bokov

Karma: 103

bokov 25 Sep 2025 20:57 UTC
1 point
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in reply to: bokov’s comment on: Are You More Real If You’re Really Forgetful?
What if my utility function is keeping alive and flourishing this one specific instance of myself, connected in an unbroken sequential chain to every previous instance? Does actual trade have anything to offer me or can I safely ignore it completely and go on with my life?

bokov 25 Sep 2025 20:50 UTC
1 point
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on: Are You More Real If You’re Really Forgetful?
Am I in the minority for thinking that this is fun and clever but absolutely irrelevant to, e.g. you not dying? Why is being indistinguishable conflated with being the same? And even if you were, by that line of reasoning don’t you stop being the same as soon as one of you dies? Why even assign non epsilon probability to Tegmark universes existing? What observation is better explained or predicted if one assumes Tegmark universes?

I’m not trying to be a jerk. This and acausal trade are the two things on LW that make absolutely no sense to me and seen to be in stark contradiction with the rest of rationalism and from time to time I try to get someone to convince me that I’m wrong. This must be my latest attempt.

bokov 15 Jan 2025 17:09 UTC
1 point
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in reply to: bokov’s comment on: My latest attempt to understand decision theory: I asked ChatGPT to debate me.
The closest I can come to examples might be ones where the two-box outcome is so much worse then the one-box outcome that I have nothing to lose by choosing the path of hope.

E.g. picking one box even though I and everybody else knows I’m a two-boxer if I believe that in this case two-boxing will kill me

Or, cooperating when both unilateral defection, unilateral cooperation, and mutual defection have results vastly worse than mutual cooperation.

Are these on the right track?

bokov 15 Jan 2025 16:54 UTC
1 point
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in reply to: bokov’s comment on: My latest attempt to understand decision theory: I asked ChatGPT to debate me.
Because, based on the behavior of people here whose intelligence and ideas I have come to respect, this is an important topic.

Clearly I completely lack the background to understand the full theoretical argument. I also lack the background to understand the full theoretical argument behind general relatively and quantum uncertainty. Yet there are many real-world practical examples that I do understand and can work backwards from to get a roughly correct intuition about these ideas.

Every example I have seen for CDT falling short has been a hypothetical scenario that almost certainly never happened.

But if the only scenarios where CDT is a dominated strategy are hypothetical ones, I wouldn’t expect smart people on LW to spend so much time and energy on them.

bokov 15 Jan 2025 16:42 UTC
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in reply to: Vladimir_Nesov’s comment on: My latest attempt to understand decision theory: I asked ChatGPT to debate me.
Thank you for responding to my post despite its negative rating.

Can you, as a human, give any practical real-world examples that do not rely on non-existent tech where anything outperforms non-naive CDT?

By non-naive I mean CDT that isn’t myopically just trying to maximize the immediate payoff but rather trying to maximize the long term value to the player into account future interactions, reputation, uncertainty about causal relationships, etc.

My latest attempt to understand decision theory: I asked ChatGPT to debate me.

bokov13 Jan 2025 19:37 UTC

−8 points

5 comments19 min readLW link

bokov 13 Jan 2025 18:36 UTC
1 point
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in reply to: RHollerith’s comment on: What to do if a nuclear weapon is used in Ukraine?
In other words, what Putin has already been doing more and more, but with a specific deadline attached?

bokov 13 Dec 2024 0:17 UTC
1 point
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on: What to do if a nuclear weapon is used in Ukraine?
Perhaps we should brainstorm leading indicators of nuclear attack.

bokov 22 Nov 2024 18:31 UTC
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in reply to: AprilSR’s comment on: Acausal normalcy
I always found that aspect weak. It is clearly and sadly evident that utility pessimization (I assume roughly synonymous with coercion?) is effective and stable, both on Golarion and Earth. Yet half the book seems to be gesturing at what a suboptimal strategy it is without actually spelling out how you can defeat an agent who pursues such a strategy (without having magic and some sort of mysterious meta-gods on your side).

bokov 22 Nov 2024 18:22 UTC
1 point
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in reply to: bokov’s comment on: Acausal normalcy
Update:
I went and read the background material on acausal trade and narrowed even further where it is I’m confused. It’s this paragraph:

> Another objection: Can an agent care about (have a utility function that takes into account) entities with which it can never interact, and about whose existence it is not certain? However, this is quite common even for humans today. We care about the suffering of other people in faraway lands about whom we know next to nothing. We are even disturbed by the suffering of long-dead historical people, and wish that, counterfactually, the suffering had not happened. We even care about entities that we are not sure exist. For example: We might be concerned by news report that a valuable archaeological artifact was destroyed in a distant country, yet at the same time read other news reports stating that the entire story is a fabrication and the artifact never existed. People even get emotionally attached to the fate of a fictional character.

