Ethics of Artificial Intelligence

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Course Description

Machine learning has become an indispensable tool for creating intelligent applications, accelerating scientific discoveries, and making better data-driven decisions. Yet, the automation and scaling of such tasks can have troubling negative societal impacts. Through practical case studies, you will identify issues of fairness, justice and truth in AI applications. You will then apply recent techniques to detect and mitigate such algorithmic biases, along with methods to provide more transparency and explainability to state-of-the-art ML models. Finally, you will derive fundamental formal results on the limits of such techniques, along with tradeoffs that must be made for their practical application. CS229 or equivalent classes or experience.

Grading Basis

ROP - Letter or Credit/No Credit

Min

3

Max

4

Course Repeatable for Degree Credit?

No

Course Component

Lecture

Enrollment Optional?

No

Does this course satisfy the University Language Requirement?

No

Programs

CS281 is a completion requirement for:
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