Data science ethics

This unit touches on data science ethics, specifically on issues of misrepresentation of data and results, data privacy, and algorithmic bias. Course lectures are supplemented with “guest lectures” from domain experts.

Slides, videos, and application exercises

Unit 3 - Deck 1: Misrepresentation

Alberto Cairo - How charts lie

Unit 3 - Deck 2: Data privacy

The Guardian - Cambridge Analytica whistleblower

Unit 3 - Deck 3: Algorithmic bias

Joy Buolamwini - How I’m fighting bias in algorithms

Cathy O’Neil - Weapons of Math Destruction

Safiya Umoja Noble - Imagining a Future Free from the Algorithms of Oppression

Kristian Lum - What’s An Algorithm Got To Do With It


Lab 9: Conveying the right message through visualisation

Improving data visualisations to better convey the right message