lukemarks

Karma: 455

lukemarks Jun 22, 2023, 12:25 PM
2 points
1
on: why I’m here now
I have enjoyed your writings both on LessWrong and on your personal blog. I share your lack of engagement with EA and with Hanson (although I find Yudkowsky’s writing very elegant and so felt drawn to LW as a result.) If not the above, which intellectuals do you find compelling, and what makes them so by comparison to Hanson/Yudkowsky?

lukemarks Jun 19, 2023, 8:04 AM
2 points
0
in reply to: NeuralSystem_e5e1’s comment on: Why I am not an AI extinction cautionista
In (P2) you talk about a roadblock for RSI, but in (C) you talk about about RSI as a roadblock, is that intentional?
This was a typo.
By “difficult”, do you mean something like, many hours of human work or many dollars spent? If so, then I don’t see why the current investment level in AI is relevant. The investment level partially determines how quickly it will arrive, but not how difficult it is to produce.
The primary implications of the difficulty of a capabilities problem in the context of safety is when said capability will arrive in most contexts. I didn’t mean to imply that the investment amount determined the difficulty of the problem, but that if you invest additional resources into a problem it is more likely to be solved faster than if you didn’t invest those resources. As a result, the desired effect of RSI being a difficult hurdle to overcome (increasing the window to AGI) wouldn’t be realized.

lukemarks Jun 19, 2023, 5:23 AM
1 point
0
in reply to: NeuralSystem_e5e1’s comment on: Why I am not an AI extinction cautionista
More like: (P1) Currently there is a lot of investment in AI. (P2) I cannot currently imagine a good roadblock for RSI. (C) Therefore, I have more reasons to believe RSI will not be entail atypically difficult roadblocks than I do to believe it will.

This is obviously a high level overview, and a more in-depth response might cite claims like the fact that RSI is likely an effective strategy for achieving most goals, or mention counterarguments like Robin Hanson’s, which asserts that RSI is unlikely due to the observed behaviors of existing >human systems (e.g. corporations).

lukemarks Jun 18, 2023, 10:10 PM
15 points
6
on: Why I am not an AI extinction cautionista
“But what if [it’s hard]/[it doesn’t]”-style arguments are very unpersuasive to me. What if it’s easy? What if it does? We ought to prefer evidence to clinging to an unknown and saying “it could go our way.” For a risk analysis post to cause me to update I would need to see “RSI might be really hard because...” and find the supporting reasoning robust.

Given current investment in AI and the fact that I can’t conjure a good roadblock for RSI, I am erring on the side of it being easier rather than harder, but I’m open to updating in light of strong counter-reasoning.

lukemarks Jun 11, 2023, 10:30 AM
2 points
0
in reply to: dr_s’s comment on: The Dictatorship Problem
See:
Defining fascism in this way makes me worry that future fascist figures can hide behind the veil of “But we aren’t doing x specific thing (e.g. minority persecution) and therefore are not fascist!”
And:
Is a country that exhibits all symptoms of fascism except for minority group hostility still fascist?

lukemarks Jun 11, 2023, 6:39 AM
1 point
0
in reply to: the gears to ascension’s comment on: The Dictatorship Problem
Agreed. I have edited that excerpt to be:
It’s not obvious to me that selection for loyalty over competence is necessarily more likely in fascism or bad. A competent figure who is opposed to democracy would be a considerably more concerning electoral candidate than a less competent one who is loyal to democracy assuming that democracy is your optimization target.

lukemarks Jun 11, 2023, 6:27 AM
4 points
0
in reply to: the gears to ascension’s comment on: The Dictatorship Problem
As in decreases the ‘amount of democracy’ given that democracy is what you were trying to optimize for.

