Financial Costs of an AI Pause?

I’ve analyzed the near-term economic effects of an AI pause, out of concern for my investments, and a desire to predict how strong political opposition to a pause is likely to be. My median estimates: The S&P 500 will drop 27.8%. AI subsectors will drop 34-69%. Interest rates will rise at a much slower rate than would be the case without a pause. The specific numbers depend on some fairly arbitrary assumptions. So please read this post in order to get a feel for how the results depend on the assumptions. I’ve tried to keep the assumptions reasonable, but some of them will prove to be wrong. My most controversial assumptions reflect an expectation that both markets and voters will be surprised at how powerful AI is, mainly in 2027. For the full model, along with many explanatory comments, see the Python source code here (zip file) . This conversation with Claude clarifies my reasoning in more detail than most people will want. Sensitivity to Assumptions Here’s how my model says the impact is influenced by changes in assumptions. Numbers are for the immediate change in the S&P500 and in the stocks of hyperscalers (Microsoft, Google/Alphabet, Amazon, Meta, and Oracle). AI economic centrality low (0.4) medium (0.7) high (0.95) SP500 -22.5% -27.8% -31.8% Hyper -26.8% -34.1% -40.4% How central is AI to economic growth? Low means AI is one technology among several. High means AI is the dominant driver of growth, and interest rates are pushed up by massive AI-related capital demand. training dependence low (0.25) medium (0.5) high (0.8) SP500 -22.2% -27.8% -31.2% Hyper -26.3% -34.1% -38.9% How much of AI’s near-term economic value requires new frontier training runs? Low means most value comes from deploying and refining existing models. High means the next major value unlocks require fundamentally new capabilities. S&P 500 immediate impact: AI centrality × training dependence Train: low Train: medium Train: high Central: low SP500 -18.9% -22.5% -25.0% Central: medium SP500 -22.2% -27.8% -31.2% Central: high SP500 -24.6% -31.8% -35.9% post pause cognitive improvement weak moderate aggressive SP500 -24.5% -27.8% -30.3% Hyper -29.5% -34.1% -37.7% I’m predicting that at the end of the pause, AI training would resume with some moderate regulation. This variable captures how much progress to expect compared to a no-regulation scenario. I’m using 75%, 50%, and 30% of unregulated progress for the weak, moderate, and aggressive post-pause regulations respectively. compute growth rate 40% 63%->40% 80% SP500 -24.1% -27.8% -30.8% Hyper -29% -34.1% -38.4% This variable describes the hardware constraints on AI growth. It represents how fast the available compute would increase given unlimited demand. The middle column assumes that growth gradually slows between 2028 and 2040 from 63% to 40%. pause duration 1 year 2 years 4 years SP500 -27.5% -27.8% -29.6% Hyper -33.7% -34.1% -36.7% task density low moderate high SP500 -27.1% -27.8% -28.4% Hyper -33.2% -34.1% -34.9% High task density means there’s still plenty of low-hanging fruit, and we haven’t yet reached the steepest part of the S-curve. Low task density means we’re using up the low-hanging fruit, and we’ve passed the steepest part of the S-curve. What Kind of Pause? I assume that governments decide in late 2027 to treat AI as slightly more dangerous than nuclear weapons, due to some combination of job displacement, and accidents that are more concerning than the one depicted in the movie 2001: A Space Odyssey . I focus on a scenario where an international agency enforces drastic limits to AI development for two years, starting at the beginning of 2028. During 2028 there is an expectation that significant AI development will resume in 2030. I will focus my analysis on the economic effects during 2028, and assume that actors during 2028 will only have rough guesses as to how fast development will be allowed to proceed in 2030. I will assume that their mean forecast involves some sort of resumption of progress, but little confidence in full-speed development being allowed in 2030. The pause will restrict all datacenters more powerful than a certain threshold, roughly corresponding to the level of the best AI which was released in 2026. The details of the pause will depend somewhat on insights that won’t become available until we know more about how AI is progressing in 2027. Instead of predicting what the pause will apply to or how it will be enforced, I’ll predict that it will be effective enough to slow AI capability progress by a factor of 5 compared to what it would be in the absence of regulation. Since regulation will be imperfect at distinguishing between harmless research and the research it intends to pause, I’ll estimate it causes a 15% slowdown in other high performance computing. Impact I assume the initial effect of the pause will be a 90% reduction