simeon_c

Karma: 807

simeon_c 12 Oct 2023 13:08 UTC
11 points
4 ∶ 0
in reply to: Linch’s comment on: Linch’s Shortform
I agree with the general underlying point.

I also think that another important issue is that reasoning on counterfactuals makes people more prone to do things that are unusual AND is more prone to errors (e.g. by not taking into account some other effects).

Both combined make counterfactual reasoning without empirical data pretty perilous on average IMO.
In the case of Ali in your example above for instance, Ali could neglect that the performance he’ll have will determine the opportunities & impact he has 5y down the line and so that being excited/liking the job is a major variable. Without counterfactual reasoning, Ali would have intuitively relied much more on excitement to pick the job but by doing counterfactual reasoning which seemed convincing, he neglected this important variable and made a bad choice.
I think that counterfactual reasoning makes people very prone to ignoring Chesterton’s fence.

simeon_c 29 Sep 2023 12:17 UTC
3 points
0 ∶ 1
in reply to: richard_ngo’s comment on: Protest against Meta’s irreversible proliferation (Sept 29, San Francisco)
I think using “unsafe” in a very broad way like this is misleading overall and generally makes the AI safety community look like miscalibrated alarmists.
I agree that when there’s no memetic fitness/calibration trade-off, it’s always better to be calibrated. But here there is a trade-off. How should we take it?
1. My sense is that there’s never been any epistemically calibrated social movement and so that it would be playing against odds to impose that constraint. Even someone like Henry Spira who was very thoughtful personally used very unnuanced communication to achieve social change.
2. Richard, do you think that being miscalibrated has hurt or benefited the ability of past movements to cause social change? E.g. climate change and animal welfare.
  
  My impression is that probably not? They caused entire chunks of society to be miscalibrated on climate change (maybe less in the US but in Europe it’s pretty big), and that’s not good, but I would guess that the alarmism helped them succeed?
  As long as there also exists a moderate faction & and there still exists background debates on the object-level, I feel like having a standard social activism movement wd be overall very welcome.
Curious if anyone here knows the relevant literature on the topic, e.g. details in the radical flank literature.

simeon_c 8 Jul 2023 12:01 UTC
8 points
3 ∶ 1
on: Announcing Manifund Regrants
Very glad to see that happening, regranting solves a bunch of unsolved problems with centralized grantmaking.

simeon_c 28 Jun 2023 21:49 UTC
5 points
1 ∶ 0
in reply to: Yellow (Daryl)’s comment on: AGI x Animal Welfare: A High-EV Outreach Opportunity?
I mean, I agree that it has nuance but it’s still trained on a set of values that are pretty much current western people values, so it will probably put more or less emphasis on various values according to the weight western people give to each of those.

simeon_c 22 Apr 2023 20:25 UTC
5 points
1 ∶ 0
in reply to: Sanjay’s comment on: The Cruel Trade-Off Between AI Misuse and AI X-risk Concerns
I may try to write something on that in the future. I’m personally more worried about accidents and think that solving accidents causes one to solve misuse pre-AGI. Post aligned AGI, misuse rebecomes a major worry.

simeon_c 13 Feb 2023 23:25 UTC
11 points
7 ∶ 1
on: New EA Podcast: Critiques of EA
Note that saying “this isn’t my intention” doesn’t prevent net negative effects of a theory of change from applying. Otherwise, doing good would be a lot easier.
I also highly recommend clarifying what exactly you’re criticizing, i.e. the philosophy, the movement norms or some institutions that are core to the movement.
Finally, I usually find the criticism of people a) at the core of the movement and b) highly truth-seeking most relevant to improve the movement so I would expect that if you’re trying to improve the movement, you may want to focus on these people. There exists relevant criticisms external to the movement but usually they will lack of context and thus fail to address some key trade-offs that the movement cares about.
Here’s a small list of people I would be excited to hear on EA flaws and their recommandations for change:
- Rob Bensinger
- Eli Lifland
- Ozzie Gooen
- Nuno Sempere
- Oliver Habryka

simeon_c 11 Feb 2023 0:57 UTC
2 points
0 ∶ 0
on: There can be highly neglected solutions to less-neglected problems
Thanks for publishing that, I also had a draft lying somewhere on that!

