Here's what seem like priorities to me after listening to the recent Dwarkesh podcast featuring Daniel Kokotajlo:
1. Developing the safer AI tech (in contrast to modern generative AI) so that frontier labs have an alternative technology to switch to, so that it is lower cost for them to start taking warning signs of misalignment of their current tech tree seriously. There are several possible routes here, ranging from small tweaks to modern generative AI, to scaling up infrabayesianism (existing theory, totally groundbreaking implementation) to starting totally from scratch (inventing a new theory). Of course we should be working on all routes, but prioritization depends in part on timelines.
2. De-agentify the current paradigm or the new paradigm:
With AI assistance, the degree to which an alternative is ready-to-go can differ a lot compared to its prior human-developed state. Also, an idea that's ready-to-go is not yet an edifice of theory and software that's ready-to-go in replacing 5e28 FLOPs transformer models, so some level of AI assistance is still necessary with 2 year timelines. (I'm not necessarily arguing that 2 year timelines are correct, but it's the kind of assumption that my argument should survive.)
The critical period includes the time when humans are still in effective control of the... (read more)