lukemarks Jun 11, 2023, 3:44 AM
24 points
12
on: The Dictatorship Problem
Sam Altman, the quintessential short-timeline accelerationist, is currently on an international tour meeting with heads of state, and is worried about the 2024 election. He wouldn’t do that if he thought it would all be irrelevant next year.
Whilst I do believe Sam Altman is probably worried about the rise of fascism and its augmenting by artificial intelligence, I don’t see this as evidence of his care regarding this fact. Even if he believed a rise in fascism had no likelihood of occurring; it would still be beneficial for him to pursue the international tour as a means of minimizing x-risks, assuming even that we would see AGI in the next <6 months.
[Facism is] a system of government where there are no meaningful elections; the state does not respect civil liberties or property rights; dissidents, political opposition, minorities, and intellectuals are persecuted; and where government has a strong ideology that is nationalist, populist, socially conservative, and hostile to minority groups.
I doubt that including some of the conditions toward the end makes for a more useful dialogue. Irrespective of social conservatism and hostility directed at minority groups, the risk of fascism existentially is probably quite similar. I can picture both progressive and conservative dictatorships reaching essentially all AI x-risk outcomes. Furthermore, is a country that exhibits all symptoms of fascism except for minority group hostility still fascist? Defining fascism in this way makes me worry that future fascist figures can hide behind the veil of “But we aren’t doing x specific thing (e.g. minority persecution) and therefore are not fascist!”
My favored definition, particularly for discussing x-risk would be more along the lines of the Wikipedia definition:
Fascism is a far-right, authoritarian, ultranationalist political ideology and movement, characterized by a dictatorial leader, centralized autocracy, militarism, forcible suppression of opposition, belief in a natural social hierarchy, subordination of individual interests for the perceived good of the nation and race, and strong regimentation of society and the economy.
But I would like to suggest a re-framing of this issue, and claim that the problem of focus should be authoritarianism. What authoritarianism is is considerably clearer than what fascism is, and is more targeted in addressing the problematic governing qualities future governments could possess. It doesn’t appear obvious to me that a non-fascist authoritarian government would be better at handling x-risks than a fascist one, which is contingent on the fact that progressive political attitudes don’t seem better at addressing AI x-risks than conservative ones (or vice versa). Succinctly, political views look to me to be orthogonal to capacity in handling AI x-risk (bar perspectives like anarcho-primitivism or accelerationism that strictly mention this topic in their doctrine).
AI policy, strategy, and governance involves working with government officials within the political system. This will be very different if the relevant officials are fascists, who are selected for loyalty rather than competence.
It’s not obvious to me that selection for loyalty over competence is necessarily more likely in fascism or bad. A competent figure who is opposed to democracy would be a considerably more concerning electoral candidate than a less competent one who is loyal to democracy assuming that democracy is your optimization target.
A fascist government will likely interfere with AI development itself, in the same way that the COVID pandemic was a non-AI issue that nonetheless affected AI engineers.
Is interference with AI development necessarily bad? We can’t predict the unknown unknown of what views on AI development fascist dictatorship (that mightn’t yet exist) might hold or how they will act on them. I agree that on principal a fascist body interfering with industry does obviously not result in good outcomes in most cases but not see how/why this appeals to AI x-risk specifically.

lukemarks Jun 3, 2023, 5:50 AM
1 point
0
in reply to: Logan Zoellner’s comment on: The AGI Race Between the US and China Doesn’t Exist.
While it’s true that Chinese semiconductor fabs are a decade behind TSMC (and will probably remain so for some time), that doesn’t seem to have stopped them from building 162 of the top 500 largest supercomputers in the world.
They did this (mostly) before the export regulations were instantiated. I’m not sure what the exact numbers are, but both of their supercomputers in the top 10 were constructed before October 2022 (when they were imposed). Also, I imagine that they still might have had a steady supply of cutting edge chips soon after the export regulations. It would make sense that they were not enacted immediately and also that exports that had already begun hadn’t been ceased, but I have not verified that.

lukemarks May 31, 2023, 10:00 PM
9 points
2
on: The Divine Move Paradox & Thinking as a Species
Sure, this is an argument ‘for AGI’, but rarely do people (on this forum at least) reject the deployment of AGI because they feel discomfort in not fully comprehending the trajectory of their decisions. I’m sure that this is something most of us ponder and would acknowledge is not optimal, but if you asked the average LW user to list the reasons they were not for the deployment of AGI, I think that this would be quite low on the list.

Reasons higher on the list for me for example would be “literally everyone might die.” In light of that; dismissing control loss as a worry seems quite miniscule. The reason people fear control loss is generally because losing control of something more intelligent than you with instrumental subgoals that if pursued would probably result in a bad outcome for you, but this doesn’t change the fact that “we shouldn’t fear not being in control for the above reasons” does not constitute sufficient reason to deploy AGI.

