I have been doing independent research in addition to my Ph.D. for roughly a year now. For the next 6 months, I’ll take a break from my Ph.D. and plan to do AI safety research full-time. I had chats with many people about independent research in the past, e.g. on EAGs or because 80K has connected me with people thinking about pursuing independent research. I had some great experiences with independent research but not everyone does. I think the variance for independent research is large and I'm worried that people get disheartened by bad experiences. So here are some considerations in which situations independent research might be a good idea and some tips that will hopefully improve your experience.
I’d like to thank Magdalena Wache and Tilman Räuker for their feedback.
TL;DR: At first glance, there is a bit of a paradoxical nature to independent research. If someone wants to pursue independent research they need a research agenda to work on. If they are able to construct a good research agenda, an existing institution often has incentives to hire them. On the flip side, if their research skills are not developed enough to be hired by an existing institution, their independent research might not be very successful. Thus, naively it would seem that there are few cases in which independent research makes sense. However, I think that there are many situations in which independent research or independent upskilling are a great option, e.g. when no established organization is working on the topic you find most promising, as a way to upskill for a job, to gain new research skills or to transition between jobs. Some tips for independent researchers include: getting feedback early on, aiming to collaborate with others and creating accountability mechanisms for yourself such as publishing your results. My most important advice for independent researchers is that you should probably be much more active than in other roles because there is less default structure and more responsibility on you.
I’ll mostly talk about AI safety research but many of these things probably also apply to other independent research.
Independent research is often presented as one of three default options for people seeking to do EA research, e.g. in AI safety:
Doing independent research well requires a multitude of skills. The independent researcher needs to be able to set their own agenda, they require some basic research skills, self-discipline and some way of evaluating and correcting their own research. These are skills that usually don’t come naturally but need to be learned and refined. In most standard career paths, e.g. within a Ph.D. or in an industry research team people have mentors who help them and ensure that they actually learn these skills. By default, independent research does not ensure that these skills are actually acquired.
The perceived paradox is now that if someone has the skills required to do high-quality independent research, existing institutions often want to hire them. If they don’t have these skills yet, the research they will produce independently is unlikely to be of high quality or conducted efficiently (unless they have mentorship or are especially talented). Thus, naively, it seems like there aren’t that many situations in which independent research makes sense.
However, I think there are many cases in which independent research makes a lot of sense and there there are a lot of tips that can improve it. As with all things, independent research obviously has its trade-offs.
I think the most important question that someone who thinks about doing independent research should ask themselves is whether they want to do independent research or upskilling (and how much of each). The goal of independent research is to produce a research result, e.g. increasing or refining the pool of existing knowledge. The goal of upskilling, on the other hand, is to increase your skills and knowledge. It doesn’t have the aim of finding anything new. You could also draw the distinction between “independent research with the main goal of producing impactful results” and “independent research with the main goal of becoming good at research (or other skills such as research engineering)”. Research and upskilling obviously correlate a bit but I think it’s really helpful to
To give a better sense of when independent research makes sense, I think the following situations are plausible candidates:
While the above points are primarily about independent research, I want to emphasize again that upskilling is sometimes the better path depending on your career goals. In that case, I would probably work through Jacob Hilton’s or Gabriel Mukobi’s curriculum on my own or with collaborators.
I think independent research is a very high-variance path, i.e. because it has so little structure and oversight, some people excel at it while others get nearly nothing out of it. Furthermore, the “default” path for independent research is probably relatively far away from fulfilling its full potential because good execution requires much more active effort than alternative paths.
I guess, this default path roughly looks like this: “Someone is excited about alignment and wants to contribute. They come up with a research idea and write a proposal to a funder. The proposal is plausible to someone with general knowledge about alignment and the grant gets approved. The researcher starts with their project and makes some initial progress. However, they also hit some unexpected roadblocks. After a while, the roadblocks turn out to be more substantial than initially expected and they reduce the scope of their project to get around them. The smaller scope of the project is still too ambitious and they carve out a small subquestion of their original proposal and do some research on that. They make progress but the grant is nearing its end so they write up their unfinished project and publish it. They get some positive feedback for the effort and preliminary findings but feel personally dissatisfied with how the project went. They then move on to do other things.”
I don’t want to criticize people who have roughly followed this path during their independent research but I think we can agree that there are a lot of things that could have gone better here. One of the reasons why I expect some version of this to be the default path rather than the more optimal version is that people are unaware of the paths they could take or at least don’t think that these paths are open to them. This is because most of the things that improve your independent research require an active effort by you, e.g. YOU have to reach out to another researcher, YOU have to make a plan for yourself, YOU have to create your own accountability mechanism and YOU have to expose your own ideas to get feedback. All of this can feel scary, especially when you aren’t (or at least don’t feel like) an established member of the community but I think it is crucial for the success of your project.
Some tips to increase the probability of success for your independent research efforts include:
I think independent research serves an important role in the EA and AI safety landscape but it comes with up- and downsides. Concretely, I’m worried that independent research becomes the one-size-fits-all solution when the capacity of established EA institutions is too low. I think there is a risk that doing independent research, if executed suboptimally, could waste a lot of talent (due to opportunity costs), or disheartened independent researchers will not want to continue contributing to EA/AI safety if they had a bad experience.
My personal experience with independent research was great and I want other people to get the most out of it. I hope my thoughts on independent research are helpful. Feedback and disagreement are appreciated.
I was an independent AGI safety researcher because I didn't want to move to a different city and (at the time, it might or might not have changed in the past couple years) few if any orgs that might hire me were willing to hire remote workers.