I do research at Longview Philanthropy. Previously I was a Research scholar at FHI and assistant to Toby Ord. Philosophy at Cambridge before that.
I also do a podcast about EA called Hear This Idea.
finm
Karma: 2,973
Do you think octopuses are conscious? I do — they seem smarter than chickens, for instance. But their most recent common ancestor with vertebrates was some kind of simple Precambrian worm with a very basic nervous systems.
Either that most recent ancestor was not phenomenally conscious in the sense we have in mind, in which case consciousness arose more than once in the tree of life. Or else it was conscious, in which case consciousness would seem easy to reproduce (wire together some ~1,000 nerves).
The main question of the debate week is: “On the margin, it is better to work on reducing the chance of our extinction than increasing the value of the future where we survive”.
Where “our” is defined in a footnote as “earth-originating intelligent life (i.e. we aren’t just talking about humans because most of the value in expected futures is probably in worlds where digital minds matter morally and are flourishing)”.
I’m interested to hear from the participants how likely they think extinction of “earth-originating intelligent life” really is this century. Note this is not the same as asking what your p(doom) is, or what likelihood you assign to existential catastrophe this century.
My own take is that literal extinction of intelligent life, as defined, is (much) less than 1% likely to happen this century, and this upper-bounds the overall scale of the “literal extinction” problem (in ITN terms). I think this partly because the definition counts AI survival as non-extinction, and I truly struggle to think of AI-induced catastrophes leaving only charred ruins, without even AI survivors. Other potential causes of extinction, like asteroid impacts, seem unlikely on their own terms. As such, I also suspect that most work directed at existential risk is just already not in practice targeting extinction as defined, though of course it is also not explicitly focusing on “better futures” instead — more like “avoiding potentially terrible global outcomes”.
(This became more a comment than a question… my question is: “thoughts?”)
Nice! Consolidating some comments I had on a draft of this piece, many of them fairly pedantic:
Why would value be disributed over some suitable measure of world-states in a way that can be described as a power law specifically (vs some other functional form where the most valuable states are rare)? In particular, shouldn’t we think that there is a most valuable world state (or states)? So at least we need to say it’s a power law distribution with a max value.
“Then there is a powerful argument that the expected value of the future is very low.”
Very low as a fraction of the best futures, but not any lower relative to (e.g.) the world today, or the EV of the future. Indeed the future could be amazing by all existing measures. One framing on what you are saying is that it could be even better than we think, which is not a pessimistic result!
Another framing is more like “it’s easier than we thought to make amazing-seeming worlds far less valuable than they seem, by making mistakes like e.g. ignoring animal farming”. That is indeed bad news.
And of course the decision-relevance of MPL depends on the feasibility of the best futures, not just how they’re distributed.
One possibility that would support MPL is the possibility that value scales superlinearly with the amount of “optimised matter” — e.g. with brain size. The task of a risk-neutral classical utilitarian can then effectively be boiled down to “maximising the chance of getting ~the most optimized state possible”, as long as “~the most optimized state possible” is at all feasible.
“If you value pretty much anything (e.g. consciousness, desire satisfaction), there’s likely to be a sharp line in phase space where a tiny change to the property makes an all-or-nothing difference to value.” — this is true, but that the [arrangements of matter] → [value] function has discontinuities doesn’t imply that the very most valuable states are extremely rare and far more valuable than all the others. So I think it’s weak evidence for MPL.
Some distinctions which occur to me below. Assuming some measure over states:
EV of the world at a state, vs value of a state itself (where EV cares about future states)
Note that the [state]→[EV] function should be discontinuous, because the evolution of states over time is discontinuous, because that’s how the world works! E.g. in some cases you should evaluate a big difference in EV just by changing a vote counter after an election by one.
Fragility of value/EV, something like how much value tends to change with small changes in space of states
Rarity of value, something like what fraction of all states are >50% as valuable as the most valuable state(s)
Unity of value, something like whether all the most valuable states are clumped together in state space, or whether the ‘peaks’ of the landscape are far apart and separated by valleys of zero or negative value
I think it’s a true and important point that people currently converge on states they agree are high EV, because the option space is limited, and most good we value are still scarce instrumental goods — but when the option space grows, the latent disagreement becomes more important.