My problem is lack of evidence that genuine caring about entities with which one can never interact really is “quite common even for humans today”, after factoring out indirect benefits/costs and social signalling.

How common, sincerely felt, and motivating should caring about such entities be for acausal trade to work?

Can you still use acausal trade to resolve various game-theory scenarios with agents whom you might later contact while putting zero priority on agents that are completely causally disconnected from you? If so, then why so much emphasis on permanently un-contactable agents? What does it add?
What links here?
- My latest attempt to understand decision theory: I asked ChatGPT to debate me. by bokov (13 Jan 2025 19:37 UTC; -8 points)

bokov 22 Nov 2024 17:53 UTC
4 points
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on: Acausal normalcy
Acausally separate civilizations should obtain our consent in some fashion before invading our local causal environment with copies of themselves or other memes or artifacts.
Aha! Finally, there it is, a statement that exemplifies much of what I find confusing about acausal decision theory.

1. What are acausally separate civilizations? Are these civilizations we cannot directly talk to and so we model their utility functions and their modelling of our utility functions etc. and treat that as a proxy for interviewing them?

2. Are these civilizations we haven’t met yet but might someday, or are these ones that are impossible for us to meet even in theory (parallel universes, far future, far past, outside our Hubble volume, etc.)? Because other acausal stuff I’ve read seems to imply the latter in which case...

2a. If I don’t care what civilizations do (to include “simulating” me) unless it’s possible for me or people I care about to someday meet them, do I have any reason to care about acausal trade?

3. Can you give any specific examples of what it would be like for an acausally separate civilization to invade our local causal environment which do NOT depend in any way on simulations?

4. I heard that acausal decision theory has practical applications in geopolitics, though unfortunately without any real-world examples. Do you know any concrete examples of using acausal trade or acausal norms to improve outcomes when dealing with ordinary physical people whom you cannot directly communicate?

I realize you probably have better things to do than educating an individual noob about something that seems to be common knowledge on LW. For what it’s worth, I might be representative of a larger group of people who are open to the idea of acausal decision theory but who cannot understand existing explanations. You seem like an especially down-to-earth and accessible proponent of acausal decision theory, and you seem to care about it enough to have written extensively about it. So if you can help me bridge the gap to fully getting what it’s about, it may help both of us become better at explaining it to a wider audience.

bokov 22 Nov 2024 17:20 UTC
1 point
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on: Acausal normalcy
What is meant by ‘reflecting’?
- reflecting on {reflecting on whether to obey norm x, and if that checks out, obeying norm x} and if that checks out, obeying norm x
Is this the same thing as saying “Before I think about whether to obey norm x, I will think about whether it’s worth thinking about it and if both are true, I will obey norm x”?

bokov 22 Nov 2024 17:18 UTC
3 points
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on: Acausal normalcy
I’ve been struggling to understand acausal trade and related concepts for a long time. Thank you for a concise and simple explanation that almost gets me there, I think...

Am I roughly correctly in the following interpretation of what I think you are saying?

Acausal norms amount to extrapolating the norms of people/aliens/AIs/whatever whom we haven’t met yet and know nothing about other than what can be inferred from us someday meeting them. If we can identify norms that are likely to generalize to any intelligent being capable of contact and negotiation and not contingent on any specific culture/biology/happenstance, then we can pre-emptively obey those norms to maximize the probability of a good outcome when we do meet these people/aliens/AIs/whatever?

bokov 20 Sep 2024 18:03 UTC
2 points
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in reply to: lc’s comment on: My simple AGI investment & insurance strategy
Would you mind sharing how you allocated the ratio of these positions?

bokov 20 Sep 2024 17:37 UTC
2 points
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in reply to: Decaeneus’s comment on: My simple AGI investment & insurance strategy
Maybe the key is not to assume the entire economy will win, but make some attempt to distinguish winners from losers and then find ETFs and other instruments that approximate these sectors.

