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Just as the 2022 crypto crash had many downstream effects for effective altruism, so could a future crash in AI stocks have several negative (though hopefully less severe) effects on AI safety.

Why might AI stocks crash?

The most obvious reason AI stocks might crash is that stocks often crash.

Nvidia’s price fell 60% just in 2022, along with other AI companies. It also fell more than 50% in 2020 at the start of the COVID outbreak, and in 2018. So, we should expect there’s a good chance it falls 50% again in the coming years.

 

Screenshot 2024-04-30 at 14.09.29

Nvidia’s implied volatility is about 60%, which means – even assuming efficient markets – it has about a 15% chance of falling more than 50% in a year.

And more speculatively, booms and busts seem more likely for stocks that have gone up a ton, and when new technologies are being introduced.

That’s what we saw with the introduction of the internet and the dot com bubble, as well as with crypto. (I'd love to see more base rate estimates here.)

(Here are two attempts to construct economic models for why. This phenomenon also seems related to the existence of momentum in financial prices, as well as bubbles in general.)

Further, as I argued, current spending on AI chips requires revenues from AI software to reach hundreds of billions within a couple of years, and (at current trends) approach a trillion by 2030. There’s plenty of scope to not hit that trajectory, which could cause a sell off.

Note the question isn’t just whether the current and next generation of AI models are useful (they definitely are), but rather:

  • Are they so useful their value can be measured in the trillions?
  • Do they have a viable business model that lets them capture enough of that value?
  • Will they get there fast enough relative to market expectations?

My own take is that the market is still underpricing the long term impact of AI (which is why I about half my equity exposure is in AI companies, especially chip makers), and I also think it’s quite plausible that AI software will be generating more than a trillion dollars of revenue by 2030.

But it also seems like there’s a good chance that short-term deployment isn’t this fast, and the market gets disappointed on the way. If AI revenues merely failed to double in a year, that could be enough to prompt a sell off.

I think this could happen even if capabilities keep advancing (e.g. maybe because real world deployment is slow), though a slow down in AI capabilities and new “AI winter” would also most likely to cause a crash.

A crash could also be caused by a broader economic recession, rise in interest rates, or anything that causes investors to become more risk-averse – like a crash elsewhere in the market or geopolitical issue.

The end of stock bubbles often have no obvious trigger. At some point, the stock of buyers gets depleted, prices start to move down, and that causes others to sell, and so on.

Why does this matter?

A crash in AI stocks could cause a modest lengthening of AI timelines, by reducing investment capital. For example, startups that aren’t yet generating revenue could find it hard to raise from VCs and fail.

A crash in AI stocks (depending on its cause) might also tell us that market expectations for the near-term deployment of AI have declined.

This means it’s important to take the possibility of a crash into account when forecasting AI, and in particular to be cautious about extrapolating growth rates in investment from the last year or so indefinitely forward.

Perhaps more importantly, just like the 2022 crypto crash, an AI crash could have implications for people working on AI safety.

First, the wealth of many donors to AI safety is pretty correlated with AI stocks. For instance as far as I can tell Good Ventures still has legacy investments in Meta, and others have stakes in Anthropic. (In some cases people are deliberately mission hedging.)

Moreover, if AI stocks crash, it’ll most likely be at a time when other stocks (and especially other speculative investments like crypto) are also falling. Donors might see their capital halve.

That means an AI crash could easily cause a tightening in the funding landscape. This tightening probably wouldn’t be as big as 2023, but may still be noticeable. If you’re running an AI safety org, it’s important to have a plan for this.

Second, an AI crash could cause a shift in public sentiment. People who’ve been loudly sounding caution about AI systems could get branded as alarmists, or people who fell for another “bubble”, and look pretty dumb for a while.

Likewise, it would likely become harder to push through policy change for some years as some of the urgency would drop out of the issue.

I don’t think this response will necessarily be rational – I’m just saying it’s what many people will think. A 50% decline in AI stock prices could maybe lengthen my estimates for when transformative AI will arrive by a couple of years, but it wouldn’t have a huge impact on my all considered view about how many resources should go into AI safety.

Finally, don’t forget about second order effects. A tightening in the funding landscape means projects get cut, which hurts morale. A turn in public sentiment against AI safety slows progress and leads to more media attacks…which also hurts morale. Lower morale leads to further community drama…which leads to more media attacks. And so on. In this way, an economic issue can go on to cause a much wider range of problems.

One saving grace is that these problems will be happening at a time when AI timelines are lengthening, and so hopefully the risks are going down — partially offsetting the damage. (This is the whole idea of mission hedging – have more resources if AI progress is more rapid than expected, and have less otherwise.) However, we could see some of these negative effects without much change in timelines. And either way it could be a difficult experience for those in AI safety, so it's worth being psychologically prepared, and taking cheap steps to become more resilient.