“I don’t know if my folk history is accurate, but my understanding is that early religions and cultures had a lot in common with each other”
I guess it depends on how you interpret ~indexical beliefs like “I want my group to win and the group over the hill to lose” — both sides can think that same thing, but might hate any compromise solution.
I think this is a reason for pessism about different values agreeing on the same states, and ∴ supportive of MPL.
Re brains, there are some (weak) reasons to expect finite optimal sizes, like speed of light. A ‘Jupiter brain’ is not very different from many smaller brains with high bandwidth (but laggy) communication.
I doubt how rare near-best futures are among desired futures is a strong guide to the expected value of the future. At least, you need to know more about e.g. the feasibility of near-best futures; whether deliberative processes and scientific progress converge on an understanding of which futures are near-best, etc.
There is an analogous argument which says: “most goals in the space of goals are bad and lead to AI scheming; AI will ~randomly initialise on a goal; so AI will probably scheme”. But obviously whenever we make things by design (like cars or whatever), we are creating things which are astronomically unlikely configurations in the “space of ways to organise matter”. And the likelihood that humans build cars just doesn’t have much to do with what fraction of matter state space they occupy. It’s just not an illuminating frame. The more interesting stuff is “will humans choose to make them”, and “how easy are they to make”. (I think Ben Garfinkel has made roughly this point, as has Joe Carlsmith more recently.)
Partly this is because I think “extinction” as defined here is very unlikely (<<1%) to happen this century, which upper bounds the scale of the area. I think most “existential risk” work is not squarely targeted at avoiding literal extinction of all Earth-originating life.
Preparing for the Intelligence Explosion
I just googled “Phil Trammell new product varieties from AI could introduce ambiguities in accounting for GDP” because I wanted something to link to, and saw you’d posted this. Thanks for writing it up!
It’s worth noting that the average answers to “How much financial compensation would you expect to need to receive to make you indifferent about that role not being filled?” were $272,222 (junior) and $1,450,000 (senior).
And so I think that just quoting the willingness to pay dollar amounts to hire top over second-preferred candidate can be a bit misleading here, because it’s not obvious to everyone that WTP amounts are typically much higher than salaries in general in this context. If the salary is $70k, for instance, and the org’s WTP to hire you over the second-preferred candidate $50k, it would be a mistake to infer that you are perceived as 3.5 times more impactful.
Another way of reading this is that the top hire is perceived as about 23% and about 46% more ‘impactful’ respectively than the second-preferred hire in WTP terms on average. I think this is a more useful framing.
And then eyeballing the graphs, there is also a fair amount of variance in both sets of answers, where perceptions of top junior candidates’ ‘impactfulness’ appear to range from ~5–10% higher to ~100% higher than the second-best candidate. That suggests it is worth at least asking about replaceability, if there is a sensitive way to bring it up!
I agree that people worry too much about replaceability overall, though.
Thanks! I’m not trying to resolve concerns around cluelessness in general, and I agree there are situations (many or even most of the really tough ‘cluelessness’ cases) where the whole ‘is this constructive?’ test isn’t useful, since that can be part of what you’re clueless about, or other factors might dominate.
Why do you think we ought to privilege the particular reason that you point to?
Well, I’m saying the ‘is this constructive’ test is a way to latch on to a certain kind of confidence, viz the confidence that you are moving towards a better world. If others also take constructive actions towards similar outcomes, and/or in the fullness of time, you can be relatively confident you helped get to that better world.
This is not the same thing as saying your action was right, since there are locally harmful ways to move toward a better world. And so I don’t have as much to say about when or how much to privilage this rule!
Moral mountaineering
Who can we thank for the design? It’s seriously impressive!
Just I want to register the worry that the way you’ve operationalised “EA priority” might not line up with a natural reading of the question.
The footnote on “EA priority” says:
By “EA priority” I mean that 5% of (unrestricted, i.e. open to EA-style cause prioritisation) talent and 5% of (unrestricted, i.e. open to EA-style cause prioritisation) funding should be allocated to this cause.
This is a bit ambiguous (in particular, over what timescale), but if it means something like “over the next year” then that would mean finding ways to spend ≈$10 million on AI welfare by the end of 2025, which you might think is just practically very hard to do even if you thought that more work on current margins is highly valuable. Similar things could have been said for e.g. pandemic prevention or AI governance in the early days!
