For context, I have happened to find myself in the highly fortunate situation of being relatively young (late-twenties) and having met my financial retirement goals. I have always held a fascination with cognitive science and want to now orient my life to participation within said field in alignment with some of my other interests, particularly the cognitive processes underlying altered states of consciousness (psychedelics, flow, religious ecstasy). After much thought, I've been able to see that a personal skill I've developed is in being able to synthesize existing information and communicate it to others in a way that is easy to understand and I would like to approach my academic pursuit from this angle instead of being involved in the actual academic lab work. I am still relatively naive to the workings and structure of academia but am trying to find a place within the field where I can combine my interests and skills to meaningfully contribute to the field of study as a whole. My fear is that this would limit me to largely commentary and synthesis of existing information and that it would label me as less credible because I am not actually involved in the work of producing scientific literature itself. 

My question is less oriented around Cognitive Science as a field of study specifically but in regards to academic fields of study as a whole. Do I need to have a Ph.D. in order to write books and articles that summarize existing literature, postulate potential avenues of research, and theorize within the field of cog sci? I currently have my bachelors in cloud computing but would any other degree of education work such as an MSc.? I have the resources and time to acquire these if necessary but I am just trying to see the best return on my time investment if I don't necessarily desire to publish academic research.  

Thank you. 

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I wrote a couple posts (that I haven't reviewed recently) on this topic. You may find them informative, or at least amusing. Insightful points were made by commenters.

Was a terminal degree necessary for inventing Boyle's desiderata?

Was a PhD necessary to solve outstanding math problems?

I will review these. Thank you for your input! 

On reading them back over, here's my updated take (partly informed by the fact that I am now an MS student and work with PhD students daily): A PhD is two things: a way to support research, and a way to reward it with a sheepskin. Budding researchers just tend to see academia as a marginally more useful and attractive place to build their career than the next best alternative. The fact that a PhD program is mostly the only way to get the most widely recognized signal of being a qualified researcher is a bonus. If they're going to do weird groundbreaking research anyway, why not do it in an environment that's relatively open to it, and that will provide them with a credential at the end of the process? If I was doing this over again, then, I might reframe the question. Instead of asking "is a PhD necessary," I might ask questions like: * "Why do excellent early-career researchers so often see a PhD as attractive?" * "What are some of the practical barriers to doing a certain type of research outside the academic system?" * "What is the next most logical alternative to building a research career without getting a PhD?" * "Why and how do some excellent early-career researchers choose to build their research career outside the normal academic system?" * "What exactly does it mean to 'contribute' to a field?" As an example, if you're going into cogsci, you might need to run experiments on people or animals. When we do animal research in our BME lab, we have all kinds of support and regulation and procedures for making sure it doesn't create a fiasco with government, administrators, or activists. Outside the academic system, I expect that trying to do animal research would be extremely difficult or impossible, not to mention publishing it and getting it taken seriously. It's not just a question of whether the research findings were any good. It's the perception. Academia is as sensitive to perception as anybody, and you want your research to not just be ethical

Derek M. Jones


To reach the boundary of what is known in your chosen field will require reading lots of papers, which will take (at least) several years.  Doing research will also require implicit knowledge that is part of the field, but does not appear in papers.

Are you the kind of person who can spend several years reading papers without significant external help?

Where are you going to acquire the implicit knowledge, e.g., how to run experiments?

PhD students are the work-horses of academic research, and don't have the power/money/experience to do anything other than tow the line.  You have a degree of independence and experience that will deter many academics taking you on as a student.

Perhaps you can find an independent scientist to take you on as an apprentice.

Or: You could kick-start your research by applying your existing knowledge of (I assume) computing/software to cognitive issues in this field (see chapter 2



No. Have actually been working in/on science communication about psychedelics (as medicines) and have received both positive feedback from researchers and am collaborating with a few.

One thing that I like about being parallel to academia is that you can build things outside of the constraints. For instance am building a tracker of all RCTs which will update automatically when new papers are added. And made a map of research that visually shows where what is taking place.

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If it's high-quality distillation you're interested in, you don't necessarily need a PhD. I'm thinking of e.g. David Roodman, now a senior advisor at Open Philanthropy. He majored in math, then did a year-long independent study in economics and public policy, and has basically been self-taught ever since. Holden Karnofsky considers what he does extremely valuable:

David Roodman, who is basically the person that I consider the gold standard of a critical evidence reviewer, someone who can really dig on a complicated literature and come up with the answers, he did what, I think, was a really wonderful and really fascinating paper, which is up on our website, where he looked for all the studies on the relationship between incarceration and crime, and what happens if you cut incarceration, do you expect crime to rise, to fall, to stay the same? He picked them apart. What happened is he found a lot of the best, most prestigious studies and about half of them, he found fatal flaws in when he just tried to replicate them or redo their conclusions.

When he put it all together, he ended up with a different conclusion from what you would get if you just read the abstracts. It was a completely novel piece of work that reviewed this whole evidence base at a level of thoroughness that had never been done before, came out with a conclusion that was different from what you naively would have thought, which concluded his best estimate is that, at current margins, we could cut incarceration and there would be no expected impact on crime. He did all that. Then, he started submitting it to journals. It’s gotten rejected from a large number of journals by now. I mean starting with the most prestigious ones and then going to the less.

Robert Wiblin: Why is that?

Holden Karnofsky: Because his paper, it’s really, I think, it’s incredibly well done. It’s incredibly important, but there’s nothing in some sense, in some kind of academic taste sense, there’s nothing new in there. He took a bunch of studies. He redid them. He found that they broke. He found new issues with them, and he found new conclusions. From a policy maker or philanthropist perspective, all very interesting stuff, but did we really find a new method for asserting causality? Did we really find a new insight about how the mind of a …

Robert Wiblin: Criminal.

Holden Karnofsky: A perpetrator works. No. We didn’t advance the frontiers of knowledge. We pulled together a bunch of knowledge that we already had, and we synthesized it. I think that’s a common theme is that, I think, our academic institutions were set up a while ago. They were set up at a time when it seemed like the most valuable thing to do was just to search for the next big insight.

These days, they’ve been around for a while. We’ve got a lot of insights. We’ve got a lot of insights sitting around. We’ve got a lot of studies. I think a lot of the times what we need to do is take the information that’s already available, take the studies that already exist, and synthesize them critically and say, “What does this mean for what we should do? Where we should give money, what policy should be.”

I don’t think there’s any home in academia to do that. I think that creates a lot of the gaps. This also applies to AI timelines where it’s like there’s nothing particularly innovative, groundbreaking, knowledge frontier advancing, creative, clever about just … It’s a question that matters. When can we expect transformative AI and with what probability? It matters, but it’s not a work of frontier advancing intellectual creativity to try to answer it.

I have no idea about cognitive science in particular, but in math and physics there is not a single worthwhile contribution that was not done either by PhD holders or PhD students. Just not a thing that happens.

Edit for pedants: in the last 50 years at least.

Edit2: one possible exception is that anonymous 4chan poster: