I’m an economics PhD student. I’ve spent some time thinking about a) how to do good and b) how to succeed in academia.
The holy grail is a project that does good and results in a paper publishable in a peer reviewed journal. But I have struggled with this and I’ve noticed a few other EAs in early stages of academia doing so too.
I’ve come to think the reason is that we are problem-solvers. We want to change people’s lives for the better. When we try to think of a research project, we think about the problems with the world, and how to fix them.
What makes a good academic research paper is fundamentally different. I am far from being an experienced academic, but I understand that research is about pushing forward the frontier of knowledge and understanding. Examples are finding a better way to explain observed phenomena, measuring something previously unmeasured, documenting a previously undocumented connection or relationship, inventing a new technique or using an old technique in a new way, or showing that supposedly separate things are just different examples of a general case.
It’s tempting to say “research is solving the problem of not understanding” or “problem solving is increasing your understanding of how to solve the problem”. But that shoe-horning only de-emphasises their considerable differences. I would rather think of them as two different stages of a process. Research creates the knowledge, and problem-solving applies the knowledge.
A trap for EAs in early-stage academia is to do work that makes the world better, without fully realising its academic potential. For some projects, a small adjustment could unlock huge academic value.
For example, think of trying to answer the donor or policy question “How much money should I allocate to x vs. y?”. I believe that is usually a problem-solving question, even if no-one has tried to answer it before. A more academic question may be “Under what conditions is [general case of x]’s impact potential dominated by [general case of y]’s impact potential?” Then, after making your academic contribution, you can also throw in your x vs. y calculation, as an example, or policy implication.
Making impact researchful
I’m an economics PhD student. I’ve spent some time thinking about a) how to do good and b) how to succeed in academia.
The holy grail is a project that does good and results in a paper publishable in a peer reviewed journal. But I have struggled with this and I’ve noticed a few other EAs in early stages of academia doing so too.
I’ve come to think the reason is that we are problem-solvers. We want to change people’s lives for the better. When we try to think of a research project, we think about the problems with the world, and how to fix them.
What makes a good academic research paper is fundamentally different. I am far from being an experienced academic, but I understand that research is about pushing forward the frontier of knowledge and understanding. Examples are finding a better way to explain observed phenomena, measuring something previously unmeasured, documenting a previously undocumented connection or relationship, inventing a new technique or using an old technique in a new way, or showing that supposedly separate things are just different examples of a general case.
It’s tempting to say “research is solving the problem of not understanding” or “problem solving is increasing your understanding of how to solve the problem”. But that shoe-horning only de-emphasises their considerable differences. I would rather think of them as two different stages of a process. Research creates the knowledge, and problem-solving applies the knowledge.
A trap for EAs in early-stage academia is to do work that makes the world better, without fully realising its academic potential. For some projects, a small adjustment could unlock huge academic value.
For example, think of trying to answer the donor or policy question “How much money should I allocate to x vs. y?”. I believe that is usually a problem-solving question, even if no-one has tried to answer it before. A more academic question may be “Under what conditions is [general case of x]’s impact potential dominated by [general case of y]’s impact potential?” Then, after making your academic contribution, you can also throw in your x vs. y calculation, as an example, or policy implication.
Thoughts?