in the brain to distinguish between true and false patterns. We have no error-detection governor to modulate the pattern-recognition engine. (Thus, the need for science with its self-correcting mechanisms of replication and peer review.) But such erroneous cognition is not likely to remove us from the gene pool and would therefore not have been selected against by evolution.

In a September 2008 paper in the Proceedings of the Royal Society B, "The Evolution of Superstitious and Superstition-like Behaviour," Harvard University biologist Kevin R. Foster and University of Helsinki biologist Hanna Kokko test my theory through evolutionary modeling and demonstrate that whenever the cost of believing a false pattern is real is less than the cost of not believing a real pattern, natural selection will favor patternicity. They begin with the formula pb > c, where a belief may be held when the cost ( c) of doing so is less than the probability ( p) of the benefit ( b). For example, believing that the rustle in the grass is a dangerous predator when it is only the wind doesn't cost much, but believing that a dangerous predator is the wind may cost an animal its life.

The problem is that we are very poor at estimating such probabilities, so the cost of believing that the rustle in the grass is a dangerous predator when it is just the wind is relatively low compared with the opposite. Thus, there would have been a beneficial selection for believing that most patterns are real. Through a series of complex formulas that include additional stimuli (wind in the trees) and prior events (past experience with predators and wind) the authors conclude that "the inability of individuals - human or otherwise - to assign causal probabilities to all sets of events that occur around them will often force them to lump causal associations with non-causal ones. From here, the evolutionary rationale for superstition is clear: natural selection will favour strategies that make many incorrect causal associations in order to establish those that are essential for survival and reproduction."

In support of a genetic selection model, Foster and Kokko note that "predators only avoid nonpoisonous snakes that mimic a poisonous species in areas where the poisonous species is common," and that even such simple organisms as " Escherichia coli cells will swim towards physiologically inert methylated aspartate presumably owing to an adaptation to favour true aspartate."

Such patternicities, then, mean that people believe weird things because of our evolved need to believe nonweird things.

# data[].attributes.attachment_link.description
Dr. Michael Shermer is the Publisher of Skeptic magazine, a monthly columnist for Scientific American, and a Presidential Fellow at Chapman University where he teaches Skepticism 101. He is the author of Why People Believe Weird Things, Why Darwin Matters, The Science of Good and Evil, and The Moral Arc.

# data[].attributes.attachment_link.readable_text
Noun. The tendency to find meaningful patterns in meaningless noise

Why do people see faces in nature, interpret window stains as human figures, hear voices in random sounds generated by electronic devices or find conspiracies in the daily news? A proximate cause is the priming effect, in which our brain and senses are prepared to interpret stimuli according to an expected model. UFOlogists see a face on Mars. Religionists see the Virgin Mary on the side of a building. Paranormalists hear dead people speaking to them through a radio receiver. Conspiracy theorists think 9/11 was an inside job by the Bush administration. Is there a deeper ultimate cause for why people believe such weird things? There is. I call it "patternicity," or the tendency to find meaningful patterns in meaningless noise.

Traditionally, scientists have treated patternicity as an error in cognition. A type I error, or a false positive, is believing something is real when it is not (finding a nonexistent pattern). A type II error, or a false negative, is not believing something is real when it is (not recognizing a real pattern - call it "apatternicity"). In my 2000 book How We Believe, I argue that our brains are belief engines: evolved patternrecognition machines that connect the dots and create meaning out of the patterns that we think we see in nature. Sometimes A really is connected to B; sometimes it is not. When it is, we have learned something valuable about the environment from which we can make predictions that aid in survival and reproduction. We are the descendants of those most successful at finding patterns. This process is called association learning and it is fundamental to all animal behavior, from the humble worm C. elegans to H. sapiens.

Unfortunately, we did not evolve a Baloney Detection Network in the brain to distinguish between true and false patterns. We have no error-detection governor to modulate the pattern-recognition engine. (Thus, the need for science with its self-correcting mechanisms of replication and peer review.) But such erroneous cognition is not likely to remove us from the gene pool and would therefore not have been selected against by evolution.

In a September 2008 paper in the Proceedings of the Royal Society B, "The Evolution of Superstitious and Superstition-like Behaviour," Harvard University biologist Kevin R. Foster and University of Helsinki biologist Hanna Kokko test my theory through evolutionary modeling and demonstrate that whenever the cost of believing a false pattern is real is less than the cost of not believing a real pattern, natural selection will favor patternicity. They begin with the formula pb > c, where a belief may be held when the cost ( c) of doing so is less than the probability ( p) of the benefit ( b). For example, believing that the rustle in the grass is a dangerous predator when it is only the wind doesn't cost much, but believing that a dangerous predator is the wind may cost an animal its life.

