The Good, The Bad, and The Creepy: Why Data Scientists Need to Understand Ethics

Few data science programs and even fewer analytics programs require courses in ethics. This has downstream consequences for businesses and for society. Although universities do a (fairly) good job at teaching students what they CAN do with data, they are less adept at teaching students what they SHOULD (or SHOULD NOT) do with data. This talk goes through three case studies that explain the unintended consequences of data science in application without ethical guide rails. The presenter discusses the obligations that universities have related to teaching ethical data science.

Presenter:
Jennifer Priestley
Associate Dean, Kennesaw State University

Presentation Outline
00:00 – Introduction
04:00 – How we got to this Point – Data Science: (United States)
06:12 – How the Data Ecosystem is Evolving…
08:46 – Why Data Scientists Need to Understand Ethics – Issue 1: A few people can cause a great deal of harm
12:57 – Why Data Scientists Need to Understand Ethics – Issue 2: Lack of consent
22:10 – Why Data Scientists Need to Understand Ethics – Issue 3: Will the algorithm do what I think it does?
36:35 – Maslow’s Hierarchy of Data Science
39:52 – Where do we go next… what is the role of academia?
41:26 – Questions and Answers

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