Deep research requires a slower pace than tech industry work

Anyone working in an industry for a while will become accustomed to that culture—its processes, its norms, its values, its tacit knowledge. Much of this is incredibly valuable, of course, but these ideas can also represent constraints. There are some important impedances here between tech industry culture and research culture. In particular, tech culture is calibrated to a much faster pace. This can lead to impatience or early abandonment when confronting problems which require a researcher’s pace.

A “huge project” for a Silicon Valley tech person may be a year or two long; a “huge project” for a researcher may last a decade. Persistence with a difficult problem may require tens of hours for a tech person and hundreds of hours for a researcher. It’s not that the tech people are constitutionally lazy or something like that: in that industry, it’s usually a bad idea to spend many hundreds of hours thinking about a single problem. But foundational insights often do require more patient, focused thought than tech culture would support, so people from tech culture may struggle to sit with a fundamental problem for the time required to make progress. More broadly: San Francisco tech culture makes research hard.

Personally, coming from the tech industry, I’ve noticed that my expectations around the pace of progress are seriously miscalibrated for many research problems. I’ll feel like I’ve been banging my head against a question forever, but it’s only been a few tens of hours—that’s nothing in this space! If I continue expecting results at the rate I’ve been expecting them, I suspect that I’ll both miss the results I’m looking for and also drive myself nuts. An important aspiration for me is to get much more comfortable slowing down.

One related special case: Inappropriate time pressures often harm creative work


References

Michael Nielsen on Twitter:

So many people give up, saying “I’m not good at proof”. When really {it has nothing to do with not being good at proof, but at not being good at dealing with being stuck and uncertain, and learning from ideas that don’t immediately succeed}.

Arun Rao, A History of Silicon Valley (excerpt):

As Xerox Chief Scientist Jack Goldman told Xerox execs: “If you hire me, you will get nothing of business value in five years. But if you don’t have something of value in ten years, you’ll know you’ve hired the wrong guy.”

(via Geoffrey Litt)

Correspondence with Michael Nielsen, 2020-07-08. Re: Early efficacy results on control vs delay5Days: hiding in-text questions sinks 5-day recall

Last updated 2023-07-13.