in spending to train AI. That effect will be somewhat offset by lower prices on that compute stimulating increased demand for inference. I assume that GDP growth rates under a no-pause scenario would gradually rise to 30% by 2040. This is more a reflection on what markets would predict in 2028 than a genuine estimate of what I expect would happen with no regulation. I see a fair amount of room for higher growth rates . I predict interest rates in 2029 of roughly 7% with a pause, compared to 11% without any AI regulation. I predict that robotics progress will continue to have roughly the same increases in economic impact that it would have had without regulation. I’m moderately confident that AI already has nearly enough general intelligence for robotics to have transformative impacts on the economy, and that the remaining engineering that is required is ordinary enough to only be slowed down a little by the pause. That slowdown will be offset by the pause reducing the extent to which AI training competes with robotics for resources. I’m assuming that financial markets are mostly rational, and will adjust price/earnings ratios mainly in reaction to predicted growth rates and interest rates. I assume markets will briefly over-react to a pause due to increased risk aversion and margin calls. I assume that pre-pause market levels would not be considered to be bubble-like under a no-pause scenario. Here’s a more detailed set of predictions for the median set of my model’s assumptions: Model Output: Executive Summary Pause period: 2028–2030 Post-pause cognitive improvement: 50% of unrestricted rate Model horizon: 2040 Net present value of foregone AI revenue: $ 111.93T Implied AI sector market cap loss: $ 839.51T S&P 500 immediate impact: -27.8% S&P 500 after one year: -17.6% Immediate market cap change: $ -20.02T One-year market cap change: $ -12.69T AI High-Growth Segment Revenue Trajectory Year | No Pause Growth | With Pause Growth | Diff -------------------------------------------------------------------------------------- 2025 | $ 350B 63.0% | $ 350B 63.0% | $ 0B 2026 | $ 570B 63.0% | $ 570B 63.0% | $ 0B 2027 | $ 930B 63.0% | $ 930B 63.0% | $ 0B 2028 | $ 1.52T 63.0% | $ 911B -2.0% | $ 604B << PAUSE 2029 | $ 2.43T 60.5% | $ 1.22T 33.4% | $ 1.22T 2030 | $ 3.84T 58.0% | $ 1.67T 37.7% | $ 2.17T 2031 | $ 6.01T 56.4% | $ 2.29T 36.7% | $ 3.72T 2032 | $ 9.31T 54.8% | $ 3.10T 35.6% | $ 6.20T 2033 | $ 14.26T 53.2% | $ 4.18T 34.6% | $ 10.08T 2034 | $ 21.61T 51.6% | $ 5.58T 33.5% | $ 16.04T 2035 | $ 32.42T 50.0% | $ 7.39T 32.5% | $ 25.03T 2036 | $ 47.98T 48.0% | $ 9.69T 31.2% | $ 38.29T 2037 | $ 70.05T 46.0% | $ 12.59T 29.9% | $ 57.46T 2038 | $ 100.88T 44.0% | $ 16.19T 28.6% | $ 84.69T 2039 | $ 143.25T 42.0% | $ 20.61T 27.3% | $ 122.63T 2040 | $ 200.55T 40.0% | $ 25.97T 26.0% | $ 174.57T Sector Market Cap Impacts Sector | Pre-Pause | Immediate % | After 1yr % ---------------------------------------------------------------------------------- Semiconductors | $ 8.00T | $ -4.50T -56.2% | $ -3.96T -49.5% Hyperscalers | $ 22.00T | $ -7.51T -34.1% | $ -5.23T -23.8% Frontier Labs | $ 3.00T | $ -2.07T -68.9% | $ -1.92T -63.9% Ai Applications | $ 4.00T | $ -1.74T -43.6% | $ -1.36T -34.1% Non Ai Sp500 | $ 35.00T | $ -4.20T -12.0% | $ -215B -0.6% ---------------------------------------------------------------------------------- TOTAL (S&P 500) | $ 72.00T | $ -20.02T -27.8% | $ -12.69T -17.6% Implications Political pressure for AI regulation is building as increasingly impressive evidence of AI capabilities erodes peoples’ ability to dismiss AI as hype. I expect this to lead to a serious debate among politicians in 2027 about AI regulation. I’m unable to predict what kind of regulation that will produce. So I’ve focused on scenarios that would matter the most if they’re adopted. The economic impact of a moderately effective pause would be big enough to create medium-sized political pressures to weaken the pause. There will be significant pressure for a strong pause due to voter concerns about job losses. There will be hard-to-predict pressures from national security professionals related to military risks. My crystal ball refuses to tell me how these pressures will play out. I see a very real chance that a debate over a pause will impact AI stocks within a year from now. This effect is worrying enough to get me to take some profits in my AI stocks, at a rate of 1% to 2% per week given recent trading patterns. I consider a pause to be more likely than do most people. Here are some Manifold markets that I’ve been modestly bidding up: Conditional on humanity surviving to 2035, will a global AI pause have been enacted? Will there be a global pause on the largest AI training runs at any point before AGI? [Carlini questions] 6+ month pause on AI development Will an international pause on large AI training runs be in effect on Jan 1, 2028? Discuss