or: The Future Will Be Weirder Than That, Part II

People often treat AI as if it will improve on its current capabilities, but won’t gain any new ones. Supposedly, AI will continue to get better at coding and at assisting with research, but it won’t broadly replace human labor. It won’t be able to do good strategic planning, and certainly won’t know how to operate in the physical realm.

Maybe that’s true. But we don’t have strong reason to believe it. Just looking at the past few years, AI has rapidly acquired new skills. The simplest extrapolation of recent trends is that it will continue to do so.

Some people think of AI capabilities growth like this, with each colored area representing another few years of progress:¹

But it’s more likely to look like this:

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This post is a submission to the Cluelessness Critiques Essay Competition.

Credence: Likely.¹

Anthony DiGiovanni’s sequence, The challenge of unawareness for impartial altruist action guidance (henceforth “the sequence”), argues that impartial altruists have no non-arbitrary reason to prefer any decision over any other. The central problem is unawareness: “many possible consequences of our actions haven’t even occurred to us in much detail, if at all.”

I disagree. Impartial altruists should act as if we have precise probabilities for beliefs and precise expected utilities of decisions, even if we (usually) do not explicitly state them. It’s okay to act on heuristics, but those heuristics are in service of maximizing the expected value of a (non-literal) utility function, rather than being “terminal” heuristics.

“Act as if” means: either I give an explicit precise credence; or I don’t, but I operate under the assumption that I could give a precise credence if I spent enough time reasoning through my beliefs.

This post starts by explaining the sequence’s central arguments in my own words. Then it offers five defenses of acting on your best guess.

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I continue to believe we should pause frontier AI development. Any discussion of alternative strategies should be thought of as planning for contingencies.

A unifying driver behind many post-alignment risks—catastrophic risks that remain even if we solve the alignment problem—is that by strong default, ASI would end liberal democracy. Liberalism—in which people have individual rights, autonomy, and the ability to choose their own destiny—is an important force protecting human welfare.¹ When people are free, we are reasonably good at making our lives better of our own volition.

Many post-alignment risks have a certain flavor. AI-empowered terrorism; coups; permanent dictatorships; concentration of power. Those risks already exist today (and existed 20 years ago), but they’re mitigated by the fact that power is relatively evenly distributed across people. The most powerful person in the world doesn’t have an extraordinary advantage over the 10th-most-powerful person. ASI could change that.

If people still have civil liberties post-ASI, that will only be because the controllers of ASI allow us to have them.²

One way of thinking goes: AI will be extremely powerful. If everyone had their own personal AI, we could each use it to protect our own interests, and things will turn out okay for us. But how do you get there? It’s not going to happen automatically, but it may be possible to set up a gradual process to keep power balanced.

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Here’s some cool stuff I’ve enjoyed recently.

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To achieve the best possible future, we must know what that future looks like. In other words, we need to solve ethics.¹

The problem of solving ethics is so large and abstract that it’s difficult to say useful things about. In lieu of any structured analysis, herein lies a collection of thoughts about the problem.

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I prefer to avoid saying things that I suspect might make me look stupid. Over the last couple of years, however, I’ve made a conscious effort to write publicly about what I’m thinking about, even if I’m afraid it might sound dumb.

Sometimes I have this feeling, like:

I have an observation about the world, about something that doesn’t seem to add up. Probably I’m missing something, and everyone but me can easily see what’s going on, and if I bring it up, then everyone will know how foolish I am for missing this obvious thing.

Sometimes I’m right, and I really was missing something obvious. But some of my most well-received writings turned out to be ones where I had this feeling, and I was ambivalent about whether it was worth saying anything.

Lately, I’m making more of an effort to overcome that feeling, and say the stupid thing anyway, because it might turn out not to be stupid.

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Some people think we should pause AI, but not now. They say we should wait until AI reaches human level,¹ because:

• It’s not (catastrophically) dangerous until after then.
• Human-level AI will help us do safety research.

Alternatively, other people (like me) think we should pause AI as soon as possible.