simeon_c 2 Jan 2023 7:48 UTC
3 points
1 ∶ 0
on: How many hours is your standard workweek? Why?
I work every day from about 9:30am to 1am with about 3h off on average and 30 min of walk which helps me brainstorming. Technically this is ~12*7=84h. The main reason is that 1) I want that we don’t die and 2) think that there are increasing marginal returns on working hours in a lot of situation, mostly due to the fact that in a lot of domains, winner takes all even if he’s only 10% better than others, and because you accumulate in a single person more expertise/knowledge which gives access to more and more rare skills

Among that, I would say that I lose about 15h in unproductive or very little productive work (e.g Twitter or working on stuff which is not on my To Do list). I also spend about 10 to 15h a week in calls.
The rest of it (from 50 to 60h) is productive work.

My productivity (& thus productive work time) has been hugely increasing over the past 3 months (my first three months where I can fully decide the allocation of my time). The total amount of hours I work increased a bit (like +1h/day) in the last 3 months, mostly thanks to optimizations of my sleep & schedule.

simeon_c 2 Jan 2023 7:05 UTC
1 point
0 ∶ 0
in reply to: calebp’s comment on: How many hours is your standard workweek? Why?
Can you share the passive time tracking tools you’re using?

simeon_c 27 Dec 2022 23:53 UTC
3 points
0 ∶ 0
in reply to: Karl von Wendt’s comment on: AGI Timelines in Governance: Different Strategies for Different Timeframes
“Nobody cared about” LLMs is certainly not true—I’m pretty sure the relevant people watched them closely.
What do you mean by “the relevant people”? I would love that we talk about specifics here and operationalize what we mean. I’m pretty sure E. Macron haven’t thought deeply about AGI (i.e has never thought for more than 1h about timelines) and I’m at 50% that if he had any deep understanding of what changes it will bring, he would already be racing. Likewise for Israel, which is a country which has strong track record of becoming leads in technologies that are crucial for defense.
That many people aren’t concerned about AGI or doubting its feasibility by now only means that THOSE people will not pursue it, and any public discussion will probably not change their minds.
I think here you wrongly assume that people have even understood what are the implications of AGI and that they can’t update at all once the first systems will start being deployed. The situation where what you say could be true is if you think that most of your arguments hold because of ChatGPT. I think it’s quite plausible that since ChatGPT and probably even more in 2023 there will be deployments that may make mostly everyone that matter aware of AGI. I don’t have a good sense yet of how policymakers have updated yet.
Already there are many alarming posts and articles out there, as well as books like Stuart Russell’s “Human Compatible” (which I think is very good and helpful), so keeping the lid on the possibility of AGI and its profound impacts is way too late
Yeah, I realize thanks to this part that a lot of the debate should happen on specifics rather that at a high-level as we’re doing here. Thus, chatting about your book in particular will be helpful for that.
I’m currently in the process of translating it to English so I can do just that. I’ll send you a link as soon as I’m finished. I’ll also invite everyone else in the AI safety community (I’m probably going to post an invite on LessWrong).
Great! Thanks for doing that!
while discussing the great potential of AGI for humanity should not.
FYI I don’t think that it’s true.
Regarding all our discussion, I realized I didn’t mention a fairly important argument: a major failure mode specifically regarding risks is the following reaction from ~any country: “Omg, China is developing bad AGIs, so let’s develop safe AGIs first!”.
This can happen in two ways:
- Misuse as the mainline scenario that people are envisioning. Basically, if you’re mostly concerned about misuse, racing to be the first to have the AGI makes sense. And because misuse is way easier to understand than accidental risk, I expect this to be ~the default.
- Overestimating one’s competence. Even if you believed in AGI accidental X-risks, you could still race thinking that you’re better than the others and that could increase the chances of X-risk.
Thanks a lot for engaging with my arguments. I still think that you’re substantially overconfident about the positive aspects of communicating AGI X-risks to the general public but I appreciate the fact that you took the time to consider and answer to my arguments.

