As Agnes mentioned, we (the Centre for Effective Altruism) are looking to hire a Product Lead for the Opportunities Board. The role listing is now live here. 

The board is now shifting from initial discovery into validating and scaling the model. We have evidence of demand, healthy engagement, and a plausible path to cost-effective impact at scale. What is needed now is a capable operator to own the board, grow it, and chase the ceiling of just how much impact this can generate.

If you're excited about the potential of the board, I encourage you to have a look at the role and consider applying!

I hadn't read footnote 3! And I agree that the 2nd list looks less important from a solely longtermist perspective. (They may still be reasons that AI safety ends up doing significant harm though; I hadn't realised you were taking a 'strong longtermist' stance in the post.)

Future life may turn out to be net negative (e.g. s-risks might become real), and work that preserves the chances of humanity spreading may essentially be enabling that.

In almost the opposite direction, AI might just be very useful and beneficial and a bunch of the risks people in AI safety worry about might not end up becoming real, or might be quite easy to overcome. And in the meantime, AI safety work may have:

• Slowed down the rate at which we achieve those things
• Decreased the chance we ever achieve them (e.g. if a pause leads to a ban etc)
• Distracted talent and money from working on more valuable things 

Oh! Without having seen this post I started vibe coding a playable version of the AI2027 scenario a few days after you posted this. It's quite fun, and is ~ready for beta testers. If anyone seeing this would like to play it, comment below or DM me your email and you will be the first person or batch of people other than me to play it. 

To be clear, I made it for fun rather than with an intentional strategy of making it mass marketable but if anyone wanted to take it on and take it that direction I would happily hand over the code etc.

(PS, cool post generally.)

Interesting! What are some examples of "where incoming freshmen are tuned in"? (Maybe it's usually obvious to people at uni these days?)

Thank you for digging into this and sharing your findings! Some of these seem like important insights if they're correct.

On observation 3:

Motivation exists, experience is scarce and takes years. There might be no shortage of junior, motivated, community-adjacent generalists seeking entry. The shortage is at the other end: senior professionals with years of accumulated judgment in operations, management, institutional engagement, communications, or policy who bring skills that cannot be acquired quickly. Several participants suggested that, for most generalist roles, a competent senior professional can get to a working level of AIS context in weeks, whereas it takes years, sometimes decades, to develop the professional judgment, external relationships, and organisational experience that senior roles require.

Seniority is a proxy for what is actually needed: diversity and outside-world fluency...

Several participants named this as an increasingly urgent gap. 

I'm somewhat surprised by this. It'd be good news for me if trye, because I run a career bootcamp that happens to have relatively large numbers of experienced, accomplished professionals seeking to transition into high-impact cause areas, often interested in AI safety, often generalists.

Would you be able to put me in touch with some of the people who expressed this need so we can understand the gap better and see if I can connect them to relevant talented people?

You can email me at [email protected] if easier!

I am currently the only Fund Manager at the EA Infrastructure Fund... and that needs to change!

I work full-time on something else within the Centre for Effective Altruism, and the EAIF needs a dedicated owner who will drive it forwards.

I think we're sitting on a big opportunity here. There's so much that the EA movement could achieve, and so much great work that could be enabled by EAIF.

Some indicators of promise here:

• CEA is growing, but there's only so much that CEA can work on in-house. We need to fund and nurture great work that's happening elsewhere, too!
• There are potential new sources of funding that EAIF could tap into; building a strong product here that donors are excited about is essential.
• We have a mini roadmap laid out by recent successes within EA Funds.

Let me say more on that last one. I've been extremely impressed by what another EA Fund, the Animal Welfare Fund, has achieved over the past year or two, improving it's evaluation quality, it's staffing, and it's available pool of resources. I think the EAIF has the potential for a similar rocketship trajectory; it needs the right person to come in and make that happen.

CEA is hiring for a new Head of the EA Infrastructure Fund: full job description and application form here, apply by 4th May.

Let me know if you have questions! I can't promise deep engagement with all potential candidates, but I'll help out with key/quick uncertainties if I can! Some additional thoughts from Loic, new Head of EA Funds, here.

Oh, nice, I hadn't seen that, thank you! 

Looks more careful/thorough.

Separately, here's Claude's direct reply to your specific points in case you're curious (sorry I don't enough of a developed inside view take to respond myself!):

On "China don't have any frontier labs, only labs which distill other models": this is probably too strong. DeepSeek introduced genuine architectural innovations (Multi-head Latent Attention, fine-grained MoE) that Epoch AI characterises as real advances, not just distillation. That said, the distillation question is genuinely debated: OpenAI has alleged it, and Chinese labs scraped millions of Claude conversations. The picture is mixed rather than one-sided.

On "no evidence of an arms race": both governments explicitly frame AI as a strategic contest (both opted out of the Feb 2026 responsible AI military declaration), there's confirmed espionage (Linwei Ding convicted Jan 2026 for stealing Google TPU secrets), and $2.5B in chip smuggling. Whether this constitutes an "arms race" depends on your definition, but the competitive dynamic Leopold predicted is clearly present.

Your most interesting point is the last one: that distillation and open source might mean an arms race never materialises because intelligence becomes cheap and accessible. This connects directly to what I think is Leopold's most consequential error. He predicted open source would fade and proprietary algorithms would create a durable American moat. Instead, capable AI is diffusing faster than his framework assumed. You're right that this weakens the case that compute concentration equals geopolitical power, and it's a genuinely underexplored implication of how things have played out.

Thanks for reviewing and raising this! You're right that the US/China dynamics are central to Situational Awareness's thesis and we underemphasised them. We've now added a dedicated China/US section with its own tab and three expandable cards, evaluating his specific sub-predictions on infrastructure (7nm chips, power, Middle East), algorithms and open source, and strategic dynamics. Would value your review of the updated version if you have time!