I often find this kind of advice too vague to really be useful. “Have taste” in the problems you work on isn’t very actionable. (Unless perhaps you list examples of good and bad taste.)
I’ll admit that I may just be immature at research as almost all my experience has either been attempting to replicate research or to put it into practice in production systems.
"Having taste" is mostly about predicting the future. Which problems are worth studying, which problems you are capable of solving, and which solutions turn out to be important, in retrospect. If there was an actionable way of developing taste in something, the activity itself would probably be so predictable that it would not be a particularly good research topic.
Taste is mostly about having a good intuition on the topics where your intuition is worth following. It tends to develop with experience. But if you want to develop the kind of taste that helps picking good research topics, you need the right kind of experience for that field of research. Experience that turns out to be of the right kind, in retrospect. If your experiences and interests align (again in retrospect), you will probably develop a good taste for research problems in your field of interest. But that requires some amount of luck, in addition to everything else.
Unrelated, but I see the use of the phrase "taste" as having a strong Twitter / e/acc smell (in a negative way).
I tend to associate it with folks who are prepared to victim blame researchers for not adapting to the "new economy" as being people who have "bad taste" or "low agency", maybe as a way to rationalize/justify the upcoming inqeuality that AI will create.
Basically a recycling of the way "IQ"/smarts/hard-work has historically been used to justify disproportionate rewards for the upper class.
(Obviously a gigantic stretch on my part, and not saying the author is in this camp, but just wanted to vent somewhere)
For non-CS people – if you're a little confused by "conference paper", CS is a little idiosyncratic in that papers are often primarily disseminated through conferences, rather than independent journals. The advice is good in general, though!
I’ve always thought the issue was a bit less “Find the interesting research problem” and more “Find the resources, network, or skills that get you into the position of being able to work on the interesting research problem.”
If you asked a bunch of researchers working on the “boring” stuff to predict what the hot papers of the year will be about, do we really think they’ll be that far off base? I’m not talking about groundbreaking or truly novel ideas that seem to come out of nowhere, but rather the high impact research that’s more typical of a field.
Even in big tech companies, it’s quite obvious what the interesting stuff to work on is. But there are limited spots and many more people who want those spots than are available.
Interesting. I don't quite agree. It's one thing to predict what general topics will be hot and popular this year. But that's not the same as what particular research problem will be important and have lasting influence.
There are a few kinds of important research. One is solving a well-defined, well-known problem everyone wants to solve but nobody knows how. Another is proposing a new problem, or a new formulation of it, that people didn't realize was important.
There is also highly-cited research that isn't necessarily important, such as being the next paper to slightly lower a benchmark through some tweaks (you get cited by all the subsequent papers that slightly lower the benchmark even further).
In the book The Cuckoo's egg, Cliff Stoll talks to I think Luiz Alvares. I don't have the book handy here, but Alvarez basically told him to nit get distracted by grants, bosses, ... Here is interesting science to do, so go for it. Just run faster than the rest of the world.
In a way, it was a sidetrack of the book, but for me the attitude speaking from that text was interesting and inspiring. When I could pull it off, it tended to work.
You made me order The Cuckoo's Egg. Luis Alvarez is my scientific hero since I read his memoir last year. Truly underappreciated in the pop-sci community.
Very insightful! I found the section on killing papers to be a helpful reminder. As a Ph.D. student, this can be particularly challenging as your environment expects somewhat steady progress (annual reviews, advisor meetings, etc.), and you're encouraged to finish papers rather than starting over.
The actual title is "How to win a best paper award", which is quite different from doing "important research that matters". Most researchers work in very niche and specialized fields, sometimes for their whole life. They grant themselves all sorts of awards within their community, but it doesn't mean their research "matters".
> Another reason ignoring the literature can be helpful is that sometimes a bunch of work tries to solve some problem, and so everyone assumes it must be hard---just because no one has solved it yet, even though no one has really tried a fundamentally different approach
How does one approach collaborators in this situation? Like, hey, I have this idea that solves the problem you have been trying to solve in a fundamentally different way that invalidates all the legacy approaches you have invested in, BTW. My emails that follow this spirit tend to get ghosted.
Sometimes you don't need a collaborator if you have the idea. If the other party is not at all working on the angle that you're interested in, it's probably not the correct collaboration to ask to.
Also, a collaborator is usually not a stranger over the internet, it's often someone who you know and you already worked with, so it is not that ackward to expose a new idea and propose to work together.
It takes time and social skills to make long lasting collaborations, the two parties must trust each other in order to collaborate. In this context, exchanging ideas is not really an issue.
I often find this kind of advice too vague to really be useful. “Have taste” in the problems you work on isn’t very actionable. (Unless perhaps you list examples of good and bad taste.)
