Summary

When should funders wanting to increase the probability of AGI going well spend their money? We have created a tool to calculate the optimal spending schedule and tentatively conclude that funders collectively should be spending at least 5% of their capital each year on AI risk interventions and in some cases up to 35%, depending on views about AGI timelines and other key variables.

This is likely higher than the current AI risk community spending rate which we estimate to be at most 3%^[1]. In most cases, we find that the optimal spending schedule is between 5% and 15% better than the ‘default’ strategy of just spending the interest one accrues and generally between 5% to 35% better than a naive projection of the community’s current spending rate^[2].

We strongly encourage users to put their own inputs into the tool to draw their own conclusions.

The key finding of a higher spending rate is supported by two distinct models we have created, one that splits spending of capital into research and influence, and a second model (the ‘alternate model’) that supposes we can spend our stock of things that grow on direct work. We focus on the former with the latter described in the appendix since its output is more obviously action-guiding^[3].

The table below shows our best guess for the optimal spending schedule using the former model when varying the difficulty of achieving a good AGI outcome and AGI timelines. We keep other inputs, such as diminishing returns to spending and interest rate constant.^[4]

How much better the optimal spending schedule is compared to the 2%+2% constant spending schedule (within-model lower bound)^[12]
	Median AGI
	2030	2040	2050
Easy	37.6%	18.4%	11.8%
Medium	39.3%	14.9%	12.0%
Hard	12.3%	5.85%	1.55%

Some of the critical limitations of our model include: poorly modelling exogenous research, which is particularly important for those with longer timelines, and many parts of the model - such as diminishing returns - remaining constant over time.

Further, we find that robust spending strategies - those that work in a wide variety of worlds - also support a higher spending rate. We show the results of a Monte Carlo simulation in the appendix.^[13]

Introduction

Humanity might be living at a hinge moment in history (MacAskill, 2020)....

Consequences of AI timelines

Further reading