What I’ve been reading this week, 22 December 2019

This is an overview of articles that I read this week and shared via my weekly newsletter. It covers the best of analytics and experimentation related content.

1. One Nation, tracked
Massive investigation into the smartphone tracking industry by The New York Times. Read the article.

2. Biased Algorithms Are Easier to Fix Than Biased People
Racial discrimination by algorithms or by people is harmful — but that’s where the similarities end. Also from NYT. Read the article.

3. Refuted Causal Claims from Observational Studies
Ronny Kohavi shared a new chapter from his upcoming book (available for pre-order). “We review famous examples where causality was claimed as likely in observational studies, but later refuted in studies higher in the hierarchy of evidence, such as randomized controlled experiments.” Read the article.

4. How Imperfect Foods built a culture of experimentation
Read the article.

5. Extending monitoring from application performance to features
Lizzie Eardley from Split explains the advantages of feature monitoring. Read the article.

6. The 3 A’s of becoming a data-driven organization
Accurate, Accessible and Actionable. Read the article.

7. Build a Career in Data Science (book)
Emily Robinson and Jacqueline Nolis have released their new book.
Read more.

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