Also, although some of the analogies drawn here do have merit; I can’t help but gesture toward the giant mass of tentacles and eyes you are applying them to. To make this more visceral, picture a literal Shoggoth descending from a plane of Eldlitch horror and claiming decision-making supremacy and human-aligned goals. Do you accept its rule because of its superior decision making supremacy and claimed human-aligned, or do you seek an alternative arrangement?

lukemarks May 25, 2023, 10:39 AM
4 points
1
in reply to: nicholashalden’s comment on: Adumbrations on AGI from an outsider
Soft upvoted your reply, but have some objections. I will respond using the same numbering system you did such that point 1 in my reply will address point 1 of yours.
1. I agree with this in the context of short-term extinction (i.e. at or near the deployment of AGI), but would offer that an inability to remain competitive and loss of control is still likely to end in extinction, but in a less cinematic and instantaneous way. In accordance with this, the potential horizon for extinction-contributing outcomes is expanded massively. Although Yudkowsky is most renowned for hard takeoff, soft takeoff has a very differently shaped extinction-space and (I would assume) is a partial reason for his high doom estimate. Although I cannot know this for sure, I would imagine he has a >1% credence in soft takeoff. ‘Problems with the outcome’ seem highly likely to extend to extinction given time.
2. There are (probably) an infinite number of possible mesa-optimizers. I don’t see any reason to assume an upper bound on potential mesa-optimization configurations, and yes; this is not a ‘slam dunk’ argument. Rather, as derived from the notion that even slightly imperfect outcomes can extend to extinction, I was suggesting that you are trying to search an infinite space for a quark that fell out of your pocket some unknown amount of time ago whilst you were exploring said space. This can be summed up as ‘it is not probable that some mesa-optimizer selected by gradient descent will ensure a Good Outcome’.
3. This still does not mean that the only form of brain hacking is via highly immersive virtual reality. I recall the Tweet that this comment came from, and I interpreted it as a highly extreme and difficult form of brain hacking used to prove a point (the point being that if ASI could accomplish this it could easily accomplish psychological manipulation). Eliezer’s breaking out of the sandbox experiments circa 2010 (I believe?) are a good example of this.
4. Alternatively you can claim some semi-arbitrary but lower extinction risk like 35%, but you can make the same objections to a more mild forecast like that. Why is assigning a 35% probability to an outcome more epistemologically valid than a >90% probability? Criticizing forecasts based on their magnitude seems difficult to justify in my opinion, and critiques should rely on argument only.

lukemarks May 25, 2023, 6:34 AM
1 point
0
in reply to: Shmi’s comment on: Adumbrations on AGI from an outsider
The focus of the post is not on this fact (at least not in terms of the quantity of written material). I responded to the arguments made because they comprised most of the post, and I disagreed with them.

If the primary point of the post was “The presentation of AI x-risk ideas results in them being unconvincing to laypeople”, then I could find reason in responding to this, but other than this general notion, I don’t see anything in this post that expressly conveys why (excluding troubles with argumentative rigor, and the best way to respond to this I can think of is by refuting said arguments).

