We’re Reading About Bias in AI, SpaceX, and More

Reading list from the curators of data.blog

Data for Breakfast

Yanir Seroussi

I have two recent reads I’d like to share. First, “Abandon statistical significance,” by McShane et al., is a well-written argument against the cult of p-values. As anyone who has seriously looked into the matter knows, a result can be statistically significant but nonsensical, or not statistically significant and valid. It’s time to look at the full body of evidence rather than focus on arbitrary thresholds.

Second, “Imposter syndrome” by Brandon Rohrer discusses the meaning of being a real data scientist. In his words: “Our goal isn’t to accumulate answers, but to ask better questions. If you are asking questions and using data to find answers, YOU ARE A DATA SCIENTIST.”

Robert Elliott

I’ve got three pieces I’d like to share. In the first piece, “Forget Killer Robots—Bias Is the Real AI Danger,” “John Giannandrea, who leads AI at Google, is worried…

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By Boris Gorelik

Machine learning, data science and visualization http://gorelik.net.

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