❝ Two University of Washington professors are teaching a course to help students “think critically about the data and models that constitute evidence in the social and natural sciences,” according to the introduction to the course.
The 160-seat seminar, titled “Calling Bullshit in the Age of Big Data,” begins in late March and continues for roughly 10 weeks. Members of the general public can follow the course syllabus, including readings and recordings of lectures, at the course’s website.
❝ At the end of the course, students should be able to “provide your crystals-and-homeopathy aunt or casually racist uncle with an accessible and persuasive explanation of why a claim is bullshit,” according to the syllabus.
❝ The syllabus went viral after it was posted last month…the instructors’ email inboxes were overflowing, and some book offers were even made. The course reportedly filled all open seats within the first minute of online registration at UW.
❝ Jevin West told Recode that he and Bergstrom started to notice a trend in the last few years: More bullshit in the articles they were reviewing…One area of big problems: Big data…He said he noticed methods of statistics meant for smaller data sets being applied to “big” data sets with millions or billions of examples, where it’s easy to force a correlation that isn’t necessarily accurate.
He also observed situations where machine learning algorithms were “overfitting” data. Basically, you can have an algorithm that so specifically matches a particular data set, meaning it reflects even errors or noise, it fails when applied to another data set where you would otherwise expect it to work. You would normally want an algorithm that is sufficiently general to fit more than one data set.
Just in case you worried that our so-called president was left out.