simeon_c 20 Dec 2022 20:24 UTC
1 point
0 ∶ 0
in reply to: Misha_Yagudin’s comment on: AGI Timelines in Governance: Different Strategies for Different Timeframes
Hey Misha! Thanks for the comment!
I am quite confused about what probabilities here mean, especially with prescriptive sentences like “Build the AI safety community in China” and “Beware of large-scale coordination efforts.”
As I wrote in note 2, I’m here claiming that this claim is more likely to be true under these timelines than the other timelines. But how could I make it clearer without bothering too much? Maybe putting note 2 under the table in italic?
I also disagree with the “vibes” of probability assignment to a bunch of these, and the lack of clarity on what these probabilities entail makes it hard to verbalize these.
I see, I hesitated in the trade-off (1) “put no probabilities” vs (2) “put vague probabilities” because I feel like that the second gives a lot more signal on how confident I am in what I say and allow people to more fruitfully disagree but at the same time it gives a “seriousness” signal which is not good when the predictions are not actual predictions.
Do you think that putting no probabilities would have been better?
By “I also disagree with the vibes of probability assignment to a bunch of these”, do you mean that it seems over/underconfident in a bunch of ways when you try to do a similar exercise?

simeon_c 20 Dec 2022 20:12 UTC
6 points
3 ∶ 0
in reply to: NickLaing’s comment on: AGI Timelines in Governance: Different Strategies for Different Timeframes
Ah ah you probably don’t realize it but “you” is actually 4 persons: Amber Dawn for the first draft of the post, me (Simeon) for the ideas, the table and the structure of the post, and me, Nicole Nohemi & Felicity Riddel for the partial rewriting of the draft to make it clearer.
So the credits are highly distributed! And thanks a lot, it’s great to hear that!

simeon_c 20 Dec 2022 20:08 UTC
5 points
2 ∶ 1
in reply to: HaydnBelfield’s comment on: AGI Timelines in Governance: Different Strategies for Different Timeframes
I think that our disagreement comes from what we mean by “regulating and directing it.”
My rough model of what usually happens in national governments (and not the EU, which is a lot more independent from its citizen than the typical national government) is that there are two scenarios:
1. Scenario 1 in which national governments regulate or do things on something nobody is caring about (in particular, not the media). That gives birth to a lot of degrees of freedom and the possibility of doing fairly ambitious things (cf Secret Congress)
2. Scenario 2 in which national governments regulate things that many people care about and brings attention and then nothing gets done, most measures are fairly weak etc. In this scenario my rough model is that national governments do the smallest thing that satisfy their electorate + key stakeholders.
I feel like we’re extremely likely to be in scenario 2 regarding AI. And thus that no significant measure will be taken, which is why I put the emphasis of “no strong [positive] effect” on AI safety. So basically I feel like the best you can probably do in national policy is something like “avoid that they do bad things” (which is really good if it’s a big risk) or “do mildly good things”. But to me, it’s quite unlikely that we go from a world where we die to a world where we don’t die thanks to a theory of change which is focused on national policy.
The EU AI Act is a bit different in that as I said above, the EU is much less tied to the daily worries of citizen and thus is operating under less constraints. Thus I think that it’s indeed plausible that the EU does something ambitious on GPAIS but I think that unfortunately it’s unlikely that the US will replicate something locally and that the EU compliance mechanisms are not super likely to cut the worst risks for the UK and US companies.
Regulating the training of these models is different and harder, but even that seems plausible to me at some point
I think that it’s plausible but not likely, and given that it would be the intervention that would cut the most risks, I tend to prefer corporate governance which seems significantly more tractable and neglected to me.
Out of curiosity, could you refer to a specific event you’d expect to see “if we get closer to substantial leaps in capabilities”? I think that it’s a useful exercise to disagree fruitfully on timelines and I’d be happy to bet on some events if we disagree on one.

