OPEN THE GATES
Causal Design Patterns for Data Analysts
Everyone needs to be able to understand the difference between causality and correlation. But because the methods for doing so are scattered across disciplines like epidemiology and economics, there’s a high barrier to entry for those outside such fields. This post aims to break down those barriers. - Emily Riederer

REPORT IT
AI Incident Database
This repository of problems caused by AI is intended to help researchers and developers prevent similar harms from happening again. - AI Incident Database

POWER OF GOOD
Data Feminism
“Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems.” - Catherine D'Ignazio and Lauren F. Klein

DAYS OF FUTURE PAST
Sports Analytics 101: Descriptive vs. Predictive
Future performance doesn’t always resemble past performance, and that’s why we need both descriptive and prescriptive metrics. - Brendan Kent

COMING UP ROSES
Why Do I Use Flowers to Visualise Data?
Flowers can be excellent vehicles for conveying information because their petals, stalks, and stamens can represent many dimensions in just one object. - Questions in Dataviz