Thanks Vasco!
Nice post! Copying the comment I left on the draft (edited for clarity) —
I agree with both conclusions, but I don’t think your argument is the strongest reason to buy those conclusions.
My picture of how large-scale space expansion goes involves probes (not humans) being sent out after AGI. Then a reasonable default might be that the plans and values embedded in humanity’s first large-scale space settlement initiatives are set by the plans and values of some very large and technologically advanced political faction at the time (capable of launching such a significant initiative by force or unanimity), rather than a smaller number of humans who were early to settle some part of the Solar System.
I then picture most human-originating life to not resemble biological humans (more like digital people). In this case it’s very hard to imagine how farming animals would make any sense.
Even with shorter-term and human-led space settlement, like bases on the Moon and Mars, I expect it to make very little logistical sense to farm animals (regardless of the psychological profile of whoever is doing the settlement). The first settlements will be water and space and especially labour constrained, and raising animals is going to look needlessly painful and inefficient without the big economies of scale of factory farms.
That said, if animals are farmed in early settlements, then note that smaller animals tend to be the most efficient at converting feed into human-palatable calories (and also the most space-efficient). For that reason some people suggest insect farming (e.g. crickets, mealworms), which does seem much more likely than livestock or poultry! But another option is bioreactors of the kind being developed on Earth. In theory they could become more efficient than animals and would then make most practical sense (since the capital cost to build the reactor isn’t going to matter; taking anything into space is already crazy expensive). Also a lot of food will probably be imported as payload early on; unsure if that’s relevant.
So I think I’m saying the cultural attitudes of early space settlers is probably less important than the practical mechanisms by which most of space is eventually settled. Especially if most future people are not biological humans, which kind of moots the question.
I do think it’s valuable and somewhat relieving to point out that animal farming could plausibly remain an Earth-only problem!
I endorse many (more) people focusing on x-risk and it is a motivation and focus of mine; I don’t endorse “we should act confidently as if x-risk is the overwhelmingly most important thing”.
Honestly, I think the explicitness of my points misrepresents what it really feels like to form a view on this, which is to engage with lots of arguments and see what my gut says at the end. My gut is moved by the idea of existential risk reduction as a central priority, and it feels uncomfortable being fanatical about it and suggesting others do the same. But it struggles to credit particular reasons for that.
To actually answer the question: (6), (5), and (8) stand out, and feel connected.
Agree.
In this spirit, here are some x-risk sceptical thoughts:
You could reasonably think human extinction this century is very unlikely. One way to reach this conclusion is simply to work through the most plausible causes of human extinction, and reach low odds for each. Vasco Grilo does this for (great power) conflict and nuclear winter, John Halstead suggests extinction risk from extreme climate change is very low here, and the background rate of extinction from natural sources can be bounded by (among other things) observing how long humans have already been around for. That leaves extinction risk from AI and (AI-enabled) engineered pandemics, where discussion is more scattered and inconclusive. Here and here are some reasons for scepticism about AI existential risk.
Even if the arguments for AI x-risk are sound, then it’s not clear how they are arguments for expecting literal human extinction over outcomes like ‘takeover’ or ‘disempowerment’. It’s hard to see why AI takeover would lead to smouldering ruins, versus continued activity and ‘life’, just a version not guided by humans or their values.
So “existential catastrophe” probably shouldn’t just mean “human extinction”. But then it surprisingly slippery as a concept. Existential risk is the risk of existential catastrophe, but it’s difficult to give a neat and intuitive definition of “existential catastrophe” such that “minimise existential catastrophe” is a very strong guide for how to do good. Hilary Greaves dicusses candidate definitions here.
From (1), you might think that if x-risk reduction this century should be a near-top priority, then most its importance comes from mitigating non-extinction catastrophes, like irreversible dystopias. But few current efforts are explicitly framed as ways to avoid dystopian outcomes, and it’s less clear how to do that. Other than preventing AI disempowerment or takeover, assuming those things are dystopian.
But then isn’t x-risk work basically just about AI, and maybe also biorisk? Shouldn’t specific arguments for those risks and ways to prevent them therefore matter more than more abstract arguments for the value of mitigating existential risks in general?
