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Science vs Pseudoscience | Neil Manson | Philosophy of Data Science
#datascience #science #pseudoscience #criticalthinking #reasoning
We each like to think of ourself as scientific. I'm yet to meet someone who would embrace being called "pseudoscientific". But what makes the difference? In this episode, Neil Manson talks about the fallout from Thomas Kuhn's 1962 book "The Structure of Scientific Revolutions" and how this created a playbook for many modern critiques/attacks on scientific activity.
We have a new series that centers on the discussion of science vs. pseudoscience. Guests of different backgrounds share their insights on what really constitutes science and the highly-contested pseudoscience. The implications for data scientists and statisticians is very interesting, since many of the examples around this debate involved the conflicts between hypothesis-driven science vs data-driven science.
0:00 - Intro
0:43 - Science vs Pseudo/Bad/No Science
05:52 - Demarcation problem of science
12:07 - Incentives in science
13:00 - Glen forgets the word for "book"
13:40 - Luminiferous aether & lunch tables
18:19 - Keeping “good science” out of the science category
22:49 - Aiming to define science in relation to Kuhn’s theory
29:06 - Kuhn’s theory in action in various scenarios
32:53 - Logical fallacies in the world of science
46:17 - Intelligent design theory as science
51:14 - Distinction of different sciences
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By Glen Wright Colopy
5
77 ratings
#datascience #science #pseudoscience #criticalthinking #reasoning
We each like to think of ourself as scientific. I'm yet to meet someone who would embrace being called "pseudoscientific". But what makes the difference? In this episode, Neil Manson talks about the fallout from Thomas Kuhn's 1962 book "The Structure of Scientific Revolutions" and how this created a playbook for many modern critiques/attacks on scientific activity.
We have a new series that centers on the discussion of science vs. pseudoscience. Guests of different backgrounds share their insights on what really constitutes science and the highly-contested pseudoscience. The implications for data scientists and statisticians is very interesting, since many of the examples around this debate involved the conflicts between hypothesis-driven science vs data-driven science.
0:00 - Intro
0:43 - Science vs Pseudo/Bad/No Science
05:52 - Demarcation problem of science
12:07 - Incentives in science
13:00 - Glen forgets the word for "book"
13:40 - Luminiferous aether & lunch tables
18:19 - Keeping “good science” out of the science category
22:49 - Aiming to define science in relation to Kuhn’s theory
29:06 - Kuhn’s theory in action in various scenarios
32:53 - Logical fallacies in the world of science
46:17 - Intelligent design theory as science
51:14 - Distinction of different sciences