"Practical Data Ethics"
Free online course released on fast.ai this month from Rachel Thomas:
In this course, we will focus on topics that are both urgent and practical. In keeping with my teaching philosophy, we will begin with two active, real-world areas (disinformation and bias) to provide context and motivation, before stepping back in Lesson 3 to dig into foundations of data ethics and practical tools. From there we will move on to additional subject areas: privacy & surveillance, the role of the Silicon Valley ecosystem (including metrics, venture growth, & hypergrowth), and algorithmic colonialism. I realize this course still just covers a slice of what is a sprawling field, and I hope that it will be a helpful entry point for continued exploration.
Looks like a lot of interesting useful material. Barrier-to-entry seems low too:
This class was originally taught in-person at the University of San Francisco Data Institute in January-February 2020, for a diverse mix of working professionals from a range of backgrounds (as an evening certificate courses). There are no prerequisites for the course.
Jim Bagrow
Associate Professor of Mathematics & Statistics
My research interests include complex networks, computational social science, and data science.