Katja Grace wrote a nice concise case for pausing ASAP. I have something I’d like to add: pausing at human level seems harder than pausing ASAP.²

Pausing ASAP sounds hard. It will be hard to get international coordination around an AI pause, and implementing a pause sounds hard even if we can agree to it in principle. But pausing ASAP still seems easier than pausing at human-level AI, for several reasons:

• Human-level AI is highly economically valuable, and therefore there is a great temptation to keep going. The monetary incentive to build increasingly-powerful AI will be intense, and industry lobbyists really won’t want to pause AI development. It seems hard to pause when the economic incentive to continue is so great.
• If AI is smart enough to accelerate safety work, then it’s also smart enough to accelerate improvements in AI capabilities. And it will probably be disproportionately good at the latter: capabilities improvements are easy to measure, and AI tends to be disproportionately good at easily measurable tasks. (Recent AI models have seen bigger improvements in math and coding abilities than in writing or philosophy.) If AI R&D used to require a team of PhDs, and now all it requires is someone in a garage with access to the latest AI model, then it’s harder to enforce a pause because clandestine AI research is harder to catch.
• This next argument is more about a unilateral pause than a coordinated pause, but: Some say that the “good” AI developers need to push the frontier to maintain their lead, and that they should wait until the last minute to burn their lead to work on safety. Burning their lead at the end provides the maximum uplift from AI-assisted safety work. However, AI developers always face a choice between an uncertain downside (keep going, and possibly kill everyone) vs. a certain downside (pause, crater your profit potential, and possibly some other developer kills everyone anyway). I cannot foresee them making a rational risk assessment under those circumstances. There is too much pressure to distort their beliefs in favor of continuing to push the frontier.
• If we had technology that could replace human labor, but it’s cheaper, faster, and can be copied as many times as one wants, how would that change the economy and society? I don’t know, but I bet it would change a lot. That level of disruption makes the world unpredictable. It seems risky to follow plans along the lines of, “let’s wait until this technology radically transforms society, possibly making things totally unrecognizable, and then implement our plan after that. Surely it will still work!”

An important counterpoint:

• The general public does not like AI. If AI starts taking people’s jobs, then people will really dislike it. The unemployment effect of AI may create enough political will to pause that it outweighs out the economic incentive effect.

I hope this final point is strong enough to make pausing much easier in the future (hopefully the near future). But that doesn’t mean we shouldn’t try to pause ASAP.

Notes

I continue to believe we should pause frontier AI development. Any discussion of alternative strategies should be thought of as planning for contingencies.

“Super-persuasive” AI is dangerous because a misaligned ASI could persuade humans to help it take over. But setting that aside, even if we manage to make ASI friendly, it may provide super-persuasive but mistaken guidance that permanently sets us down the wrong path.

This post focuses on the danger of an aligned super-persuasive AI that simply comes up with the wrong answers.

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An argument goes: If we don’t build aligned artificial superintelligence, we risk driving ourselves extinct for some other reason. We should rush to build ASI quickly, in spite of the risks—the longer we wait, the more vulnerable we are to extinction from a different cause.

Other than ASI, the biggest extinction risk is synthetic biology. Some lab could (accidentally or on purpose) develop a highly transmissible, 100% fatal super-plague that wipes out humanity.

An aligned ASI could stop that from happening by shutting down dangerous biological research, or by developing advanced countermeasures that stop the spread of deadly infections. So the argument goes: We need to build ASI to save us from non-AI extinction risks.

However, that argument doesn’t work. In the near term, AI will make biological risks worse, not better. AI will accelerate scientific research, which will bring us closer to the level of knowledge necessary to build extinction-level pathogens. And in the long term, the way ASI eliminates biological x-risk is by taking control of the world.

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Say you work at a private company that gives you stock options or RSUs. How should you value your stock?

• If you have a choice between getting more stock or more cash salary, how do you decide which to get?
• If you have the chance to sell some stock, should you do it?

Stock is risky and inflexible (especially if you work for a private company where you can’t easily sell shares), but you might be able to get it at a discount to its true value. How do you estimate how much it’s worth?

One heuristic you can use is to compare the stock against a risk-matched index fund. What would happen if you used the cash to buy a leveraged index fund with the same level of risk as the company stock? If the leveraged index fund has a higher expected return than the company stock, that means cash is probably better. (The reverse is not necessarily true because company stock can have other downsides, which I will get into later.)

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