yooo x-risk is a cult you should get out while you can <3
beth
Three Biases That Made Me Believe in AI Risk
It is most apparent in this piece of the review:
He also points out that Tanzanian natives using their traditional farming practices were more productive than European colonists using scientific farming. I’ve had to listen to so many people talk about how “we must respect native people’s different ways of knowing” and “native agriculturalists have a profound respect for the earth that goes beyond logocentric Western ideals” and nobody had ever bothered to tell me before that they actually produced more crops per acre, at least some of the time. That would have put all of the other stuff in a pretty different light.
He remains focused on the expected crops per acre, even though every case study in the book illustrates that such a single variable doesn’t encompass the multitude of uses that the acre in question has. I don’t think I could describe it better than Reddit user u/TheHiveMindSpeaketh does:
The point of the book is not to point and laugh at the technocrats who failed to squeeze the most X out of Y because they didn’t listen to the noble savages. The point is that ‘how do we squeeze the most X out of Y’ is a bad way to position yourself in relation to your surroundings. The point is that technocrats often succeed in squeezing more X out of Y over a relevant period of time via their techniques, but that treating a forest like a timber-maximizer is already missing the [..] point because a forest is also a home for woodland creatures, and a source for medicinal herbs and fruits and berries, and a nice place to take a hike and stare at the stars. The point is that the mistake was not made at the level of what was implemented, the mistake was made at the level of what was valued, and the implementation mistake was an inevitable downstream consequence of that. The point is that even if traditional Tanzanian farming methods didn’t produce more crops per acre, they might still be preferable, because they are more sustainable or less time-intensive or etc, but that these benefits become unintelligible to the technocrat who has already committed to a value system where land is only judged by its yield per acre.
I personally think this is an important question for EA’s to grapple with: can we reason abstractly about doing good without this abstraction causing mistakes at the level of what to value. Scott’s technocrats surely did not think they were making that mistake, but they were. If we believe that we are somehow different, that is kind of arrogant.
Just in the past weeks, San Francisco, Oakland and Cambridge.
ahead of their time, in the sense that if they hadn’t been made by their particular discoverer, they wouldn’t have been found for a long time afterwards?
This definition is surprisingly weak, and in fact includes some scientific results that were way past their time. One striking example is Morley’s trisector theorem, which is an elegant fact in Euclidean 2d geometry which had been overlooked for 2000 years. If not for Morley, this fact might have remained unknown for millennia longer.
Are there any plans to evaluate the current karma system? Both the OP and multiple comments expressed worries about the announced scoring system, and in the present day we regularly see people complain about voting behaviour. It would be worth knowing if the concerns from a year ago turn out to have been correct.
Related to this, I have a feature request. Would it be possible to break down scores in a more transparent way, for example by number of upvotes and downvotes? The current system gives very little insight to authors about how much people like their posts and comments. The lesson to learn from getting both many upvotes and many downvotes is very different from the lesson to learn if nobody bothered to read and vote on your content.
1. The mechanics of cryptographic attack and defense are more complicated that you might imagine. This is because (a) there is a huge difference between the attack capabilities of nations versus those of other maligne actors. Even if the NSA, with its highly-skilled staff and big budget, is able to crack your everyday TLS traffic, doesn’t mean that your bank transactions aren’t safe against petty internet criminals. And (b) state secrets typically need to be safe against computers of 20+ years in the future, as you don’t want enemy states to capture your traffic now and decrypt it as soon as slightly better hardware is available.
2. NIST is running a project at this moment to standardize a post-quantum cryptographical protocol. Cryptographers from many countries in the world are collaborating on this. The tentative timeline lists the completion of the draft standards in 2022-2024.
Hence, experts worldwide estimate that strong quantum computers will not be deployed even by intelligence agencies until well into the 2030s (e: 40′s). Consumer targets will stay safe for even longer than that.
As per my initial comment, I’d compare it to pre-WWII Netherlands banning government registration of religion. It could safe tens of thousands of people from deportation and murder.
it reflects a sentiment that effective altruism is not about one thing, about having the right politics, about saying the right things, about adopting groupthink, or any of the many other things we associate with ideology.
Can you expand a bit on this statement? I don’t see how you can say only other ideologies of being full of groupthink and having the right politics, even though most posts on the EA forum that don’t agree with the ideological tennets listed in the OP tends to get heavily downvoted. When I personally try to advocate against the idea that AI Safety is an effective cause, I experience quite some social disapproval for that within EA.
I think the points you’re complaining about affect EA just as much as any other ideology, but that they are hard to see when you are in the midst of it. Your own politics and groupthink don’t feel like politics and groupthink, they feel like that is the way the world is.
