By Stuart Russell Although it was published several years after Bostrom’s Superintelligence, I recommend reading Human Compatible first. Russell covers similar ground with respect to the problem of control over a superintelligence but in a style that I think most interested readers will find easier to follow and more insightful. If you then want a… Read More »
Given that I was reading Factfulness during the early stages of the COVID-19 crisis, the book was a pleasant release from the bitter news each day, even though Ebola, tuberculosis, the swine flu, and the Spanish flu play important roles in the book. In chapter ten in the section “The five global risks we should… Read More »
AIQ by Nick Polson and James Scott is a book I would have loved to have written. I often give talks to non-engineers on the core ideas behind machine learning, deep learning, and artificial intelligence. It took me many months to refine the material but I think it is possible to convey the core ideas… Read More »
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz is a deeply analytical, and yet hilarious, look at what Internet users tell us through their behaviors, as opposed to what they might directly tell us if we asked them. Stephens-Davidowitz digs deep into… Read More »
In Naked Statistics, Charles Whelan does a great, and often very funny, job of not only explaining statistics in very simple terms, but also explaining why you should understand statistics. Statistics can be used to simplify complex situations to a small set of indexes or metrics, many of which are meaningful only for relative comparisons.… Read More »
How Not to Be Wrong: The Power of Mathematical Thinking by Jordan Ellenberg is a very funny and beautiful book about math and is my favorite book of the year so far. It’s very rare that when I finish a book, I have the urge to read it again. But, that’s how I felt after finishing How Not to Be Wrong,… Read More »
Provost and Fawcett do a fantastic job of describing the main techniques used in data mining – classification, clustering and regression – along with high level explanations of the algorithms most commonly used for each. In addition, they present an expected value framework that is very useful for choosing the right balance between true positives,… Read More »