Many creators act as though Youtube's algorithm disfavors content that refers to graphic acts of sex and violence, i.e., bleeping words like 'kill' or 'suicide' or referring to these in very circuitous ways. I would guess these are incomplete methods of avoidance and that YT tries to keep up by detecting these workarounds. Seems like a potential issue for the MechaHitler video. 

@Andy Masley and @Richard Y Chappell🔸 are my top recommendations here

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Good characterization; I should have watched the video. Seems like she may be unwilling to consider that the weird Silicon Valley stuff is correct, but explicitly says she's just raising the question of motivated reasoning.

The "writing scifi with your smart friends" is quite an unfair characterization, but fundamentally on us to counter. I think it will all turn on whether people find AI risk compelling. 

For that, there's always going to be a large constituency scoffing. There's a level at which we should just tolerate that, but we're still at a place where communicating the nature of AI risk work more broadly and more clearly is important on the margin.

I agree there should be a counter narrative. It is also important to realize that people who create, like, and comment on mean-spirited TikToks who are self-absorbed in their own misguided ideology are far enough from the target market that you really shouldn't worry about changing their behavior.

A 10% chance of transformative AI this decade justifies current EA efforts to make AI go well. That includes the opportunity costs of that money not going to other things in the 90% worlds. Spending money on e.g. nuclear disarmament instead of AI also implies harm in the 10% of worlds where TAI was coming. Just calculating the expected vale of each accounts for both of these costs.

It's also important to understand that Hendrycks and Yudkowsky were simply describing/predicting the geopolitical equilibrium that follows from their strategies, not independently advocating for the airstrikes or sabotage. Leopold is a more ambiguous case, but even he says that the race is already the reality, not something he prefers independently. I also think very few "EA" dollars are going to any of these groups/individuals.

My list is very similar to yours. I believe items 1, 2, 3, 4, and 5 have already been achieved to substantial degrees and we continue to see progress in the relevant areas on a quarterly basis. I don't know about the status of 6. 

For clarity on item 1, AI company revenues in 2025 are on track to cover 2024 costs, so on a product basis, AI models are profitable; it's the cost of new models that pull annual figures into the red. I think this will stop being true soon, but that's my speculation, not evidence, so I remain open that scaling will continue to make progress towards AGI, potentially soon. 

Your picture of EA work on AGI preparation is inaccurate to the extent I don't think you made a serious effort to understand the space you're criticizing. Most of the work looks like METR benchmarking, model card/RSP policy (companies should test new models for dangerous capabilities a propose mitigations/make safety cases), mech interp, compute monitoring/export controls research, and trying to test for undesirable behavior in current models. 

Other people do make forecasts that rely on philosophical priors, but those forecasts are extrapolating and responding to the evidence being generated. You're welcome to argue that their priors are wrong or that they're overconfident, but comparing this to preparing for an alien invasion based on Oumuamua is bad faith. We understand the physics of space travel well enough to confidently put a very low prior on alien invasion. One thing basically everyone in the AI debate agrees on is that we do not understand where the limits of progress are as data reflecting continued progress continues to flow.  

I agree there's logical space for something less than less than AGI making the investments rational, but I think the gap between that and full AGI is pretty small. Peculiarity of my own world model though, so not something to bank on. 

My interpretation of the survey responses is selecting "unlikely" when there are also "not sure" and "very unlikely" options suggests substantial probability (i.e. > 10%) on the part of the respondents who say "unlikely," or "don't know." Reasonable uncertainty is all you need to justify work on something so important if-true and the cited survey seems to provide that.