Here are 10 of helpful pieces of advice I received in 2022:

  1. Understand things for yourself. Figure out what you actually think about this AI stuff. What do you think will happen? What concrete risks and scenarios are you worried about? (Credit to Oliver Habryka. Last year at a winter break retreat in Berkeley, he asked me to explain how I thought AI would lead to an existential catastrophe. I had a weak answer at the time, which motivated me to improve.
  2. Write about “big if true” opinions. One of the biggest mistakes junior researchers make is that they try to be too neutral. Be opinionated instead. Find something that you think other people are wrong about, and then write up why you think they’re wrong. Be open to changing your mind, but be OK with starting off by saying “let me see if I can defend this thing that I think I believe.” (Credit to Ajeya Cotra. Note thought that the version presented here has gone through an “Akash filter” and may only partially reflect Ajeya’s model.)
  3. Write concrete scenarios about your worldview. Write about what you think the world will look like, and be concrete. (Credit to Daniel Kokotajlo and what 2026 looks like.)
  4. Write about harder topics that force you to learn. Write about topics that push you to think more. Write about things that feel less like “teaching/explaining things that you already know” and more “learning things and getting less confused about things you don’t yet understand.” (Credit to Olivia Jimenez. I think earlier in the year, my posts were more like “reflections from EAG”, and these days I’m thinking more about how the community should allocate technical talent and what I think about the OpenAI alignment plan. I expect to be wrong more often and learn more rapidly.)
  5. Think about macrostrategy. (Credit to Thomas Larsen, who initiated a shift in the kind of work I’m prioritizing. I now identify less as an “AIS field-builder” and more as “someone who’s trying to become less confused about AI risk, AI governance, and AI macrostrategy.”)
  6. Think regularly about who you could learn from; message them. I think this strategy is overpowered and underutilized. I think it’s one of the few malleable things that can >3X the rate at which people learn & find opportunities. Obvious caveat that you shouldn’t expect anyone to respond & you should respect boundaries. But there are actually a lot of smart/competent people in the community who can (and want to) help. (Credit to Olivia Jimenez & various SERI-MATS mentors who I interviewed.)
  7. Think carefully about personal and professional boundaries. I was surprised at how quickly my personal/professional networks ended up overlapping, and I was surprised at how quickly I started to notice power dynamics. Apparently, it’s not uncommon for people to be like “wait what? I’m new and confused about so much-- why are people taking me seriously, or deferring to me, or thinking about how our social interactions will affect their professional life?” (Credit to Aris Richardson and various other friends).
  8. Focus on finding amazing teammates/allies. I think it’s common for people to think “what should I work on?” and less common for people to think “who should I work with?” At least for me, the latter is extremely important. 
  9. Take fewer (and shorter) meetings. Most things don’t need to be a meeting. Most 60-min meetings can be 30-min meetings, and most 30-min meetings can be “can you please send me a google doc that describes how you’ve been thinking about X?” The “if someone who I don’t know asks for a meeting, ask them for a Google doc before agreeing to meet with them” method has been great. (Credit to Olivia Jimenez.)
  10. Slow is smooth, and smooth is fast. Many things can be done 5-10X faster. Some things can’t. Apparently, surgeons have a phrase: “slow is smooth, and smooth is fast.” Notice when you’re doing something that shouldn’t be 80-20ed, and be willing to slow down. Areas where I think the “smooth and slow” approach are especially helpful: Interpersonal conflicts, mental health interventions, learning about a new topic, conflicts between different parts of the self (see IDC), and getting “unstuck” when doing research. (Credit to Everett Smith.)

Disclaimer: It’s plausible that the people I “credit” would find my summaries inaccurate or no longer endorse the advice.

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Items 1 through 4 rhyme with the advice in the Learning By Writing post on Cold Takes, which I found quite inspiring (emphasis in the original):

[During this process I am] trying to “always have a hypothesis” and re-articulating it whenever it changes. By doing this, I try to continually focus my reading on the goal of forming a bottom-line view, rather than just “gathering information.” I think this makes my investigations more focused and directed, and the results easier to retain. I consider this approach to be probably the single biggest difference-maker between "reading a ton about lots of things, but retaining little" and "efficiently developing a set of views on key topics and retaining the reasoning behind them."

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