Kaiser Fung, founder of Applied Analytics at Columbia University and Principal Analytics Prep, the premier data analytics bootcamp from Harvard Business School Startup Studio, discusses how a software vendor uses the power of suggestion to seduce users into believing the accuracy of predictive analytics; and how such a tactic got exposed by the visibility of errors.
Kaiser Fung, author of Numbersense and founder of Principal Analytics Prep, discusses the rejection of a predictive model used to find vulnerable children at risk for child abuse in Chicago.
Kaiser Fung, founder of Principal Analytics Prep and Columbia's MS in Applied Analytics, discusses an article by Rodney Brooks (MIT) on the future of AI.
Kaiser Fung, author of Numbersense and founder of Principal Analytics Prep, sees a crisis of confidence in self-reported non-financial metrics by technology upstarts. He calls for third-party auditing.
Kaiser Fung, founder of Principal Analytics Prep, discusses some market research about pricing changes at Whole Foods after the Amazon acquisition.
Kaiser Fung, founder of Principal Analytics Prep, and former director of Applied Analytics at Columbia University, explains why you can't run proper A/B tests on Facebook
New York Times reports that Harvard rescinded admission offers to 10 students (link). These kids allegedly engaged in horrible behavior on "private" chatrooms online. Not reported is how Harvard admission officers got a hold of such information. Is it possible there are jealous classmates? I am not condoning the bad behavior - I put this link up to remind people: (a) no data are private, not even "deleted" data (b)…
A nice article in Zerohedge about the recent rate hike for Tesla owners (link). Of course, Tesla is crying foul. The gist of the story is that Tesla owners tend to get into more crashes and the repair cost is higher than for other brands. The former is a matter of statistics - but also self-selection: in my limited encounters, the first things Tesla owners tell me about their cars…
When we use the words artificial intelligence, we typically mean artificial machine intelligence, training machines to act like human beings. What is actually happening is the opposite - we are developing artificial human intelligence, as in, humans are being trained to think like machines. Example 1: I recently called a cab company and told them I was at Union Square. The despatcher was taking a long time to respond, and…
Kaiser Fung, founder of Principal Analytics Prep, discusses Seth Stephens-Davidowitz's new book, Everybody Lies
