A recent discussion of curiosity prompted me to start wondering about the importance of curiosity as a factor in research. Most people seem to agree that curiosity is a useful intrinsic motivator for research at the macro level. And discussions I’ve seen make a strong case for curiosity working better as a motivation for research at the macro-level than other potential motivators—status, prestige, etc. But, every time I read or think about this, I’ve felt this nagging unease that I only just managed to pinpoint the source of. My unease comes from my uncertainty about how much curiosity can drive act as a single source of motivation to do day-to-day work in the absence of “discipline”.
Personally, as I mentioned in a comment on this post, I haven’t found that curiosity on its provides sufficient motivation for me to continue making progress on work day after day. Even for work I’m genuinely interested in, there tend to be parts that are more and less interesting, so I still need to employ daily scheduling to make continuous progress.
However, I’m a nobody, and famous thinkers like Richard Feynman talk about how they’re motivated by the pleasure of finding things out and getting unstuck by playing. I love Feynman as much as the next person, but am wary of over-updating on his example or the public persona of any eminent thinker for that matter.
So instead, I’m curious to hear from people here: how much are you able to motivate yourself day-to-day via curiosity? Does this motivation substitute for scheduling / planning or complement it? Bonus points for discussing what your work tends to be and whether there are certain parts of it that you are more / less motivated to by curiosity.
I’m a post-bacc student researcher, a teacher, and I do project management, working toward a career in biomedical research.
It’s hard to translate a general problem into a concrete understanding of specific technical issues and solutions for them. I find it hard to stay curious, and to continue work, when I lose sight of what new insight the project I’m working on is going to reveal. Not only that, but if I catch a whiff that my project is either overbuilt or underbuilt, it can kill my motivation before I have even fully clarified that to myself.
Example:
I was interested in a heavily-cited study in the field of education, which graded education department dissertation reviews for the quality of their content and found low scores. They’ve since used this as justification for overhauling their program to focus more on scholarship. But they never actually checked to see whether dissertation lit reviews are correlated with career outcomes, or did any kind of published experiment.
I wanted to look for such a correlation with career outcomes, and I was interested in STEM research. Up to this point, I was riding on pure curiosity, and found it easy to read, write, and stay engaged.
At first, I was going to copy the authors by grading 30 biochem dissertations from around the year 2000 for the quality of their lit review, then supplement this grading by correlating the grades with the h-index of the authors 20 years later. This would have taken a lot of work. It was a major divergence from the original study. And I found it difficult to start.
Then I hit on the idea of a much simpler study, simply checking whether there was a difference in total publication count (easier to measure) among authors whose STEM dissertations contained a stand-alone lit review vs. those who did a purely empirical lit review. This required no grading. And, I realized that of course I would want to know this before I committed to the larger project.
It took me an hour or two to gather the data and plot it, and I found no correlation. Right then and there, I realized that my prior on the genuine causal importance of the content of a literature review on long-term career impact, especially in STEM, was so low that this data tipped me over into “why bother” territory.
And that was great, because I was doing all this as part of a larger research project to identify was to help undergraduates become better STEM researchers—very meta, I know. I have lots of other avenues to investigate. So getting no result in my exploratory data allowed me to abandon that line of inquiry for others that might be more fruitful.
If I’d gone through with the full analysis, I’d have used up so much time and energy, only to arrive at a result that would still just have been a non-experimental observation, and not very reliable at that, that who knows what I’d have done? Maybe I’d have tried to act as if finding a correlation there was important.
Conclusion:
I think this is why curiosity really is a consistently important motivator, not just a way to get started. If you are always keeping your primary research objective in mind—in my case, how to help undergrad STEM students become better researchers—then being guided by a sense of curiosity about that central question will help you prioritize your sub-projects.
If you’re driven by pure “grit” to keep going on a specific sub-project even when you’ve lost your curiosity, then maybe that’s a sign that you no longer believe the work you’re doing is going to teach you enough to justify the cost of investigation. I conjecture that “grit” might be associated with sunk-cost-fallacy reasoning.
I think the idea of curiosity being a transient sensation akin to emotion or hunger is not accurate, or at least not what I mean when I use the term in an intellectual sense. Nor is it distractability, the desire to jump down every rabbit hole that presents itself. Instead, it’s about having goals that stem from a sense of value and importance, which remain fundamentally steady even as you update the specifics over time.
It’s the intellectual equivalent to having a house half-built.
I find that the older I get the less curiosity for its own sake works as a motivator and the more I’m most strongly motivated to do things because I want to generate the outcomes of the work.
The standard story on this is something like age is inversely proportional to curiosity “essence”, but I think we can do a bit better than that. Some ideas of what this is happening to me and why it happens to lots of people:
changes in the brain (though this is basically a scientifically justified version of the “essence” theory)
changes in life circumstances (I’m more rewarded for getting results than effort the older I get)
knowledge saturation (the more I know the less I don’t know and so the gains from curiosity drop over time)
On knowledge saturation, there’s also a nuance there which is that I find I get most curious when I’m trying to do something and I’m looking at some narrow part of the world related to doing that something. For example, I started a new job recently and the company uses different databases than I have recently been using, so I’ve been digging in a lot to understand things about these databases and how they differ from the ones I’ve used a lot and am already expert with. I wake up excited to read about the internals of them because I know having a deep understanding about them will make me better at my job. This is a kind of “targeted” curiosity that’s a bit different than the normal “general” curiosity we think about when we talk about curiosity because it’s not interest for its own sake, but it still looks a lot like curiosity even if it is motivated.
Not a researcher—I’m a fairly senior engineer at a large tech company. I do work closely with applied scientists, and am currently building systems used primarily by researchers.
For myself, I am driven mostly by curiosity, and struggle to maintain discipline to actually complete things once I understand them well enough to know how they probably will work.
My main technique for actually doing, as opposed to thinking and exploring, is guiding that curiosity into different levels of detail.
As long as I remember to wonder how this behavior is happening at the code level, and I remind myself that I don’t really get it fully until I see it working in the debugger , I can use that curiosity to drive the detail work of actually delivering well-understood working code.
This works at other levels too—wondering if a feature actually helps users leads to wanting to understand the overall processes that users are performing, and figuring out how to instrument things in order to measure impact.
I’ve also found this to work well in my work as a programmer, but it’s generally something I have to remind myself to do in a reactionary way and therefore doesn’t seem to help me “get my butt in the chair”. So, this is a good reminder to try and guide my curiosity in the way you described, thanks!