Many strategies to mitigate x-risks trade off uncomfortably against other goods. Of course they require money and talent, but it’s hard to argue the world is spending too much on e.g. preventing engineered pandemics. But (to give a random example), mitigating x-risk from AI might require strong AI control measures. If we also end up thinking things like AI autonomy matter, that could be an uncomfortable (if worthwhile) price to pay.
It’s not obvious that efforts to improve prospects for the long-run future should focus on preventing unrecoverable disasters. There is a strong preemptive argument for this; roughly that humans are likely to recover from less severe disasters, and so retain most their prospects (minus the cost of recovering, which is assumed to be small in terms of humanity’s entire future). The picture here is one on which the value of the future is roughly bimodal — either we mess up irrecoverable and achieve close to zero of our potential, or we reach roughly our full potential. But that bimodal picture isn’t obviously true. It might be comparably important to find ways to turn a mediocre-by-default future into a really great future, for instance.
A related picture that “existential catastrophe” suggests is that the causes of losing all our potential are fast and discrete events (bangs) rather than gradual processes (whimpers). But why are bangs more likely than whimpers? (See e.g. “you get what you measure” here).
Arguments for prioritising x-risk mitigation often involve mistakes, like strong ‘time of perils’ assumptions and apples to oranges comparisons. A naive case for prioritising x-risk mitigation might go like this: “reducing x-risk this century by 1 percentage point is worth one percentage point of the expected value of the entire future conditional on no existential catastrophes. And the entire future is huge, it’s like lives. So reducing x-risk by even a tiny fraction, say , this century saves (a huge number of) lives in expectation. The same resources going to any work directed at saving lives within this century cannot save such a huge number of lives in expectation even if it saved 10 billion people.” This is too naive for a couple reasons:
This assumes this century is the only time where an existential catastrophe could occur. Better would be “the expected value of the entire future conditional on no existential catastrophe this century”, which could be much lower.
This compares long-run effects with short-run effects without attempting to evaluate the long-run effects of interventions not deliberately targeted at reducing existential catastrophe this century.
Naive analysis of the value of reducing existential catastrophe also doesn’t account for ‘which world gets saved’. This feels especially relevant when assessing the value of preventing human extinction, where you might expect the worlds where extinction-preventing interventions succeed in preventing extinction are far less valuable than the expected value of the world conditional on no extinction (since narrowly avoiding extinction is bad news about the value of the rest of the future). Vasco Grilo explores this line of thinking here, and I suggest some extra thoughts here.
The fact that some existential problems (e.g. AI alignment) seem, on our best guess, just about solvable with an extra push from x-risk motivated people doesn’t itself say much about the chance that x-risk motivated people make the difference in solving those problems (if we’re very uncertain about how difficult the problems are). Here are some thoughts about that.
These thoughts make me hesitant about confidently acting as if x-risk is overwhelmingly important, even compared to other potential ways to improve the long-run future, or other framings on the importance of helping navigate the transition to very powerful AI.
But I still existential risk matters greatly as an action-guiding idea. I like this snippet from the FAQ page for The Precipice —
But for most purposes there is no need to debate which of these noble tasks is the most important—the key point is just that safeguarding humanity’s longterm potential is up there among the very most important priorities of our time.
[Edited a bit for clarity after posting]
Thanks for the comment, Owen.
I agree with your first point and I should have mentioned it.
On your second point, I am assuming that ‘solving’ the problem means solving it by a date, or before some other event (since there’s no time in my model). But I agree this is often going to be the right way to think, and a case where the value of working on a problem with increasing resources can be smooth, even under certainty.
Ah thanks, good spot. You’re right.
Another way to express (to avoid a stacked fraction) is ; i.e. percentage change in resources. I’ll update the post to reflect this.
Just noticed I missed the deadline — will you be accepting late entries?Edit: I had not in fact missed the deadline
Where are you getting those numbers from? If by “subjective decades” you mean “decades of work by one smart human researcher”, then I don’t think that’s enough to secure it’s position as a singleton.
If you mean “decades of global progress at the global tech frontier” then imagining that the first-mover can fit ~100 million human research-years into a few hours shortly after (presumably) pulling away from the second-mover in a software intelligence explosion, then I’m skeptical (for reasons I’m happy to elaborate on).