Being a military brat growing up, I moved a lot. About every three years, we would move halfway across the country (or, when I was very young, halfway across the world) so it’s not too surprising that it was only recently that I ever spent more than a couple of years in one spot.
There are some advantages, possessions-wise, in moving frequently. Moving sucks, logistically, so it incentivizes minimalism. The less stuff you have, the less you need to pack up. It also encourages you to sort through what you have, because if there’s some pile of boxes in the corner that never even get unpacked, then it’s probably likely there’s nothing you need in those boxes.
A few years ago, specifically 2019, the popularity of Tidying Up with Marie Kondo hit right at the same time as I was moving across the country (again). In addition to a physical, geographical transition, I was also transitioning emotionally and professionally, having also just gotten married and defending my PhD roughly 48 hours apart. All this to say that it was a perfect moment to reflect on all my physical stuff as I was packing it into boxes, and think about what was serving me by either literally being frequently used or by being emotionally valuable. Everything else was clutter that was taking up space in my small UHaul and should be donated or disposed of.
Having these “tidying” moments is useful to clean up a literal house and also a metaphorical house. In science and tech, there’s the idea of “tech debt”, where solutions do technically work for some problem, but they’re rushed, suboptimal, and eventually cause problems themselves because they don’t scale or require too much frequent fixing. So, every so often, it’s helpful to pause, inventory what’s going on, and spend some time resolving that tech debt so that there’s less problems in the future. Tidy up. Declutter.
I don’t think anybody ever has a perfectly minimal house, or a perfectly debtless tech stack. Those only exist in magazines and are almost entirely staged to look that way. The incentives to “move fast and break things” is too high in tech work to always take the slow, thorough route. But even if you have to take on some tech debt, it’s always nice to keep that debt manageable so that you don’t end up with the tech equivalent of a hoarding situation, or a critical process that ends up duct-tape-and-chewing-gum system that requires Windows 7 or something to remain functional.
Tech debt (and clutter) can also indicate a lack of focus or thoughtfulness. The quick and easy solution is not always the right one, “measure twice, cut once” or “buy it for life” kind of a situation. It’s the same with experimental design in the wet lab. Without thoughtful experimental design, like including all the proper negative and positive controls required to adequately interpret the results, you end up with a pile of uninterpretable data that needs to be repeated anyway. The simpler and more straightforward the experimental designs, the more likely you are to be able to draw a conclusion from it.
Too frequently, though, scientists are encouraged to move quickly. Usually too quickly to really be doing the science as rigorously as they should, or set up the processes required to sufficiently repeat an experiment. Some of this might come from misaligned incentives, as the publish-or-perish mentality in academia demands high output and productivity without the timelines that allow truly innovative ideas to come to fruition. Some of it is bad processes, as the manuscript-write-up process is usually only built around “successful” experiments, which the replication crisis has demonstrated as a not-infrequently lucky one-off observation rather than a truly reproducible phenomenon.
The lack of reproducibility, “reproducibility crisis”, in science is another form of tech debt, in a way. There’s a lot of “clutter” in the scientific literature, things that have been disproven or haven’t replicated and should probably be reduced or eliminated. Most scientists go through the rite-of-passage that is composing a “literature review”, basically reading everything they can find about a topic and organizing it into a “too long; don’t read” compilation, usually with some minor commentary or perspective to frame the topic.
While a lot of “mess” makes it into the scientific community, there’s also a lot of really good stuff that never makes it. It fades away because the grad student or postdoc moved on, or there was one last experiment to do that never got done, or just something else exciting came along and became the new shiny thing to work on. It’s the complete opposite side of the spectrum, a lack of work that should be out there but instead is cluttering someone’s abandoned to-do list.
It’s a shame that there’s probably a lot of good work out there that never got the attention it deserved, and it’s equally a shame that there’s a lot of bad work out there making a mess of the literature.
Lindsay K. Pino 