Philosophy of Data Science | S01 E04 | Values and Subjectivity in Data Science

Philosophy of Data Science Series
Session 1: Scientific Reasoning for Practical Data Science
Episode 4: Values and Subjectivity in Data Science
 
The Value-Free Ideal is a central tenant of objective science. But how do values, value judgements, and subjectivity leak into the practice of data science and statistics. To what extent is it desirable for science to be informed by values? Kevin Zollman (Carnegie Mellon University) covers the range of key ideas, from Heather E. Douglas to W.E.B. du Bois.
 
Watch it on...
YouTube: https://youtu.be/9USkWtX-ydc
Podbean: https://podofasclepius.podbean.com/e/philosophy-of-data-science-s01-e04-values-and-subjectivity-in-data-science/
 
You can join our mail list at: https://www.podofasclepius.com/mail-list
 
We're always happy to hear your feedback and ideas - just post it in the YouTube comment section to start a conversation.
 
Thank you for your time and support of the series!
 
0:00 Intro
0:03 Welcome Kevin Zollman (Carnegie Mellon University)!
1:44 Is Science Value-Free?
6:08 How might values affect science?
9:00 Choice of Research Problem
10:45 Loss Functions
18:34 Choice of Variables
24:10 Choice of Statistical Model
29:30 Minimizing the Values in Science (W.E.B. du Bois)
35:20 Philosopher in Science
41:20 Statements on Generalizability
47:45 Clarifying Subjective Choices
52:45 Conflicts between Scientific Disciplines
61:18 Scientific Value Judgments & Self Correcting Science
67:50 Choice in Metrics and Research Focus
70:30 Concluding Ideas