What can we do about this, practically? I’m not sure there’s that much, but being on record that a crash in AI stocks is possible seems helpful. It also makes me want to be more cautious about hyping short term capabilities, since that makes it sound like the case for AI Safety depends on them. If you’re an advocate it could be worth thinking about what you’d do if there were an abrupt shift in public opinion.

It’s easy to get caught up in the sentiment of the day. But sentiment can shift, quickly. And shifts in sentiment can easily turn into real differences in economic reality.

This was originally posted on benjamintodd.substack.com. Subscribe there to get all my new posts.

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the wealth of many donors to AI safety is pretty correlated with AI stocks

Unpopular opinion (at least in EA): it not only looks bad, but it is bad that this is the case. Divest!

AI safety donors investing in AI capabilities companies is like climate change donors investing in oil companies or animal welfare donors investing in factory farming (sounds a bit ridiculous when put like that, right? Regardless of mission hedging arguments).

(It's bad because it creates a conflict of interest!)

"I donate to AI safety and governance" [but not enough to actually damage the bottom lines of the big AI companies I've invested in.]

"Oh, no of course I intend to sell all my AI stock at some point, and donate it all to AI Safety." [Just not yet; it's "up only" at the moment!]

"Yes, my timelines stretch into the 2030s." [Because that's when I anticipate that I'll be rich from my AI investments.]

"I would be in favour of a Pause, if I thought it was possible." [And I could sell my massive amounts of non-publicly-traded Anthropic stock at another 10x gain from here, first.]

You could invest in AI stocks through a donor-advised fund or private foundation to reduce the potential for personal gain and so COIs.

Yes, but the COIs extend to altruistic impact too. Like - which EA EtG-er wouldn't want to be able to give away a billion dollars? Having AI stocks in your DAF still biases you toward supporting the big AI companies, and against trying to stop AGI/ASI development altogether (when that may well actually be the most high impact thing to do, even if it means you never get to give away a billion dollars).

How much impact do you expect such a COI to have compared to the extra potential donations?

For reference:

  1. You could have more than doubled your investments over the past 1 year period by investing in the right AI companies, e.g. Nvidia, which seemed like a predictably good investment based on market share and % exposure to AI and is up +200% (3x). SMH is up +77%.
  2. Even the S&P500 is around 30% Microsoft, Apple (maybe not much of an AI play now), Nvidia, Amazon, Meta, Google/Alphabet and Broadcom, and these big tech companies have driven most of its gains recently (e.g. this and this).

And how far do you go in recommending divestment from AI to avoid COIs?

  1. Do you think people should avoid the S&P500, because its exposure to AI companies is so high? (Maybe equal-weight ETFs, or specific ETFs missing these companies, or other asset classes.)
  2. Do you think people should short or buy put options on AI companies? This way they're even more incentivized to see them do badly.

Well, the bottom line is extinction, for all of us. If the COIs block enough people from taking sufficient action, before it's too late, then that's what happens. The billions of EA money left in the bank as foom-doom hits will be useless. Might as well never have been accumulated in the first place.

I'll also note that there are plenty of other potential good investments out there. Crypto has gone up about as much as AI stocks in general over the last year, and some of them (e.g. SOL) have gone up much more than NVDA. There are promising start-ups in many non-AI areas. (Join this group to see more[1]).

To answer your bottom two questions:

1. I think avoiding stock-market-wide index funds is probably going too far (as they are neutral about AI - if AI starts doing badly, e.g. because of regulation, then the composition of the index fund will change to reflect this).

2. I wouldn't recommend this as a strategy, unless they are already on their way down and heavy regulation looks imminent.

  1. ^

    But note that people are still pitching the likes of Anthropic in there! I don't approve of that.

Bitcoin is only up around 20% from its peaks in March and November 2021. It seems far riskier in general than just Nvidia (or SMH) when you look over longer time frames. Nvidia has been hit hard in the past, but not as often or usually as hard.

Smaller cap cryptocurrencies are even riskier.

I also think the case for outperformance of crypto in general is much weaker than for AI stocks, and it has gotten weaker as institutional investment has increased, which should increase market efficiency. I think the case for crypto has mostly been greater fool theory (and partly as an inflation hedge), because it's not a formally productive asset and its actual uses seem overstated to me. And even if crypto were better, you could substantially increase (risk-adjusted) returns by also including AI stocks in your portfolio.

I'm less sure about private investments in general, and they need to be judged individually.

I don't really see why your point about the S&P500 should matter. If I buy 95% AI stocks and 5% other stuff and don't rebalance between them, AI will also have a relatively smaller share if it does relatively badly, e.g. due to regulation.

Maybe there's a sense in which market cap-weighting from across sectors and without specifically overweighting AI/tech is more "neutral", but it really just means deferring to market expectations, market time discount rates and market risk attitudes, which could differ from your own. Equal-weighting (securities above a certain market cap or asset classes) and rebalancing to maintain equal weights seems "more neutral", but also pretty arbitrary and probably worse for risk-adjusted returns.