Let me try to illustrate this using an example. Plenty of people accuse any piece of popular media with a poc/female/lgbt protagonist as being overly political, seemingly thinking that white cishet male protagonists are the unique non-political choice. Whether you like this new trend or not, it is absurd to think that one position here is political and the other isn’t. But your own view always looks apolitical from the inside. For EA this phenomenon might be compounded by the fact that there is no singular opposing ideology.
My troubles with this method are two-fold.
1. SHA256 is a hashing-algorithm. Its security is well-vetted for certain kinds of applications and certain kinds of attacks, but “randomly distribute the first 10 hex-digits” is not one of those applications. The post does not include so much as a graph of the distribution of what the past drawing results would have been with this method, so CEA hasn’t really justified why the result would be uniformly distributed.
2. The least-significant digits in the IRIS data are probably fungible by adversaries. It is hard to check them, and IRIS has no reason to secure their data pipeline against attacks that might cost tens of thousands of dollars, because there are normally no stakes whatsoever attached to those bits.
Random.org is exactly in the business that we’re looking for, so they’d be a good option for their own institutional guarantee. Otherwise, any big lottery in any country will work as a source of randomness: the prizes there are bigger, which means that, even if these lotteries could be corrupted, nobody would waste that ability on rigging the donor lottery.
I don’t have any specific instances in mind.
Regarding your accounting of cases, that was roughly my recollection as well. But while the posts might not address the second concern directly, I don’t think that the two concerns are separable. The actual mechanisms and results might largely overlap.
Regarding the second concern you mention specifically, I would not expect those complaints to be written down by any users. Most people on any forum are lurkers, or at the very least they will lurk a bit to get a feel for what the community is like and what it values before participating. This makes people with oft-downvoted opinions self-select out of the community before ever letting us know that this is happening.
The hovering is helpful, thank you.
Can you make a case as to why the two have enough notability separately to deserve their own separate Wikipedia pages?
The EA forum doesn’t seem like an obvious best choice. Just because it is related to EA does not make it effective, especially considering the existence of discussion software like Reddit, Discourse, and phpBB.
I’d say it mostly depends on what kind of skills and career capital you are aiming for. There are a number of important (scientific) software packages with either zero or one maintainers, which could be useful to work on either upstream or downstream.
Personally, I am presently just doing (easy) fixes for bugs that I run into myself. But I am considering to either start officially maintaining a driver that I keep patching for my own use anyway or to contribute to some decentralized web project.
It might not be super relevant for you specifically, but I do want to plug Google Summer of Code for all university students of 18 years and older as a wonderful opportunity. (application deadline April 9th)
This is mostly a problem with an example you use. I’m not sure whether it points to an underlying issue of your premise:
You link to the exponential growth of transistor density. But that growth is really restricted to just that: transistor density. Growing your number of transistors doesn’t necessarily grow your capability to compute things you care about, both from a theoretical perspective (potential fundamental limits in the theory of computation) as well as a practical perspective (our general inability to write code that makes use of much circuitry at the same time + the need for dark silicon + Wirth’s law). Other numbers, like FLOP/s, don’t necessarily mean what you’d think either.
Moore’s law does not posit exponential growth in amount of “compute”. It is not clear that the exponential growth of transistor density translates to exponential growth of any quantity you’d actually care about. I think it is rather speculative to assume it does and even more so to assume it will continue to.
For a different take on the consequences of being “rational”, I would highly recommend James C. Scott’s book Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed. The book summary of SSC is pretty good, but when he gives his opinion on the book he seems to have missed the point of the book entirely.
Same for the unconference, should be this link.
Let me try to rephrase this part, as I consider it to be the main part of my argument and it doesn’t look like I managed to convey what I intended to:
AI Safety would be a worthy cause if a superintelligence were powerful and dangerous enough to be an issue but not so powerful and dangerous as to be uncontrollable.
The most popular cause evaluation framework within EA seems to be Importance/Neglectedness/Tractability. AI Safety enthusiasts tell a convincing story on importance and neglectedness being good and make an effort at arguing that tractability is as well.
But here is the thing: all arguments given in favour of AI being risky (to establish importance) can be rephrased as arguments against tractability. Similarly for neglectedness.
I’ll illustrate this with a caricature, but it takes little effort to transfer this line of thought to the real arguments being made. Let’s say the pro-AIS argument is “AGI will become infinitely smart, so it can out-think all humans and avoid all our security measures. Hence AGI is likely to escape any restrictions we put on it, so it will be able to tile the universe with paperclips if it wants to”. Obviously, if it can out smart any security measure, then no sufficient security exists, AI Safety research will never lead to anything and the problem is intractable.
AI Safety is only effective if you can simultaneously argue for each of importance/neglectedness/tractability without detracting from the others. Moreover, your arguments have to address the exact same scenarios. It is not enough for AIS to be important with 50% probability and tractable with 50% probability, these two properties have be likely to hold simultaneously. A coin flip has 50% probability of heads and 50% probability of tails, but they will never happen at the same time.
