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