The problem is that we are very poor at estimating such probabilities, so the cost of believing that the rustle in the grass is a dangerous predator when it is just the wind is relatively low compared with the opposite. Thus, there would have been a beneficial selection for believing that most patterns are real. Through a series of complex formulas that include additional stimuli (wind in the trees) and prior events (past experience with predators and wind) the authors conclude that "the inability of individuals - human or otherwise - to assign causal probabilities to all sets of events that occur around them will often force them to lump causal associations with non-causal ones. From here, the evolutionary rationale for superstition is clear: natural selection will favour strategies that make many incorrect causal associations in order to establish those that are essential for survival and reproduction."

In support of a genetic selection model, Foster and Kokko note that "predators only avoid nonpoisonous snakes that mimic a poisonous species in areas where the poisonous species is common," and that even such simple organisms as " Escherichia coli cells will swim towards physiologically inert methylated aspartate presumably owing to an adaptation to favour true aspartate."

Such patternicities, then, mean that people believe weird things because of our evolved need to believe nonweird things.

# data[].attributes.attachment_link.description
Dr. Michael Shermer is the Publisher of Skeptic magazine, a monthly columnist for Scientific American, and a Presidential Fellow at Chapman University where he teaches Skepticism 101. He is the author of Why People Believe Weird Things, Why Darwin Matters, The Science of Good and Evil, and The Moral Arc.

# data[].attributes.body
Our minds form patterns based on similar memories
Do patterns contribute to the origin of stereotypes?

# data[].attributes.headline
Do not forget to properly conclude your TOK essay !!! Many students don't  

# data[].attributes.subject
Do not forget to properly conclude your TOK essay !!! Many students don't  

# data[].attributes.body
Patterns
adept (science backing)

# data[].attributes.body
Early humans, learning what to eat and what not to based off of how it affects people

Pavlov's dogs

B. F. Skinner's behavorial conditioning

# data[].attributes.headline
THE BAADER-MEINHOF PHENOMENON and Synchronicity

# data[].attributes.subject
THE BAADER-MEINHOF PHENOMENON and Synchronicity

# data[].attributes.body
Coincidentally hearing the mention of a word or knowledge repeatedly after learning it when it supposedly wasn't there before

Synchronicity is highly meaningful coincidence, such as a person calling you just as you were thinking of them (speak of the devil, and such)

# data[].attributes.body
https://activatingtok.net/2016/09/15/is-that-woman-really-a-man-tidy-categories-messy-world/

# data[].attributes.body
Finding a pattern to fit a presumption by cherry-picking clusters of information

# data[].attributes.body
If a pattern is not there but gains enough attention, it can gain traction

# data[].attributes.body
Misinterpreting correlation for causation

# data[].attributes.body
Holding on to old beliefs by coming up with an explanation for why something isnt true in that one case

# data[].attributes.body
http://www.michaelshermer.com/2008/12/patternicity/
https://www.ted.com/talks/michael_shermer_the_pattern_behind_self_deception?language=en

# data[].attributes.body
Thinking there is a pattern, and only selecting events/facts/observations that prove the pattern

# data[].attributes.headline
Weather as an example of pattern recognition

# data[].attributes.subject
Weather as an example of pattern recognition

# data[].attributes.body
weatherman finds pattern, which then leads to predictions about future weather, impacting agriculture and population fluxes of animals

# data[].attributes.body
Are based mostly on pattern recognition - is this representative of true/extensive knowledge

# data[].attributes.body
Humans finding patterns when there are none can lead to superstition or false claims regarding society, life or existence

# data[].attributes.body
Models created by us to explain patterns are never fully representative of the real-life structure/process/event and can always be updated

# data[].attributes.body
... don't get ulcers like humans, because they do not associate stress with memory as we do

# data[].attributes.body
- looking for easy, quick-fire ways to achieve outcomes could reduce quality of work

# data[].attributes.body
The human brain's tendency to find human faces in our surroundings.

# data[].attributes.body
The 'creative cycle/ design cycle' taught in schools. based on 'observed' pattern of creative practice. Students are asked to show evidence of the cycle. Does the creative cycle really exist? What of those students who don't think that way?

Was it developed simply to enable assessment?

# data[].attributes.body
Diagnosis of illness inc. mental illness: Human Sciences
Implications for diagnosis and mis diagnosis. 'Invention' of diseases such as ADHD based on percieved patterns.

# data[].attributes.body
Mathematics.

Natural Sciences.

Human Sciences.

History.

The Arts.

Ethics.

Religious Knowledge Systems.

Indigenous Knowledge Systems.