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Thanks for writing a summary of your progress and learnings so far, it’s so useful for the EA community to share its findings.
A few comments:
You might consider making the website more targeted. It seems best suited to undergraduate theses, so it would be useful to focus in on that. For example, it might be valuable to increase the focus on learning. During your degree, building career capital is likely to be the most impactful thing you can do. Although things like building connections can be valuable for career capital, learning useful skills and researching deeply into a topic are the expected goals a thesis and so what most university courses give you the best opportunity to do. Choosing a topic which gives you the best opportunity for learning could mean, for example, thinking about which people in your department you can learn the most from (whether because the best researchers, or because they are likely to be the most conscientious supervisors), and what topic is of interest to them so that they’ll be enthusiastic to work with you on it.
People in academia tend to be sticklers wrt writing style, so it could be worth getting someone to copy edit your main pages for typos.
Coming up with a topic to research is often a very personal process that happens when reading around an area. So it could be useful to have a page linking to recommended EA research / reading lists, to give people an idea of where they could start if they want to read around in areas where ideas are likely to be particularly useful. For example you might link to this list of syllabi and reading lists Pablo compiled.
Thanks for your comment!
I agree. This is one of the inefficiencies of the “list of predefined topics” concept we would like to improve by shifting to Thesis Topic Coaching. The plan is to count in the individual supervisor availability when offering topics. However, I guess that most students’ supervisors won’t be mainly focused on some EA topic so we will have to find a balance between advising to choose a topic which the supervisor is mainly focused on and a degree to which the topic relates to EA causes for each student individually.
You mean reading generally about EA? The value we wanted to add by this project is not to compile general reading lists in which students would have to search themselves, but helping them in the process of choosing a topic individually by directing them toward specific EA sub-topics relevant to their degree, experience and circumstances.
This is a great project! I agree unfunded theses are a huge untapped resource. We were trying to do something similar with our essay contest on global agricultural catastrophes, but it was not very successful. Joshua Pearce and I have dozens of ideas for effective theses, so we will reach out. Minor comment: it is good to spell out the month, because date conventions are different in the US than Europe.
Thanks for this summary. Just on comment: wouldn’t it be useful to have a kind of Effective Thesis prize? It might be convenient for advancing the idea among professors.
(This is the third − 1st in Open Thread #43, 2nd in a facebook comment—and last time I make this suggestion. Sorry if it’s getting boring)
In my opinion it would be definitely worth to try! What’s possibly not clear is that Effective Thesis is to some extent funding constrained, so in present it would need to get some additional sources of funding to run prizes
And prizes wouldn’t have to be super expensive. I mean, graduate students don’t need too much additional incentives to write a good thesis; the main one is to be acknowledged as “Effective Thesis of the year”
I’d contribute to that, especially if the theses were open for reading or download.
(Maybe we could for the right of voting on a thesis in a pre-selection phase. E.g., I’d be willing to pay U$50 to get access to them and vote on my favorite ones. But I haven’t really thought a lot about it)
Forethought just launched one a few hours ago!
This is a fantastic project! I encourage other EA university chapters to share the Effective Thesis website on their social media pages and internal groups 1-2x per year. When you share it on Facebook, make sure to mention the Effective Thesis Facebook page on your post.
This is awesome!
One thing which might be worth emphasizing is comparative advantage. For example, suppose I’m an econ student in a department that’s known for X, Y, and Z. My pool of potential advisors includes some of the world’s leading experts on X, Y, and Z, and I’m well-positioned to apply those ways of thinking to problems of EA interest. So a good strategy might be something like: Identify topics in your field of study (that you find personally interesting, that are currently hot research areas, that your advisor is interested in, etc.), and identify EA topics that you think are important/interesting, then create a 2d grid where you examine intersections of topics in your field/EA topics and see which are fertile.
To take this even further, thesis writers could ask questions like: What is the most beneficial/harmful research that has been done in my field so far from an EA perspective, and how can I do research that is likely to be beneficial and not harmful? If someone was to write a history of my field from an EA perspective, what might it look like? I would be interested to know what the “outside view” says about which research is likely to be beneficial in various fields.
You’ve probably already seen this thread, but if not you should take a look; many of the projects are research projects.
To make maximally good use of researcher time, it might be good to thoroughly familiarize yourself with publicly available info before having conversations. I added a comment to the other thread linking to some more obscure AI safety problem lists that could be useful (in addition to those in the main post).
This thread talks about the value of having a central clearinghouse for EA research, which is something you might aim to do in the long run.
Thanks for the comment!
That’s what we plan to do, with the fact that the grid work will be done by our coaches, who we believe have a comparative advantage in doing this since they have a better overview of EA research landscape and can assess better what students’ opportunities are.
I think this is worth re-considering. I see strong potential for applied projects on specific topics, tied to specific measures and datasets of interest. This might not be the best for people looking to pursue broad ‘theoretical/academic’ research careers. However, it could be very useful as a stepping stone to working at an EA research or impact-driven org.
I had a version of this (list of topics) when I was supervising the undergrad Econ dissertation modules at Essex and Exeter universities. Seemed to work well.
I especially see value in things like cost-effectiveness analysis, shallow reviews of potential high impact interventions/cause areas, fermi/Monte-carlo estimation, forecasting, meta-analysis/synthesis, and data science stuff, including re-analysis of existing data from trials and experiments in movement building, charitable giving, etc.
EA and EA research orgs often have more questions and more data than we have the capacity to handle. And these are often very interesting contexts from an academic and research PoV. Students can work on these, and get some feedback and recognition for their work.
There should be little risk, because if the students’ analysis ends up not being useful, the organization and decisionmakers do not have to use it.
E.g., a case in point (sketch):
High Impact Athletes is interested in modeling the estimated lifetime income over an athlete’s career, as a function of their sport, age, gender, ranking, etc. They would also like to model expected value of atheletes donations, and of their voice/impact on others. (The latter is harder still, but note there is some academic lit on, e.g., the value of celebrity Twitter posts
From experience, I know students are interested in this sort of topic and I suspect there is some research out there already. This could then be part of a larger model (Fermi Montecarlo guesstimate squiggle) of expected donations from athletes who pledge.
Why: this can help them consider which athletes to target more, and how much to emphasize their different theories of change (athlete donations, athletes getting their supporters to donate, etc.)