0/ Essential philosophy for #DataScience, a thread of 32 questions.
Grab a friend (virtually) and tackle these 32 essential questions (all with more than one reasonable answer) that every serious #data professional should answer for themselves.
4/ What is the difference between knowledge, truth, assumptions, opinions, and beliefs?
5/ What does it take to "justify" a belief? (Please don't embarrass the class by blurting out, "Make a scatterplot!")
6/ Does it make sense to talk about a shared reality?
7/ Is knowledge personal or social?
8/ Is persuasion philosophically justified?
9/ Is there something special about mathematical reasoning?
10/ Can pure logic create knowledge?
11/ What is a fact?
12/ Can sensory experience produce knowledge?
13/ Does someone else's sensory experience give you less knowledge than your own?
14/ What makes a source of evidence trustworthy?
15/ If logic and data point in opposite directions, which way do you go?
16/ Does every quantity you've measured really exist? ("Rate your happiness on a scale of 1 to 7!")
17/ Do all measurements quantify anything real?
18/ What makes categories valid?
19/ Does evidence apply across nonidentical semantically-related concepts? (When, if ever, is it valid to apply evidence about something called user happiness to make inferences about something called user satisfaction?)
20/ Is there a difference between knowing a theory is true and acting as though a theory were true?
21/ Is it possible to behave as though a theory were true without believing it?
22/ Can you make reliable predictions about something without understanding how it works?
23/ What makes science "scientific" or special?
24/ Is there a reason to trust scientists more than other people?
25/ Are scientists who apply statistical hypothesis testing adhering to the core principles of the scientific method, such as falsifiability?
26/ Can analytics produce facts?
27/ Are analytical "insights" facts? Are statistical conclusions facts?
28/ Is it ethical to work on a project that may harm your fellow human beings?
29/ Is it ethical to use your data skills to legitimize someone's actions in hindsight?
30/ Is it ethical to use statistics for persuasion?
31/ Is it ethical to share your analysis with people who will draw incorrect conclusions from it?
32/ Who is morally responsible for how your conclusions are used?
Perhaps a better use of question 17 is: 17/ What makes a measurement valid?
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2/10 It's not helpful to form an uninformed opinion & then look for media that confirms your views. You'll find it, maybe you'll feel better, but you may as well skip it - it's a waste of time. You already know you'll just confirm whatever you wanted to believe. Instead, do this:
3/10 Think carefully about your ethics/values/goals (for world, community, family, self). (This post isn't about telling you how much of a nice person to be, only how to make decisions within your own moral framework... but I hope you'll choose to be nice.)