lukemarks May 25, 2023, 12:44 AM
3 points
1
on: Adumbrations on AGI from an outsider
I disagree with your objections.
“The first argument–paperclip maximizing–is coherent in that it treats the AGI’s goal as fixed and given by a human (Paperclip Corp, in this case). But if that’s true, alignment is trivial, because the human can just give it a more sensible goal, with some kind of “make as many paperclips as you can without decreasing any human’s existence or quality of life by their own lights”, or better yet something more complicated that gets us to a utopia before any paperclips are made”
This argument is essentially addressed by this post, and has many failure modes. For example, if you specify the superintelligence’s goal as the example you gave, it’s most optimal solution might be to cryopreserve the brain of every human in a secure location, and prevent any attempts an outside force could make at interfacing with them. You realize this, and so you specify something like “Make as many squiggles as possible whilst leaving humans in control of their future”, and the intelligence is quite smart and quite general, so it can comprehend the notion of what you want when you say “we want control of our future”, but then BayAreaAILab#928374 trains a superintelligence designed to produce squiggles without this limit and outcompetes the aligned intelligence, because humans are much less efficient than inscrutable matrices.
This is not even mentioning issues with inner alignment and mesa-optimizers. You start to address this with:
AGI-risk argument responds by saying, well, paperclip-maximizing is just a toy thought experiment for people to understand. In fact, the inscrutable matrices will be maximizing a reward function, and you have no idea what that actually is, it might be some mesa-optimizer
But I don’t feel as though your referencing to Eliezer’s Twitter loss drop fiasco and subsequent argument regarding GPU maximization successfully refutes claims regarding mesa-optimization. Even if GPU-maximizing mesa-optimization was intractable, what about the other potentially infinite number of possible mesa-optimizer configurations that result ?
You don’t know that human brains can be hacked using VR headsets; it has never been demonstrated that it’s possible and there are common sense reasons to think it’s not. The brain is an immensely complicated, poorly-understood organ. Applying a lot of computing power to that problem is very unlikely to yield total mastery of it by shining light in someone’s eyes
When Eliezer talks about ‘brain hacking’ I do not believe he means by dint of a virtual reality headset. Psychological manipulation is an incredibly powerful tool, and who else could manipulate humanity if not a superintelligence? Furthermore, if said intelligence models humans via simulating strategies, which that post argues is likely assuming large capabilities gaps between humanity and a hypothetical superintelligence.
As I said before, I’m very confused about how you get to >90% chance of doom given the complexity of the systems we’re discussing
The analogy of “forecasting the temperature of the coffee in 5 minutes” VS “forecasting that if left the coffee will get cold at some point” seems relevant here. Without making claims about the intricacies of the future state of a complex system, you can make high-reliability inferences about their future trajectories in more general terms. This is how I see AI x-risk claims. If the claim was that there was a 90% chance that a superintelligence will render humanity extinct and it will have some architecture x I would agree with you, but feel as though Eliezer’s forecast is general enough to be reliable.

lukemarks May 24, 2023, 10:09 PM
1 point
0
in reply to: simon’s comment on: Crunch Dynamics and Control Loss
Agreed. I will add a clarifying statement in the introduction.

lukemarks May 24, 2023, 10:07 PM
1 point
0
on: A rejection of the Orthogonality Thesis
So if the argument the OT proponents are making is that AI will not self-improve out of fear of jeopardising its commitment to its original goal, then the entire OT is moot, because AI will never risk self-improving at all.
This seems to me to apply only to self improvement that modifies the outcome of decision-making irrespective of time. How does this account for self improvement that only serves to make decision making more efficient?
If I have some highly inefficient code that finds the sum of two integers by first breaking them up into 10000 smaller decimal values, randomly orders them and then adds them up in serial, and I rewrite the code to do the same thing but in way less ops, I have self improved without jeopardizing my goal.
This kind of self improvement can still be fatal in the context of deceptively aligned systems.

