"returns that can later be deployed to greater altruistic effect as AI research progresses"

This is hiding an important premise, which is that you'll actually be able to deploy those increased resources well enough to make up for the opportunities you forego now. E.g. Paul thinks that (as an operationalisation of slow takeoff) the economy will double in 4 years before the first 1 year doubling period starts. So after that 4 year period you might end up with twice as much money but only 1 or 2 years to spend it on AI safety.

I like the general idea that AI timelines matter for all altruists, but I really don't think it's a good idea to try to "beat the market" like this. The current price of these companies is already determined by cutthroat competition between hyper-informed investors. If Warren Buffett or Goldman Sachs thinks the market is undervaluing these AI companies, then they'll spend billions bidding up the stock price until they're no longer undervalued.

Thinking that Google and Co are going to outperform the S&P500 over the next few decades might not sound like a super bold belief--but it should. It assumes that you're capable of making better predictions than the aggregate stock market. Don't bet on beating markets.

The same neglect that potentially makes AI investments a good deal can also make AI philanthropy a better deal. If there is a huge AI boom, a prescient investment in AI companies might leave you with a larger share of the world economy---but you'll probably still be a much smaller share of total dollars directed at influencing AI.

That said, I do think this is a reasonable default thing to do with dollars if you are interested in the long term but unimpressed with the current menu of long-termist philanthropy (or expect to be better-informed in the future).

There are three additional premises required here. The first is that your own use of funds from investments must be significantly better than that of of other shareholders of the companies you invest in. The second is that the growth rate of the companies you invest in must exceed the rate at which the marginal cost of doing good increases, due to low-hanging fruit getting picked and due to lost opportunities for compounding. The third is that the growth potential of AI companies isn't already priced in, in a way that reduces your expected returns to be no better than index funds.

The first of these premises is probably true. The second is probably false. The third is definitely false.

When planning how to donate, it seems very important to consider the impact of market returns increasing due to progress in AI. But I think more considerations should be taken into account before drawing the conclusion in the OP.

For each specific cause, we should estimate the curve over time of EV-per-additional-dollar-invested-in-2019-and-used-now (given an estimate of market returns over time). As Richard pointed out, for reducing AI x-risk, it is not obvious we will have time to effectively use the money we invest today if we wait for too long (so "the curve" for AI safety might be sharply decreasing).

Here is another consideration I find relevant for AI x-risk: in slow takeoff worlds more people are likely to become worried about x-risk from AI (e.g. after they see that the economy has doubled in the past 4 years and that lots of weird things are happening). In such worlds, it might be the case that a very small fraction of the money that will be allocated for reducing AI x-risk would be donated by people who are currently worried about AI x-risk. This consideration might make us increase the weight of fast takeoff worlds.

On the other hand, maybe in slow takeoff worlds there is generally a lot more that could be done for reducing x-risk from AI (especially if slow takeoff correlates with longer timelines), which suggests we increase the weight of slow takeoff worlds.

If you think a fast takeoff is more likely, it probably makes more sense to either invest your current capital in tooling up as an AI alignment researcher, or to donate now to your favorite AI alignment organization (Larks' 2018 review (a) is a good starting point here).

I just wanted to note that some of the research directions for reducing AI x-risk, including ones that seem relevant in fast takeoff worlds, are outside of the technical AI alignment field (for example, governance/policy/strategy research).

February 2021 update:  I now think holding these ETFs, Tesla, and stock in the companies discussed in the post is a good way to quickly approximate the optimal AGI-bull-case portfolio.

(This isn't financial advice.)