AI Safety can only be an effective cause (on the margin) if solving it is possible (tractability) but not trivial (importance/neglectedness). I think this is a narrow window to hit, and current arguments are all way off-target.
These are some issues that actively frustrate me to the point of driving me away from this site.
Loading times for most pages are unbearably slow. So are most animations (like the menu from clicking your username top right).
Many features break badly when Javascript is turned off.
Text field for bio is super small and cannot be rescaled.
Super upvotes have their use but the super downvote just encourages harsh voting behaviour.
The contrast on the collapse comment button is minimal, same for a number of other places.
Basic features take much effort to navigate to. Going to all posts either means two clicks (hamburger menu then all posts) or clicking a link that can not always be seen without scrolling (which is a mess because the page height will change when recent comments have finished loading)
Regarding 1), if I were to guess which events of the past 100 years made the most positive impact on my life today, I’d say those are the defeat of the Nazis, the long peace, trans rights and women’s rights. Each of those carries a major socio-political dimension, and the last two arguably didn’t require any technological progress.
I very much think that socio-political reform and institutional change are more important for positive long-term change than technology. Would you say that my view is not empirically grounded?
Thank you for this nice summary of the argument in favour of AI Safety as a cause. I am not convinced, but I appreciate your write-up. As you asked for counterarguments, I’ll try to describe some of my gripes with the AI Safety field. Some have to do with how there seems to be little awareness of results in adjacent fields, making me doubt if any of it would stand up to scrutiny from people more knowledgeable in those areas. There are also a number of issues I have with the argument itself.
Where’s does it end? Well, eventually, at the theoretical limits of computation. These theoretical limits are very, very high—without even getting close to the limit, a 10kg computer could do more computation every hour than 10 billion human brains could do in a million years. (And a superintelligence wouldn’t be limited to just 10kg). At that point, we are talking about something that can essentially do anything that is allowed by the laws of physics—something so incredibly smart it’s comparable to a civilisation millions of years ahead of us.
The theoretical limits of computation are lower bounds, we don’t know if it is possible to achieve them for any kind of computation, let alone for general computation. Moreover, having a lot of computational power probably doesn’t mean that you can calculate everything. A lot of real-world problems are hard to approximate in a way that adding more computational power doesn’t meaningfully help you. For example, computing approximate Nash-equilibria or finding good lay-outs for microchip design. It is not clear that having a lot of computing power translates into relevant superior capabilities.
We don’t yet know how to program any high-level human concept like morality, love, or happiness—the difficulty is in nailing down the concept to the kind of mathematical language a computer can understand before it becomes superintelligent.
There is a growing literature on making algorithms fair, accountable and transparent. This is a collaborative effort between researchers in computer science, law and many other fields. There are so many similarities between this and the professed goals of the AI Safety community that it is strange that no cross-fertilization is happening.
The problem is Instrumental Convergence.
You can’t just ask the AI to “be good”, because the whole problem is getting the AI to do what you mean instead of what you ask. But what if you asked the AI to “make itself smart”? On the one hand, instrumental convergence implies that the AI should make itself smart. On the other hand, the AI will misunderstand what you mean, hence not making itself smart. Can you point the way out of this seeming contradiction?
So a superintelligence could be super powerful and super dangerous if and when we are able build it.
AI Safety would be a worthy cause if a superintelligence were powerful and dangerous enough to be an issue but not so powerful and dangerous as to be uncontrollable. A solution has to be necessary, but it also has to exist. Thus, there is a tension between scale and tractability here. Both Bostrom and Yudkowsky only ever address one thing at a time, never acknowledging this tension.
If it takes off slow enough, we’ll have time to figure out how to make it safe after we create the first superintelligence, which would be very handy indeed. Unfortunately, it turns out nobody agrees on that either.
Most estimates on take-off speed start counting from the point that the AI is superintelligent. Why wait until then? A computer can be reset, so if you had a primitive AGI specimen you’d have unlimited tries to spot problems and make it behave.
I’d say that a 0.0001% chance of a superintelligence catastrophe is a huge over-estimate. Hence, AI Safety would be an ineffective cause area if you hold a person-affecting view. If you don’t, then at least this opens the way for the kind of counterarguments used against Pascal’s Mugging.
I am not a historian, but during the Nazi regime, The Netherlands had among the highest percentages of Jews killed in all of Western Europe. I remember historians blaming this on the Dutch having thorough records of who the Jews were and where they lived. Access to information is definitely a big factor in how succesful a genocidal regime can be.
The worry is not so much about killer robots enacting a mass murder campaign. The worry is that humans will use facial recognition algorithms to help state-sanctioned ethnic cleansing. This is not a speculative worry. There are a lot of papers on Uyghur facial recognition.