Data: Ethical Issues and Best Practices and Ethical Issues and Best Practices in Analytics
Instructor: David Corliss, Principal Data Scientist at Grafham Analytics and University of Michigan Institute for Data Science (MIDAS) as a Data and AI in Society Specialist
Full-Day Course
Description:
This workshop discusses ethical issues in data and analytics. The class spends 20-30 minutes each on a series of issues, alerting students to the existence of these issues and how to identify them. The course includes a half day on data issues such as privacy and data ownership, followed by a half-day on analytics issues such as p-hacking, sources of bias, and responding to algorithm failure. The workshop teaches a practical and applied understanding of ethical issues in data and analytics, presenting concrete examples of both good and bad practices, enabling course attendees to be better aware of and address potential issues.
Part 1: Ethical Issues in Data Ownership, Use, and Practices • Data Ownership • Data Privacy • Ethics of Data Usage • Ethics of Data in the Workplace
Part 2: Analytics and Algorithms - Ethical Issues and Best Practices • Bias in Analytics • Ethics of Algorithm and Model Failure • Ethical Analytics Practices in the Workplace • Analytics intentionally used to cause harm
About the instructor:
David J Corliss, PhD is the Principal Data Scientist at Grafham Analytics and holds an appointment at University of Michigan Institute for Data Science (MIDAS) as a Data and AI in Society Specialist. His work in ethical best practices includes writing a column on Data for Good in Amstat News and serving on the steering committee of the Statistics section of the American Association for the Advancement of Science. Dr. Corliss is the founder of Peace-Work, a volunteer cooperative of statisticians, data scientists and other researchers applying analytics in issue-driven advocacy.
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