This course highlights the ethical responsibilities we have as statisticians and data scientists when working with data. This course demonstrates situations where ethical concerns with data arise and helps train our brains to be more aware of how data are used and the intent behind data collection. By the end of this course, you will be able to identify misrepresentation in visualizations, describe the basics of data privacy, and recognize potential situations where algorithmic bias is at play.
Overview
Syllabus
- Data Ethics
- Data ethics is an essential component for those who work with data. In this module, we will become aware and hold discussions around how data visualizations can mislead and strategies to mitigate these types of situations. Further, we will discuss and critically think about data privacy. Lastly, we will define algorithmic bias and be aware of situations where this type of bias can occur.
Taught by
Mine Çetinkaya-Rundel and Dr. Elijah Meyer
