One way you can approach this in a scientific context is by picking a broad unsolved or imperfectly solved problem (“cure cancer,” “outperform the market,” “improve personal productivity”) and dividing it into sub-problems at progressively granular levels of detail.
You’d look for descriptions of things like:
Theory that articulates the general nature of the problem. For cancer, it’s things like selection for drug resistance and immune system evasion. For outperforming the market, it’s the EMH and analyzing risk. For improving personal productivity, it’s the ratio of salesmanship to science in the field.
Understanding how people work on the problem. For cancer, it’s divided into areas like screening, treatments, classifying cancers, and identifying pathways of cancer growth and suppression. For outperforming the market, it’s analyzing specific markets or evaluating investment strategies. For personal productivity, it’s researching products, building habits, improving motivation.
It seems very important to me to work on problems you can actually solve with the tools you have on hand. For example, I am preparing for grad school in bioengineering. As it is, though, I don’t have access to a biology lab. I’m just living in my apartment. I have a nice computer, a light microscope, a few basic chemistry apparatus from the in-home o-chem labs I took during COVID, and that’s about it.
Hence, despite my interest in problems like biosecurity, cancer, aging, Alzheimer’s, and vaccine development, I don’t have much of an ability to work on any of these problems with the tools I have at hand. I don’t have access to data, equipment, expertise, funding, or mentorship.
But I can do a couple things.
I can work on projects related to the work I want to do, but that require only what I have on hand. For example, although I can’t work on the project “cure Alzheimer’s,” I can work on the problem “understand how scientists are trying to cure Alzheimer’s,” a purely scholarly project.
I can find projects that are tractable with the tools I have on hand. For example, I might be able to do some actual bioinformatics or mathematical modeling. I could re-analyze published datasets. I can build software tools.
I can expand my resources, trying to acquire new pieces of equipment, funding opportunities, and building my network.
One way you can approach this in a scientific context is by picking a broad unsolved or imperfectly solved problem (“cure cancer,” “outperform the market,” “improve personal productivity”) and dividing it into sub-problems at progressively granular levels of detail.
You’d look for descriptions of things like:
Theory that articulates the general nature of the problem. For cancer, it’s things like selection for drug resistance and immune system evasion. For outperforming the market, it’s the EMH and analyzing risk. For improving personal productivity, it’s the ratio of salesmanship to science in the field.
Understanding how people work on the problem. For cancer, it’s divided into areas like screening, treatments, classifying cancers, and identifying pathways of cancer growth and suppression. For outperforming the market, it’s analyzing specific markets or evaluating investment strategies. For personal productivity, it’s researching products, building habits, improving motivation.
It seems very important to me to work on problems you can actually solve with the tools you have on hand. For example, I am preparing for grad school in bioengineering. As it is, though, I don’t have access to a biology lab. I’m just living in my apartment. I have a nice computer, a light microscope, a few basic chemistry apparatus from the in-home o-chem labs I took during COVID, and that’s about it.
Hence, despite my interest in problems like biosecurity, cancer, aging, Alzheimer’s, and vaccine development, I don’t have much of an ability to work on any of these problems with the tools I have at hand. I don’t have access to data, equipment, expertise, funding, or mentorship.
But I can do a couple things.
I can work on projects related to the work I want to do, but that require only what I have on hand. For example, although I can’t work on the project “cure Alzheimer’s,” I can work on the problem “understand how scientists are trying to cure Alzheimer’s,” a purely scholarly project.
I can find projects that are tractable with the tools I have on hand. For example, I might be able to do some actual bioinformatics or mathematical modeling. I could re-analyze published datasets. I can build software tools.
I can expand my resources, trying to acquire new pieces of equipment, funding opportunities, and building my network.