DATA 340 - Data Science Ethics

Units: 3
Understanding ethical implications of one’s personal data, the risks and rewards of data collection and surveillance, and the needs for policy, advocacy, and privacy monitoring. Implications of algorithms and models.

Prerequisites: STAT 215 or DATA 215
Possible Instructional Methods: Hybrid, or Online-Asynchronous, or Online-Synchronous.
Grading: A-F grading only.
Cross-listed: STAT 340
Course Typically Offered: Fall ONLY

Student Learning Outcomes - Upon successful completion of this course students will be able to:

Describe how data science transform how people live and how societies function.
Identify and carefully distinguish challenges particular to data science and other related computational methods of analysis such as Machine Learning and Artificial Intelligence.
Explain data lifecycles and ethical implications on a personal and global level.
Communicate orally and in writing a critical analysis and an argumentative position regarding novel ethical and practical issues related to data science in relation to privacy, surveillance, and moral responsibility.