lukemarks May 22, 2023, 1:14 PM
5 points
0
on: Distillation of Neurotech and Alignment Workshop January 2023
I agree with this post almost entirely and strong upvoted as a result. The fact that more effort has not been allocated to the neurotechnology approach already is not a good sign, and the contents of this post do ameliorate that situation in my head slightly. My one comment is that I disagree with this analysis of cyborgism:
Interestingly, Cyborgism appeared to diverge from the trends of the other approaches. Despite being consistent with the notion that less feasible technologies take longer to develop, it was not perceived to have a proportionate impact on AI alignment. Essentially, even though cyborgism might require substantial development time and be low in feasibility, its success wouldn’t necessarily yield a significant impact on AI alignment.
Central to the notion of cyborgism is an alternative prioritization of time. Whilst other approaches focus on deconfusing basic concepts central to their agenda or obtaining empirical groundings for their research, cyborgism opts to optimize for the efficiency of applied time during ‘crunch time’. Perhaps the application of neurotechnology to cyborgism mightn’t seem as obviously beneficial as say WBE relative to its feasibility, but cyborgism is composed of significantly more than just the acceleration of alignment via neurotechnology. I will attempt to make the case for why cyborgism might be the most feasible and valuable “meta-approach” to alignment and to the development of alignment-assisting neurotechnology.
Suitability to Commercialization
Cyborgism is inherently a commercializable agenda as it revolves around the production of tools for an incredibly cognitively-demanding task. Tools capable of accelerating alignment work are generally capable of lots of things. This makes cyborgist research suited to the for-profit structure, which has clear benefits for rapid development over alternative structures. This is invaluable in time-sensitive scenarios and elevates my credence in the high-feasibility of cyborgism.
Better Feedback Loops
Measuring progress in cyborgism is considerably more trivial than alternative approaches. Metrics like short-form surveys become an actual applicable metric for success, and proxies like “How much do you feel this tool has accelerated your alignment work” are useful sources of information that can be turned into quantifiable progress metrics. This post is an example of that. Furthermore, superior tools can not only accelerate alignment work but also tool development. As cyborgism has a much broader scope than just neurotechnology, you could differentially accelerate higher value neurotechnological or otherwise approaches with the appropriate toolset. It may be better to invest in constructing the tools necessary to perform rapid neurotechnology research at GPT-(N-1) than it is to establish foundational neurotechnology research now at a relatively lower efficiency.
Broad Application Scope
I find any statement like “cyborgism is/isn’t feasible” to be difficult to support due mainly to the seemingly infinite possible incarnations of the agenda. Although the form of AI-assisted-alignment described in the initial cyborgism post is somewhat specific, other popular cyborgism writings describe more varied applications. It seems highly improbable that we will not see something remotely “cyborg-ish” and that some cyborgish acts will not affect existential risk posed by artificial intelligence, which makes it difficult from my perspective to make claims like that which I instantiated this paragraph with. The primary question to me seems to be more of the kind “how heavily do we lean into cyborgism?”, or more practically “what percentage of resources do we allocate toward efficiency optimization as opposed to direct alignment/neurotechnology research?”.
My personal preference is to treat cyborgism as more of a “meta-agenda” than as an agenda itself. Shifting toward this model of it impacted how I see its implications for other agendas quite significantly, and has increased my credence in its feasibility substantially.
Also, as a side note; I think that the application of neurotechnology to cyborgism is quite non-obvious. “Use neurotechnology as a more efficient interface between tools and their human user” and “use invasive BCI technology to pursue the hardest form of cyborgism” are exceedingly different in nature, and as a result contribute to the difficulty of assessing the approach due in large to the reasons that drove me to classify it more as a meta-agenda.

lukemarks May 18, 2023, 8:35 AM
3 points
0
in reply to: Nathan Helm-Burger’s comment on: (Slightly) Scalable RLHF Alternatives: A Productive Path for Slow Takeoff Worlds?
Agreed and edited.

lukemarks May 17, 2023, 3:29 AM
5 points
1
in reply to: pjeby’s comment on: AI Will Not Want to Self-Improve
I disagree with your framing of the post. I do not think that this is wishful thinking.
The first and most obvious issue here is that an AI that “solves alignment” sufficiently well to not fear self-improvement is not the same as an AI that’s actually aligned with humans. So there’s actually no protection there at all.
It is not certain that upon deployment the first intelligence capable of RSI will be capable of solving alignment. Although this seems improbable in accordance with more classic takeoff scenarios (i.e. Yudkowsky’s hard takeoff), the likelihood of those outcomes has been the subject of great debate. I feel as though someone could argue for the claim “it is more likely than not that there will be a period of time in which AI is capable of RSI but not of solving alignment”. The arguments in this post seem to me quite compatible with e.g. Jacob Cannell’s soft(er) takeoff model, or many of Paul Christiano’s takeoff writings.
In fact, the phenomenon described here seems to make it more likely that an unaligned AI will be fine with self-improving, because the simpler the utility function the easier time it has guaranteeing the alignment of the improved version!
Even with your model of solving alignment before or at the same time as RSI becomes feasible, I do not think that this holds well. As far as I can tell, the simplicity of the utility function a general intelligence could be imbued with doesn’t obviously impact the difficulty of alignment. My intuition is that attempting to align an intelligence with a utility function dependent on 100 desiderata is probably not that much easier than trying to align an intelligence with a utility function dependent on 1000. Sure, it is likely more difficult, but is utility function complexity realistically anywhere near as large a hurdle as say robust delegation?
Last, but far from least, self-improvement of the form “get faster and run on more processors” is hardly challenging from an alignment perspective. And it’s far from unlikely an AI could find straightforward algorithmic improvements that it could mathematically prove safe relative to its own utility function.
This in my opinion is the strongest claim, and is in essence quite similar to this post, my response to which was “I question the probability of a glass-box transition of type “AGI RSIs toward non-DL architecture that results in it maximizing some utility function in a pre-DL manner” being more dangerous than simply “AGI RSIs”. If behaving like an expected utility maximizer was optimal: would not AGI have done so without the architecture transition? If not, then you need to make the case for why glass-box architectures are better ways of building cognitive systems. I think that this argument is at odds with the universal learning hypothesis and seems more in-line with evolved modularity, which has a notoriously poor mapping to post-DL thinking. ULH seems to suggest that actually modular approaches might be inferior efficiency-wise to universal learning approaches, which contradicts the primary motive a general intelligence might have to RSI in the direction of a glass-box architecture.”
In summary: Although it seems probable to me that algorithmic approaches are superior for some tasks, it seems to me that ULH would imply that the majority of tasks are best learned by a universal learning algorithm.

