Last Friday, the National Research Council released a report titled Computing Research for Sustainability, written by the NRC’s Committee on Computing Research for Environmental and Societal Sustainability, on which I served (press release). This was a novel experience for me given that I was the only non-computer scientist on the committee. That said, I think the report is quite interesting for a number of reasons. As a statistician, I took away a few lessons.
- Sustainability presents many opportunities for CS. One of the first things the committee did was hold a workshop where researchers from all over presented their work on CS and sustainability—-and it was impressive. Everything from Shwetak Patel’s clever use of data analysis to monitor home power usage to Bill Tomlinson’s work in human computer interaction. Very educational for me. One thing I remember is that towards the end of the workshop John Doyle made some comment about IPv6 and everyone laughed and…I didn’t get it. I still don’t get it.
- CS faces a number of statistical challenges. Many of the interesting areas posed by sustainability research come across, in my mind, as statistical problems. In particular, there is a need to develop better statistical models for understanding uncertainty in a variety of systems (e.g. electrical power grids, climate models, ecological dynamics). These are CS problems because they are “big data” systems but the underlying issues are largely statistical. Overall, it seems a lot of money has been put into collecting data but relatively little investment has been made (so far) in figuring out what to do with it.
- Statistics and CS will be crashing into each other at a theater near you. In many discussions the Committee had, I couldn’t help thinking that a lot of the challenges in CS are exactly the same as in statistics. Specifically, how integrated should computer scientists be in the other sciences? Being an outsider to that area, it seems there is a debate going on between those who do “pure” computer science, like compilers and programming languages, and those who do “applied” computer science, like computational biology. This debate sounds eerily familiar.
It was fun to hang out with the computer scientists for a while, and this group was really exceptional. But now, back to my day job.