5. Data Ethics

Label	KSAC Description		Bloom's Taxonomy Level
a	Identify how global legal, policy and/or ethical constraints might impact data analyses	knowledge	2
b	Identify the established ethical and legal issues in data management facing organizations	knowledge	2
c	Explain how ethical, compliance, and legal issues should/must be considered in data driven decision making	knowledge	1
d	Explain the important issues around data governance	knowledge	2
e	Present real world examples of data bias and the unintended consequences of using analytics, machine learning, and AI in making decisions	knowledge	2
f	Discuss the importance of provenance, transparency, and explainability in data analysis and the ability to build trust	knowledge	2
g	Explain the importance of personal privacy issues related to the collection and usage of data	knowledge	2
h	Demonstrate an understanding of the way your machine learning algorithms are vulnerable and can be manipulated	knowledge	2
i	Explain the limitations and potential unintended effects of machine learning when such algorithms encounter new scenarios	knowledge	2
j	Understand potential societal impacts of using machine learning	knowledge	2
k	Explain individual and data bias and the implications each has in data analysis	knowledge	3