Ethics in the Age of AI Specialization

In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models.

In this course, we will explore fundamental concepts involved in security and privacy of machine learning projects. Diving into the ethics behind these decisions, we will explore how to protect users from privacy violations while creating useful predictive models. We will also ask big questions about how businesses implement algorithms and how that affects user privacy and transparency now and in the future.

AI Ethics research is an emerging field, and to prove our skills, we need to demonstrate our critical thinking and analytical ability. Since it's not reasonable to jump into a full research paper with our newly founded skills, we will instead work on 3 projects that will demonstrate your ability to analyze ethical AI across a variety of topics and situations. These projects include all the skills you've learned in this AI Ethics Specialization.