So, some wild guesses...
- AI labs and their big-tech partners: winners
- Cloud hosting: winners
- Commercial real estate specializing in server farms: winners
- Whoever comes up with tractable ways to power all these server farms: winners
- AI-enabling hardware companies: winners until the Chinese blockade Taiwan and impose an embargo on raw materials… after that… maybe losers except the ones that have already started diversifying their supply-chains?
- Companies which inherently depend on aggregating and reselling labor: tricky, because if they do nothing, they’re toast, but some of them can turn themselves into resellers of AI… e.g. a temp agency rolling out AI services as a cheaper product line
- Professional services: same as above but less exposed
- Businesses that are needed only in proportion to other businesses having human employees: travel, office real estate, office furniture and supplies: losers
As the effects ripple out and more and more workers are displaced...
- Low to mid-end luxury goods and eventually anything that depends on mass discretionary spending: losers
Though what I really would like to do is create some sort of rough model of an individual non-AI company with the following parameters:
- Recurring costs attributable to employees
- Other recurring costs
- Revenue
- Fraction of employees whose jobs can be automated at the current state of the art
- Variables representing of how far along this company is in planning or implementing AI-driven consolidation and how quickly it is capable of cutting over to AI
- Fixed costs of cut-over to AI
- Variable costs of cut-over to AI (depending on aggregate workload being automated)
- Whatever other variables people who unlike me actually know something about fundamental analysis would put in such a model.
...and then be able to make a principled guess about where on the AI-winners vs AI-losers spectrum a given company is. I even started sketching out a model like this until I realized that someone with relevant expertise must have already written a general-purpose model of this sort and I should find it and adapt it to the AI-automation scenario instead of making up my own.

bokov 20 Sep 2024 17:00 UTC
5 points
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on: My simple AGI investment & insurance strategy
I’m trying out this strategy on Investopedia’s simulator (https://www.investopedia.com/simulator/trade/options)

The January 15 2027 call options on QQQ look like this as of posting (current price 481.48):

Strike Black-Scholes Ask

485 64.244 77.4

500 57.796 69.83

… … …

675 14.308 14

680 13.693 13.5

685 13.077 12.49

… … …

700 11.446 10.5

… … …

720 9.702 8.5

So, if you were following this strategy and buying today, would you buy 485 because it has the lowest OOM strike price? Would you buy 675 because it’s the lowest strike price where the ask is lower than the theoretical Black-Sholes fair price? Would you go for 720 because it’s the cheapest available? Would you look for the out-of-money option with the largest difference between Black-Sholes and the ask?

What would be your thought process? I’m definitely hoping to hear from @lc but am interested in hearing from anybody who found this line of reasoning worth investigating and has opinions about it.

Strike	Black-Scholes	Ask
485	64.244	77.4
500	57.796	69.83
…	…	…
675	14.308	14
680	13.693	13.5
685	13.077	12.49
…	…	…
700	11.446	10.5
…	…	…
720	9.702	8.5

bokov 20 Sep 2024 1:30 UTC
1 point
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on: My simple AGI investment & insurance strategy
So, how can we improve this further?

Some things I’m going to look into, please tell me if it’s a waste of time:
- Seeing if there are any REITs that specialize in server farms or chip fabs and have long-term options
- Apparently McKinsey has a report about what white-collar jobs are most amenable to automation. Tracking down this report (they have lots) if it’s not paywalled or at least learning enough about it to get the gist of which (non-AI) companies would save the most money by “intelligent automation”.
  - From first principles I’d expect companies/industries which have a large proportion of their operating expenses going to salaries and benefits as the first in line to automate.
  - Industries that are essentially aggregators and resellers of labor would have to do this to survive at all
  - ...and the ones among them that lag in AI adoption would be candidates for short positions

bokov 19 Sep 2024 22:35 UTC
1 point
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on: My simple AGI investment & insurance strategy
A risk I see is China blockading Taiwan and/or limiting trade with the US and thus slowing AI development until a new equilibrium is reached through onshoring (and maybe recycling or novel sources of materials or something?)

On the other hand maybe even the current LLMs already have the potential to eliminate millions of jobs and it’s just going to take companies a while to do the planning and integration work necessarily to actually do it.

So one question is, will the resulting increase in revenue offset the revenue losses from a proxy war with China?

bokov 4 Jun 2024 20:14 UTC
1 point
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in reply to: ChristianKl’s comment on: Is it time to talk about AI doomsday prepping yet?
I guess scenarios where humans occupy a niche analogous to animals that we don’t value but either cannot exterminate or choose not to.

bokov 4 Jun 2024 18:33 UTC
1 point
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on: Another attempt to explain UDT
Parfitt’s Hitchhiker and transparent Newcomb: So is the interest in UDT motivated by the desire for a rigorous theory that explains human moral intuitions? Like, it’s not enough that feelings of reciprocity must have conveyed a selective advantage at the population level, we need to know whether/how they also are net beneficial to the individuals involved?

bokov

My lat­est at­tempt to un­der­stand de­ci­sion the­ory: I asked ChatGPT to de­bate me.

My latest attempt to understand decision theory: I asked ChatGPT to debate me.