simeon_c 20 Dec 2022 14:46 UTC
6 points
2 ∶ 0
in reply to: HaydnBelfield’s comment on: AGI Timelines in Governance: Different Strategies for Different Timeframes
Thanks for your comment!
A couple of remarks:
1. Regulations that cut X-risks are strong regulations: My sense is that regulations that really cut X-risks at least a bit are pretty “strong”, i.e. in the reference class of “Constrain labs to airgap and box their SOTA models while they train them” or “Any model which is trained must be trained following these rules/applying these tests”. So what matters in terms of regulation is “will governments take such actions?” and my best guess is no, at least not without the public opinion caring a lot about that. Do you have in mind an example of regulation which is a) useful and b) softer than that?
2. Additional state funding would be bad by default: I think that the default of “more funding goes towards AGI” is that it accelerates capabilities more (e.g backing some labs so that they move faster than China, things like that). Which is why I’m not super excited about increasing the amount of funding governments put into AGI. But to the extent that there WILL be some funding, then it’s nice to steer it towards safety research.
And finally, I like the example you gave on cyber. The point I was making was something like “Your theories of change for pre-2030 timelines shouldn’t rely too much on national government policy” and my understanding of what you’re saying is something like “that may be right, but national governments are still likely to have a lot of (bad by default) influence, so we should care about them”.
I basically had in mind this kind of scenario where states don’t do the research themselves but are backing some private labs to accelerate their own capabilities, and it makes me more worried about encouraging states to think about AGI. But I don’t put that much weight on these scenarios yet.
How confident are you that governments will get involved in meaningful private-public collaboration around AGI by 2030? A way of operationalizing that could be “A national government spends more than a billion $ in a single year on a collaboration with a lab with the goal to accelerate research on AGI”.
If you believe that it’s >50%, that would definitely update me towards “we should still invest a significant share of our resources in national policy, at least in the UK and the US so that they don’t do really bad moves”.

simeon_c 20 Dec 2022 14:18 UTC
1 point
0 ∶ 0
in reply to: HaydnBelfield’s comment on: AGI Timelines in Governance: Different Strategies for Different Timeframes
Oh that’s fun, thanks for the context!

simeon_c 20 Dec 2022 11:08 UTC
16 points
4 ∶ 0
in reply to: Karl von Wendt’s comment on: AGI Timelines in Governance: Different Strategies for Different Timeframes
Thanks for your comment!
First, you have to have in mind that when people are talking about “AI” in industry and policymaking, they usually have mostly non-deep learning or vision deep learning techniques in mind simply because they mostly don’t know the ML academic field but they have heard that “AI” was becoming important in industry. So this sentence is little evidence that Russia (or any other country) is trying to build AGI, and I’m at ~60% Putin wasn’t thinking about AGI when he said that.
If anyone who could play any role at all in developing AGI (or uncontrollable AI as I prefer to call it) isn’t trying to develop it by now, I doubt very much that any amount of public communication will change that.
I think that you’re deeply wrong about this. Policymakers and people in industry, at least till ChatGPT had no idea what was going on (e.g at the AI World Summit, 2 months ago very few people even knew about GPT-3). SOTA large language models are not really properly deployed, so nobody cared about them or even knew about them (till ChatGPT at least). The level of investment right now in top training runs probably doesn’t go beyond $200M. The GDP of the US is 20 trillion. Likewise for China. Even a country like France could unilaterally put $50 billion in AGI development and accelerate timelines quite a lot within a couple of years.
Even post ChatGPT, people are very bad at projecting what it means for next years and still have a prior on the fact that human intelligence is very specific and can’t be beaten which prevents them from realizing all the power of this technology.
I really strongly encourage you to go talk to actual people from industry and policy to get a sense of their knowledge on the topic. And I would strongly recommend not publishing your book as long as you haven’t done that. I also hope that a lot of people who have thought about these issues have proofread your book because it’s the kind of thing that could really increase P(doom) substantially.