I’ll admit that I may just be immature at research as almost all my experience has either been attempting to replicate research or to put it into practice in production systems.
"Having taste" is mostly about predicting the future. Which problems are worth studying, which problems you are capable of solving, and which solutions turn out to be important, in retrospect. If there was an actionable way of developing taste in something, the activity itself would probably be so predictable that it would not be a particularly good research topic.
Taste is mostly about having a good intuition on the topics where your intuition is worth following. It tends to develop with experience. But if you want to develop the kind of taste that helps picking good research topics, you need the right kind of experience for that field of research. Experience that turns out to be of the right kind, in retrospect. If your experiences and interests align (again in retrospect), you will probably develop a good taste for research problems in your field of interest. But that requires some amount of luck, in addition to everything else.
Unrelated, but I see the use of the phrase "taste" as having a strong Twitter / e/acc smell (in a negative way).
I tend to associate it with folks who are prepared to victim blame researchers for not adapting to the "new economy" as being people who have "bad taste" or "low agency", maybe as a way to rationalize/justify the upcoming inqeuality that AI will create.
Basically a recycling of the way "IQ"/smarts/hard-work has historically been used to justify disproportionate rewards for the upper class.
(Obviously a gigantic stretch on my part, and not saying the author is in this camp, but just wanted to vent somewhere)
For non-CS people – if you're a little confused by "conference paper", CS is a little idiosyncratic in that papers are often primarily disseminated through conferences, rather than independent journals. The advice is good in general, though!
Yeah, and I always find the phrase "publish in a conference" to sound vaguely oxymoron-ish.
I’ve always thought the issue was a bit less “Find the interesting research problem” and more “Find the resources, network, or skills that get you into the position of being able to work on the interesting research problem.”
If you asked a bunch of researchers working on the “boring” stuff to predict what the hot papers of the year will be about, do we really think they’ll be that far off base? I’m not talking about groundbreaking or truly novel ideas that seem to come out of nowhere, but rather the high impact research that’s more typical of a field.
Even in big tech companies, it’s quite obvious what the interesting stuff to work on is. But there are limited spots and many more people who want those spots than are available.
Interesting. I don't quite agree. It's one thing to predict what general topics will be hot and popular this year. But that's not the same as what particular research problem will be important and have lasting influence.
There are a few kinds of important research. One is solving a well-defined, well-known problem everyone wants to solve but nobody knows how. Another is proposing a new problem, or a new formulation of it, that people didn't realize was important.
There is also highly-cited research that isn't necessarily important, such as being the next paper to slightly lower a benchmark through some tweaks (you get cited by all the subsequent papers that slightly lower the benchmark even further).
In the book The Cuckoo's egg, Cliff Stoll talks to I think Luiz Alvares. I don't have the book handy here, but Alvarez basically told him to nit get distracted by grants, bosses, ... Here is interesting science to do, so go for it. Just run faster than the rest of the world.
In a way, it was a sidetrack of the book, but for me the attitude speaking from that text was interesting and inspiring. When I could pull it off, it tended to work.
You made me order The Cuckoo's Egg. Luis Alvarez is my scientific hero since I read his memoir last year. Truly underappreciated in the pop-sci community.
Very insightful! I found the section on killing papers to be a helpful reminder. As a Ph.D. student, this can be particularly challenging as your environment expects somewhat steady progress (annual reviews, advisor meetings, etc.), and you're encouraged to finish papers rather than starting over.
This might also be of interest: https://karpathy.github.io/2016/09/07/phd/
mandatory: 'You and Your research' https://news.ycombinator.com/item?id=35776480
The actual title is "How to win a best paper award", which is quite different from doing "important research that matters". Most researchers work in very niche and specialized fields, sometimes for their whole life. They grant themselves all sorts of awards within their community, but it doesn't mean their research "matters".
> Another reason ignoring the literature can be helpful is that sometimes a bunch of work tries to solve some problem, and so everyone assumes it must be hard---just because no one has solved it yet, even though no one has really tried a fundamentally different approach
How does one approach collaborators in this situation? Like, hey, I have this idea that solves the problem you have been trying to solve in a fundamentally different way that invalidates all the legacy approaches you have invested in, BTW. My emails that follow this spirit tend to get ghosted.
Sometimes you don't need a collaborator if you have the idea. If the other party is not at all working on the angle that you're interested in, it's probably not the correct collaboration to ask to.
Also, a collaborator is usually not a stranger over the internet, it's often someone who you know and you already worked with, so it is not that ackward to expose a new idea and propose to work together.
It takes time and social skills to make long lasting collaborations, the two parties must trust each other in order to collaborate. In this context, exchanging ideas is not really an issue.
This is an exceptional read.