TLDR: I’ve collected some tips for research that I’ve given to other people and/or used myself, which have sped things up and helped put people in the right general mindset for empirical AI alignment research. Some of these are opinionated takes, also around what has helped me. Researchers can be successful in different ways, but I still stand by the tips here as a reasonable default.

What success generally looks like

Here, I’ve included specific criteria that strong collaborators of mine tend to meet, with rough weightings on the importance, as a rough north star for people who collaborate with me (especially if you’re new to research). These criteria are for the specific kind of research I do (highly experimental LLM alignment research, excluding interpretability); some examples of research areas where this applies are e.g. scalable oversight, adversarial robustness, chain-of-thought faithfulness, process-based oversight, and model organisms of misalignment. The exact weighting will also vary heavily depending on what role you’re serving on the team/project. E.g., I’d probably upweight criteria where you’re differentially strong or differentially contributing on the team, since I generally guide people towards working on things that line up with their skills. For more junior collaborators (e.g., first time doing a research project, where I’ve scoped out the project), this means I generally weigh execution-focused criteria more than direction-setting criteria (since here I’m often the person doing the direction setting). Also, some of the criteria as outlined below are a really high bar, and e.g. I only recently started to meet them myself after 5 years of doing research and/or I don’t meet other criteria myself. This is mainly written to be a north star for targets to aim for. That said, I think most people can get to a good-to-great spot on these criteria with 6-18 months of trying, and I don’t currently think that many of these criteria are particularly talent/brains bottlenecked vs. just doing a lot of deliberate practice and working to get better on these criteria (I was actively bad at some of the criteria below like implementation speed even ~6 months into me doing research, but improved a lot since then with practice). With that context, here are the rough success criteria I’d outline:

[70%] Getting ideas to work quickly
- [45%] Implementat

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