I think that to make your point, it would be easier to defend the line that “even if more governments got involved, that wouldn’t change much”. I don’t think that’s right because if you gave $10B more to some labs, it’s likely they’d move way faster. But I think that it’s less clear.
a common, clear understanding of the dangers
I agree that it would be something good to have. But the question is: is it even possible to have such a thing?
I think that within the scientific community, it’s roughly possible (but then your book/outreach medium must be highly targeted towards that community). Within the general public, I think that it’s ~impossible. Climate change, which is a problem which is much easier to understand and explain is already way too complex for the general public to have a good idea of what are the risks and what are the promising solutions to these risks (e.g. a lot people’s top priorities is to eat organic food, recycle and decrease plastic consumption).
I agree that communicating with the scientific community is good, which is why I said that you should avoid publicizing only among “the general public”. If you really want to publish a book, I’d recommend targeting the scientific community, which is not at all the same public as the general public.
“On the other hand, if most people think that strong AI poses a significant risk to their future and that of their kids, this might change how AI capabilities researchers are seen, and how they see themselves”
I agree with this theory of change and I think that it points a lot more towards “communicate in the ML community” than “communicate towards the general public”. Publishing great AI capabilities is mostly cool for other AI researchers and not that much for the general public. People in San Francisco (where most of the AGI labs are) also don’t care much about the general public and whatever it thinks ; the subculture there and what is considered to be “cool” is really different from what the general public thinks is cool. As a consequence, I think they mostly care about what their peers are thinking about them. So if you want to change the incentives, I’d recommend focusing your efforts on the scientific & the tech community.

simeon_c 20 Dec 2022 10:01 UTC
5 points
2 ∶ 1
in reply to: alex lawsen (previously alexrjl)’s comment on: AGI Timelines in Governance: Different Strategies for Different Timeframes
Thanks for your comment!
That’s an important point that you’re bringing up.
My sense is that at the movement level, the consideration you bring up is super important. Indeed, even though I have fairly short timelines, I would like funders to hedge for long timelines (e.g. fund stuff for China AI Safety). Thus I think that big actors should have in mind their full distribution to optimize their resource allocation.
That said, despite that, I have two disagreements:
1. I feel like at the individual level (i.e. people working in governance for instance, or even organizations), it’s too expensive to optimize over a distribution and thus you should probably optimize with a strategy of “I want to have solved my part of the problem by 20XX”. And for that purpose, identifying the main characteristics of the strategic landscape at that point (which this post is trying to do) is useful.
2. “the EV gained in the worlds where things move quickly is not worth the expected cost in worlds where they don’t.” I disagree with this statement, even at the movement level. For instance I think that the trade-off of “should we fund this project which is not the ideal one but still quite good?” is one that funders often encounter and I would expect that funders have more risk adverseness than necessary because when you’re not highly time-constrained, it’s probably the best strategy (i.e. in every fields except in AI safety, it’s probably a way better strategy to trade-off a couple of years against better founders).
Finally, I agree that “the best strategies will have more variance” is not a good advice for everyone. The reason I decided to write it rather than not is because I think that the AI governance community tends to have a too high degree of risk adverseness (which is a good feature in their daily job) which penalizes mechanically a decent amount of actions that are way more useful under shorter timelines.

simeon_c 18 Sep 2022 6:40 UTC
4 points
0 ∶ 0
on: Forecasting thread: How does AI risk level vary based on timelines?
One of my friends and collaborators did this app which is aimed at predicting the likelihood that we go extinct: https://xriskcalculator.vercel.app/
It might be useful!

simeon_c 20 Aug 2022 14:19 UTC
2 points
0 ∶ 0
in reply to: JakubK’s comment on: Longtermists Should Work on AI—There is No “AI Neutral” Scenario
It was a way to say that if you think that intelligence is perfectly correlated with “morally good”, then you’re fine. But you’re right that it doesn’t include all the ways you could reject the orthogonality thesis

simeon_c 9 Aug 2022 9:30 UTC
3 points
0 ∶ 0
on: AMA: Ought
Why do you think your approach is better than working straight on alignment?