Many moons ago, my friend the super-librarian Dianne and I used to hang out in Ann Arbor and talk about feminism and computers. She has FAR MORE formal training with computers (like, a lot compared to none) and I have a bit more training in feminist critical theory. We had a lot of fun, but I definitely got the better part of this deal, because I had the privilege of having Dianne shape my professional thinking. And here, I share with you, the single principle that will never leave me.
- Never have a human do something that a computer is better at, even if it takes longer to explain to the computer than it would have been to do by hand.
SURELY I can’t mean that every single time I want to transform a bunch of lines of something to somewhere else, I write an xslt or a bit of python or whatever, right? Well, no, I don’t, because I’m not as smart and disciplined as Dianne. But I should. Because the time I spend transforming data by hand only results in transformed data — but the time I spend learning how to do it programmatically results in me having another tool in my toolkit. I have seen some CRAZY examples of people in libraries having students transform data by hand (or worse, doing it themselves).
Confession bear time:
- Once, in grad school, to keep me busy on the reference desk I had to manually find webpages for publishers of journals. This list was more than a thousand lines long. A computer can do this.
- Once, in my last job, I made a student sit down with a spreadsheet and identify dates in title fields, pull them out, and put them in a different field. I’m so embarrassed to even admit that. A computer can do this.
- In my life, I have done so much copying and pasting and pulling down of Excel cells. There are better ways. I have learned some of them. I need to learn more.
- Because I didn’t start by learning tools that would help me verify the correctness of my data transformations, I have shot myself in the foot SO MANY TIMES. There are ways to put safeguards in place. I need to employ them more often.
We work with too much data too often to not figure out the right tools to deal with it. We need to stop repetitively manipulating data by hand, or at least cut back, and start thinking through what kinds of things we would need to tell a computer to do, even if we don’t yet speak the language.