40 GENIUS INTERVIEW Lauren Klein
ENGINEERSWHO CAN’TWRITE WORK FOR ENGINEERSWHOCAN
looking to start a data science department. They’re trying to make it a programme that brings together statistical methods and data analysis techniques, high- performance computing with traditional liberal arts disciplines – not just English, but the social sciences. So I’ve just finished our first year there – online. I think it’s increasingly clear to more people that we need these humanistic approaches to address all the technical stuff we’ve got out there. The problems we’re causing are so enormous that we need all the methods at our disposal to help figure out how to solve them. FEED: We do constantly hear that we need to get more people into STEM (science, technology, engineering & maths). But sometimes that feels a little short-sighted. LAUREN KLEIN: The really interesting thing is that at Georgia Tech, a big engineering school, as is MIT, where my collaborator Catherine D’Ignazio works, have huge amounts of humanities requirements for the engineers. There’s a joke at MIT, which was passed on to Georgia Tech, that engineers who can’t write, work for engineers who can. FEED: You collaborated with MIT’s Catherine D’Ignazio on the book, Data Feminism. How did this come about? LAUREN KLEIN: We actually didn’t know each other before we started working together. I think that’s different from how most collaborations work. But for me and Catherine, it was a case of us both being interested in this very specific thing. One of my research interests is the history of data visualisation and the people who have been left out of the standard, Edward Tufte-style account of how you ought to design clean, clear, minimalist data visualisations. It turns out there’s a whole bunch of people who don’t fit into that lineage and have been doing really interesting stuff for hundreds of years. I’m working on a project now that looks back to some of these 18th and 19th century early visualisation innovators.
A PERFECT PARTNERSHIP Catherine D’Ignazio is director of the Data + Feminism Lab, MIT, and co- authored the Data Feminism book
A lot of them, it turns out, were women, coming from places like primary schools, teaching young children. As they were early childhood educators, they weren’t viewed with the same level of prestige as someone like William Playfair who was a Scottish political economist who invented the pie chart. People think a serious intellectual inquiry looks like political philosophy or political economy. They don’t think it looks like teaching kindergarten. Edward Tufte is an American statistician, working at Yale. His big thing is that visualisation should be clear and incisive; you should look at it and, in an instant, be able to tell what the data say. But a lot of these early women were using visualisation in different ways, as tools to think with. One of the people I’ve written about – and I’ve tried to reuse or reanimate some of
her techniques – had this big chart that she laid out like a rug and invited the kids to sit around it and sort of contemplate things like colour for example. She really viewed visualisation as this process where the kids would be coming to their own learning in their own way, rather than her doing it from top down. That’s a very feminist theoretical move to say that knowledge isn’t like this top down system where you just need to believe what I say is true, but that it is this process and interplay between the person who knows something and the person who is coming to know. FEED: And how did the book Data Feminism come about? LAUREN KLEIN: I had come to Boston to give a talk on a historical project that
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