This week, Sirin, Boris, and Demet have some recommended reading for you in the fields of descriptive data analysis, machine learning, and ethics in artificial intelligence. Have you recently read anything thought-provoking in the field of data science? Written anything thought-provoking? Be sure to comment and share your recommendations with us.
Seth Stephens-Davidowitz studies publicly available, anonymous Google Search data. His work reveals prejudices and sheds light on aspects of demography that are hard to tackle with surveys. It’s a long, yet captivating read and a great example data story telling that shows how insightful descriptive data analysis can be. It’s also deeply infuriating because, among other things, his work implies that open racism and biases against girls are widespread.
The post “Supervised learning is great — it’s data collection that’s broken” talks about the pain common to many machine learning practitioners, namely, obtaining…
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