lukemarks May 10, 2023, 10:10 PM
2 points
0
on: AGI-Automated Interpretability is Suicide
Strong upvoted this post. I think the intuition is good and that architecture shifts invalidating anti-foom arguments derived from the nature of the DL paradigm is counter-evidence to those arguments, but simultaneously does not render them moot (i.e. I can still see soft takeoff as described by Jacob Cannell to be probable and assume he would be unlikely to update given the contents of this post).

I might try and present a more formal version of this argument later, but I still question the probability of a glass-box transition of type “AGI RSIs toward non-DL architecture that results in it maximizing some utility function in a pre-DL manner” being more dangerous than simply “AGI RSIs”. If behaving like an expected utility maximizer was optimal: would not AGI have done so without the architecture transition? If not, then you need to make the case for why glass-box architectures are better ways of building cognitive systems. I think that this argument is at odds with the universal learning hypothesis and seems more in-line with evolved modularity, which has a notoriously poor mapping to post-DL thinking. ULH seems to suggest that actually modular approaches might be inferior efficiency-wise to universal learning approaches, which contradicts the primary motive a general intelligence might have to RSI in the direction of a glass-box architecture.

lukemarks May 7, 2023, 10:00 PM
1 point
0
in reply to: ChristianKl’s comment on: Mass Communication About AI X-Risk Via… A Very Large Email?
I agree with some of this as a crticism of the idea, but not of the post. Firstly, I stated the same risk you did in the introduction of the post, hence the communication was “Here is an idea, but it has this caveat”, and then the response begins with “but it has this caveat”.

Next, if the ‘bad outcome’ scenario looks like most or all parties that receive the email ignoring it/not investigating further, then I see such an email as easily justifiable to send, as it is a low-intensity activity labour-wise with the potential to expand knowledge of x-risks posed by AI. Obviously this isn’t the upper bound for the negativity of the outcome of sending an email like this, as you and I both pointed out a worse alternative, but as outlined in the post, I believe this can be accounted for via an iterative drafting process (like the one I am trying to initiate by sharing the draft above) and handling communications like this with care.

I agree with the assertion regarding consulting a PR professional (and I think this is another reason to delegate the task to a willing organization with access to resources like this).

As for the critique of the email itself, I agree that omitting that sentence improves the conciseness of the email, but that sequence of six words doesn’t make the entire email contents not concise. Also, feedback like this was my primary motivation for sharing a draft.

I disagree with your final remark regarding email communication. Email is the single digital communication medium shared by almost every company and individual on the planet and is the medium most likely to be selected as an open contact method on the website of a journalist/media company. Furthermore, communication via email is highly scalable, which is a critical factor in mass communication. Sure, I cannot prove that email is undoutably the most superior form of communication for this task (and thus by definition the conjecture is subject to the criticism you posed), but I can (and hope I just did) make a case supporting my intuition. I’m not sure by what other means than my best intellectual effort and discussion with others you could want when justifying the use of a communication method. Are you looking for a formal proof?

lukemarks

Suitability to Commercialization

Better Feedback Loops

Broad Application Scope