CONCLUSION Bayesian Life Flashcards

1
Q

What should you do if you think you’ve found a theory of everything?

A

Diagnose yourself with mania and check yourself into a psychiatric hospital.

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2
Q

What percentage of emails sent in the world are potentially spam?

A

Between 35 and 70 percent.

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3
Q

What is the prior probability in the context of a spam filter?

A

The prior probability is the assumption about the percentage of spam emails.

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4
Q

How does a spam filter update its probability assessment?

A

It updates using new information about the content of emails.

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5
Q

What is the phrase that a spam filter might associate with higher spam probability?

A

Penis extension.

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6
Q

What did Fred Hoyle compare the chances of evolution successfully producing life to?

A

A whirlwind passing through a junkyard and creating a Boeing 747.

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7
Q

Is evolution a random process?

A

No, evolution is not random; it is guided by natural selection.

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8
Q

What does Price’s equation describe?

A

How the frequency of a characteristic in a population changes based on relative fitness.

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9
Q

What happens to copies of a gene that enhance an organism’s survival?

A

They tend to make more copies and survive to the next generation.

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10
Q

What is a genome seen as in the context of Bayesian reasoning?

A

A prediction about the world.

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11
Q

What does the frequency of a gene in a population represent?

A

A prior probability.

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12
Q

What influences the updating of a gene’s likelihood in evolution?

A

The survival and reproduction of organisms carrying that gene.

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13
Q

True or False: Confirmation bias is always irrational.

A

False.

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14
Q

What influences the trustworthiness of information from different political parties?

A

Prior probabilities associated with those parties.

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15
Q

How do peer reviewers judge scientific papers differently based on the authors?

A

They are more likely to accept papers from Nobel-winning authors than novices.

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16
Q

Who said, ‘All models are wrong, but some are useful’?

A

George Box.

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17
Q

What do our mental models of the world contain?

A

Both quotidian and abstract concepts.

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18
Q

What is prediction error?

A

The discrepancy between expected and actual outcomes.

19
Q

How does the brain process predictions?

A

By making predictions and updating them based on new information.

20
Q

What is a ‘flow state’?

A

A state where predictions are high-precision and come true consistently.

21
Q

Why do older people become more set in their ways?

A

They have a richer, more precise model of the world and require more information to shift their beliefs.

22
Q

What does the Bayesian framework suggest about consciousness?

A

It provides a perspective on how we experience the world as predictions.

23
Q

Fill in the blank: Evolution works to minimize _______.

A

Prediction error.

24
Q

What does the Bayesian process describe in decision-making?

A

The optimal way to integrate new information with prior best guesses.

25
Q

What is the Bayesian framework in relation to consciousness?

A

It allows us to think of our experience of the world as our predictions of the world, our Bayesian prior.

26
Q

How does science relate to the Bayesian model of perception?

A

Science is about making predictions and testing them, while the Bayesian model is explicitly subjective.

27
Q

What is a probability estimate in the Bayesian context?

A

It is my best guess of the world, given the information I have.

28
Q

What is the significance of prior probabilities in Bayesian reasoning?

A

They are subjective estimates that help us assess how likely a hypothesis is true based on new data.

29
Q

What does the phrase ‘the map is not the territory’ imply in relation to Bayesian models?

A

It implies that our mental models of the world may be incorrect, but the real world exists.

30
Q

What do philosophers of science struggle with regarding knowledge?

A

They deal with epistemology and the uncertainty of knowing anything for certain.

31
Q

What is the process of updating beliefs in Bayesian terms?

A

As new evidence comes in, we adjust our confidence in a hypothesis without reaching total certainty.

32
Q

How does Bayesian reasoning help in evaluating skill versus luck?

A

It allows us to upgrade our confidence in someone’s skill based on their successful outcomes.

33
Q

What is a practical application of Bayesian thinking in everyday life?

A

Thinking in terms of confidence levels rather than binary true/false beliefs.

34
Q

Fill in the blank: Bayesianism helps us think in terms of _______ rather than right and wrong.

A

confidence levels

35
Q

How does Bayesianism help in discussions about terms like ‘cancel culture’?

A

It allows for focusing on predictions about future outcomes rather than arguing over definitions.

36
Q

What does the author suggest about arguments in the real world?

A

Many arguments are about labeling phenomena rather than making substantial predictions.

37
Q

How do humans function as ‘prediction machines’?

A

We constantly make predictions at various levels to navigate the world.

38
Q

Who is specifically acknowledged for their help in understanding Bayes’ theorem?

A

Kevin McConway, emeritus professor of statistics at the Open University.

39
Q

What is the role of subjective estimates in Bayesian science?

A

They help in determining how confident we are in hypotheses based on prior knowledge.

40
Q

True or False: Bayesian models of perception claim that all models are equally valid.

41
Q

What happens to our probability distribution when we see counterexamples?

A

It becomes less likely that our initial hypothesis is true, prompting a reevaluation.

42
Q

Fill in the blank: The Bayesian model emphasizes _______ rather than absolute certainty.

A

uncertainty

43
Q

What is the significance of the phrase ‘making predictions and updating them’ in Bayesian reasoning?

A

It highlights the iterative process of refining our understanding based on new evidence.