Furthermore, I can increase my absolute exposure to AI with leverage on the S&P500, like call options, margin or leveraged ETFs. Maybe I assume non-AI stocks will do roughly neutral or in line with the past, or the market as a whole will do so assuming AI progress slows. Then leverage on the S&P500 could really just be an AI play.

One quick point is divesting, while it would help a bit, wouldn't obviously solve the problems I raise – AI safety advocates could still look like alarmists if there's a crash, and other investments (especially including crypto) will likely fall at the same time, so the effect on the funding landscape could be similar.

With divestment more broadly, it seems like a difficult question.

I share the concerns about it being biasing and making AI safety advocates less credible, and feel pretty worried about this.

On the other side, if something like TAI starts to happen, then the index will go from 5% AI-companies to 50%+ AI companies. That'll mean AI stocks will outperform the index by ~10x or more, while non-AI stocks will underperform by 2x or more.

So by holding the index, you'd be forgoing 90%+ of future returns (in the most high leverage scenarios), and being fully divested, giving up 95%+.

So the costs are really big (far far greater than divesting from oil companies).

Moreover, unless your p(doom) is very high, it's plausible a lot of the value comes from what you could do in post-TAI worlds. AI alignment isn't the only cause to consider.

On balance, it doesn't seem like the negatives are so large as to reduce the value of your funds by 10x in TAI worlds. But I feel uneasy about it.

What impact do you expect a marginal demand shift of $1 million (or $1 billion) in AI stocks to have on AI timelines? And why?

(Presumably the impact on actual investments in AI is much lower, because of elasticity, price targets for public companies, limits on what private companies intend to raise at a time.)

Or is the concern only really COIs?

The concern is mainly COIs, then bad PR. The direct demand shift could still be important though, if it catalyses further demand shift (e.g. divestment from apartheid South Africa eventually snowballed into having a large economic effect).

Furthermore, if you're sufficiently pessimistic about AI alignment, it might make sense to optimize for a situation where we get a crash and the longer timeline that comes with it. ("Play to your outs"/condition on success.)

That suggests a portfolio that's anticorrelated with AI stocks, so you can capitalize on the longer-timelines scenario if a crash comes about.

"Nvidia’s implied volatility is about 60%, which means – even assuming efficient markets – it has about a 15% chance of falling more than 50% in a year.

And more speculatively, booms and busts seem more likely for stocks that have gone up a ton, and when new technologies are being introduced."

Do you think the people trading the options setting that implied volatility are unaware of this?

Agree it's most likely already in the price.

Though I'd stand behind the idea that markets are least efficient when it comes to big booms and busts involving large asset classes (in contrast to relative pricing within a liquid asset class), which makes me less inclined to simply accept market prices in these cases.

And more speculatively, booms and busts seem more likely for stocks that have gone up a ton, and when new technologies are being introduced.

If I understand correctly, you are interpreting the above as stating that the implied volatility would be higher in a more efficient market. But I originally interpreted it as claiming that big moves are relatively more likely than medium-small moves compared to other options with the same IV (if that makes any sense)

Taking into account volatility smiles and all the things that I wouldn't think about, as someone who doesn't know much about finance and doesn't have Bloomberg Terminal, is there an easy way to answer the question "what is the option-prices-implied chance of NVDA falling below 450 in a year?"

I see that the IV for options with a strike of 450 next year is about ~70% for calls and ~50% for puts. I don't know how to interpret that, but even using 70%, this calculator gives me a ~16% chance, so would it be fair to say that traders think there's a ~15% chance of NVDA falling below 450 in a year?

In general, I think both here and in the accompanying thread finance professionals might be overestimating people's average familiarity with the field.

The IV for puts and calls at a given strike and expiry date will be identical, because one can trivially construct a put or a call from the other by trading stock, and the only frictions are the cost of carry.

The best proxy for probability an option will expire in the money is the delta of the option.

The best proxy for probability an option will expire in the money is the delta of the option.

 

Thank you. Here's an explanation from Wikipedia for others like me new to this.

Looking at the delta here and here, the market would seem to imply a ~5% chance of NVDA going below 450, which is not consistent with the ~15% in the article derived from the IV. Is it mostly because of a high risk-free interest rate?

I wonder which value would be more calibrated, or if there's anything I could read to understand this better. It seems valuable to be able to easily find rough market-implied probabilities for future prices.

Generally I just wouldn't trust numbers from Yahoo and think that's the Occam's Razor explanation here.

Delta is the value I would use before anything else since the link to models of reality is so straightforward (stock moves $1 => option moves $0.05 => clearly that's equivalent to making an extra dollar 5% of the time)

Just had another glance at this and I think the delta vs implied vol piece is consistent with something other than a normal/log normal distribution. Consider: the price is $13 for the put, and the delta is 5. This implies something like - the option is expected to pay off a nonzero amount 5% of the time, but the average payoff when it does is $260 (despite the max payoff definitionally being 450). So it looks like this is really being priced as crash insurance, and the distribution is very non normal (i.e. circumstances where NVDA falls to that price means something weird has happened)

Can you explain? I see why the implied vols for puts and calls should be identical, but empirically, they are not—right now calls at $450 have an implied vol of 215% and puts at $450 have an implied vol of 158%. Are you saying that the implied vol from one side isn't the proper implied vol, or something?

Right now the IV of June 2025 450 calls is 53.7, and of puts 50.9, per Bloomberg. I've no idea where your numbers are coming from, but someone is getting the calculation wrong or the input is garbage.

The spread in the above numbers is likely to do with illiquidity and bid ask spreads more than anything profound.

Could be interesting to see some more thinking about investments that have short-to-medium-term correlations with long-term-upside-capturing/mission-hedging stocks that don't themselves have these features (as potential complementary shorts).

You could look for investments that do neutral-to-well in a TAI world, but have low-to-negative correlation to AI stocks in the short term. That could reduce overall portfolio risk but without worsening returns if AI does well.

This seems quite hard, but the best ideas I've seen so far are:

  1. The cluster of resources companies, electricity producers, commodities, land. There's reason to think these could do quite well during a TAI transition, but in the short term they do well when inflation rises, which tends to be bad for AI stocks. (And they were effective hedges in the most recent draw down and in 2022.) Some of them also look quite cheap at the moment. However, in a recession, they will fall at the same time as AI stocks.
  2. Short long-dated government bonds or AI company credit. In the short term helps to hedge out the interest rate and inflation exposure in AI companies, and should also do well in the long term if an AI boom increases interest rates. Credit spreads are narrow so you're not paying much for the hedge. However, if there's a recession, these will also do badly.
  3. Index shorts (especially focused on old economy stocks). This could reduce overall market risk, and AI stocks will most likely fall at the same time as other stocks. If you buy long dated put options there's some reason to think AI will increase volatility, so you might also benefit a little there. However, on net it might be desirable to have high market exposure / this trade most likely loses money.
  4. Long-short multi-asset trend-following. This is an active strategy (so you might be skeptical that it works) but tends to do well during macro regime changes / big market crashes / high volatility, which will likely be times when AI stocks are doing badly. But for the same reasons it could also do well during an AI boom.

However, all of these have important downsides and someone would need to put billions of dollars behind them to have much impact on the overall portfolio. 

(Also this is not investment advice and these ideas are likely to lose a lot of money in many scenarios.)

Thanks for the post, Ben!

First, the wealth of many donors to AI safety is pretty correlated with AI stocks.

I like that Founders Pledge's Patient Philanthropy Fund (PPF) invests in "a low-fee Global Stock Index Fund". I also have all my investments in global stocks (Vanguard FTSE All-World UCITS ETF USD Acc).

A crash in the stock market might actually increase AI arms races if companies don't feel like they have the option to go slow.

Here is some data indicating that time devoted to AI in earnings calls peaked in 2023 and has dropped significantly since then.

According to the Gartner hype cycle, new technologies are usually overhyped, and massive hype is typically followed by a period of disillusionment. I don't know if this claim is backed by solid data, however. The wikipedia page cites this LinkedIn post, which discusses a bunch of counterexamples to the Gartner hype cycle. But none of the author's counterexamples take the form of "technology generates massive hype, hype turns out to be fully justified, no trough of disillusionment". Perhaps the iPhone would fall in this category?

Interesting. I guess a key question is whether another wave of capabilities (e.g. gpt-5, agent models) comes in soon or not.

Executive summary: A potential crash in AI stocks, while not necessarily reflecting long-term AI progress, could have negative short-term effects on AI safety efforts through reduced funding, shifted public sentiment, and second-order impacts on the AI safety community.

Key points:

  1. AI stocks, like Nvidia, have a significant chance of crashing 50% or more in the coming years based on historical volatility and typical patterns with new technologies.
  2. A crash could occur if AI revenues fail to grow fast enough to meet market expectations, even if capabilities continue advancing, or due to broader economic factors.
  3. An AI stock crash could modestly lengthen AI timelines by reducing investment capital, especially for startups.
  4. The wealth of many AI safety donors is correlated with AI stocks, so a crash could tighten the funding landscape for AI safety organizations.
  5. Public sentiment could turn against AI safety concerns after a crash, branding advocates as alarmists and making it harder to push for policy changes.
  6. Second-order effects, like damaged morale and increased media attacks, could exacerbate the direct impacts of a crash on the AI safety community.

 

 

This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.

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