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Discussion (81 Comments)Read Original on HackerNews
In what world would I ever expect a commercial (or governmental) entity to have precise alignment with me personally, or even with my own business? I argue those relationships are necessarily adversarial, and trusting anyone else to align their "AI" tool to my goals, needs, and/or desires is a recipe for having my livelihood completely reassigned into someone else's wallet.
I guess I'm trying to wonder why this line of thinking (in theory) doesn't turn to paranoia about everybody. I don't know much ethics or political theory or anything.
It does. People drive these entities. People hide behind the liability shields and authority of these entities. Also notice that I generalized with the phrase ââŚand trusting anyoneâŚâ
This is true, and I believe that the "sufficient funds" threshold will keep dropping too. It's a relief more than a concern, because I don't trust that big models from American or Chinese labs will always be aligned with what I need. There are probably a lot of people in the world whose interests are not especially aligned with the interests of the current AI research leaders.
"Don't turn the visible universe into paperclips" is a practically universal "good alignment" but the models we have can't do that anyhow. The actual refusal guards frontier models come with are a lot more culturally/historically contingent and less universal. Lumping them all under "safety" presupposes the outcome of a debate that has been philosophically unresolved forever. If we get hundreds of strong models from different groups all over the world, I think that it will improve the net utility of AI and disarm the possibility of one lab or a small cartel using it to control the rest of us.
Most countries have a pretty strong ban on most kinds of weapons, the US is one of the few that lets everyone run around with their rooty tooty point and shooty, but most countries have implemented bans. Some because the government doesn't want the people having them, and in others the citizens call for the bans because they don't like the idea of getting shot by their fellow citizens.
It won't be long before citizens and governments get tired of models being used for criminal activities and will eventually lay down laws around this. Models will have to be registered and safety tested, strict criminal prosecution will happen if you don't. And the big model companies will back their favorite politicians to ensure this will happen to.
Now, that in general will be helpful as there will still be more models, but it will still not be a free for all.
Anyone outside the UK can share what this is about?
Alignment is a Joke Well-meaning people are trying very hard to ensure LLMs are friendly to humans. This undertaking is called alignment. I donât think itâs going to work.
First, ML models are a giant pile of linear algebra. Unlike human brains, which are biologically predisposed to acquire prosocial behavior, there is nothing intrinsic in the mathematics or hardware that ensures models are nice. Instead, alignment is purely a product of the corpus and training process: OpenAI has enormous teams of people who spend time talking to LLMs, evaluating what they say, and adjusting weights to make them nice. They also build secondary LLMs which double-check that the core LLM is not telling people how to build pipe bombs. Both of these things are optional and expensive. All it takes to get an unaligned model is for an unscrupulous entity to train one and not do that workâor to do it poorly.
I see four moats that could prevent this from happening.
First, training and inference hardware could be difficult to access. This clearly wonât last. The entire tech industry is gearing up to produce ML hardware and building datacenters at an incredible clip. Microsoft, Oracle, and Amazon are tripping over themselves to rent training clusters to anyone who asks, and economies of scale are rapidly lowering costs.
Second, the mathematics and software that go into the training and inference process could be kept secret. The math is all published, so thatâs not going to stop anyone. The software generally remains secret sauce, but I donât think that will hold for long. There are a lot of people working at frontier labs; those people will move to other jobs and their expertise will gradually become common knowledge. I would be shocked if state actors were not trying to exfiltrate data from OpenAI et al. like Saudi Arabia did to Twitter, or China has been doing to a good chunk of the US tech industry for the last twenty years.
Third, training corpuses could be difficult to acquire. This cat has never seen the inside of a bag. Meta trained their LLM by torrenting pirated books and scraping the Internet. Both of these things are easy to do. There are whole companies which offer web scraping as a service; they spread requests across vast arrays of residential proxies to make it difficult to identify and block.
Fourth, thereâs the small armies of contractors who do the work of judging LLM responses during the reinforcement learning process; as the quip goes, âAIâ stands for African Intelligence. This takes money to do yourself, but it is possible to piggyback off the work of others by training your model off another modelâs outputs. OpenAI thinks Deepseek did exactly that.
In short, the ML industry is creating the conditions under which anyone with sufficient funds can train an unaligned model. Rather than raise the bar against malicious AI, ML companies have lowered it.
To make matters worse, the current efforts at alignment donât seem to be working all that well. LLMs are complex chaotic systems, and we donât really understand how they work or how to make them safe. Even after shoveling piles of money and gobstoppingly smart engineers at the problem for years, supposedly aligned LLMs keep sexting kids, obliteration attacks can convince models to generate images of violence, and anyone can go and download âuncensoredâ versions of models. Of course alignment prevents many terrible things from happening, but models are run many times, so there are many chances for the safeguards to fail. Alignment which prevents 99% of hate speech still generates an awful lot of hate speech. The LLM only has to give usable instructions for making a bioweapon once.
We should assume that any âfriendlyâ model built will have an equivalently powerful âevilâ version in a few years. If you do not want the evil version to exist, you should not build the friendly one! You should definitely not reorient a good chunk of the US economy toward making evil models easier to train. ...
* https://news.ycombinator.com/item?id=47703528
* https://news.ycombinator.com/item?id=47730981
You don't need to train new models. Every single frontier model is susceptible to the same jailbreaks they were 3 years ago.
Only now, an agent reading the CEOs email is much more dangerous because it is more capable than it was 3 years ago.
The cynic in me agrees with the articleâs premise, but not because I believe "alignment is a joke", but because I doubt that humans are "biologically predisposed to acquire prosocial behavior."
Geoffrey Hinton will not have his liver pecked out every day like Prometheus does.
How did brains acquire this predisposition if there is nothing intrinsic in the mathematics or hardware? The answer is "through evolution" which is just an alternative optimization procedure.
This "just" is... not-incorrect, but also not really actionable/relevant.
1. LLMs aren't a fully genetic algorithm exploring the space of all possible "neuron" architectures. The "social" capabilities we want may not be possible to acquire through the weight-based stuff going on now.
2. In biological life, a big part of that is detecting "thing like me", for finding a mate, kin-selection, etc. We do not want our LLM-driven systems to discriminate against actual humans in favor of similar systems. (In practice, this problem already exists.)
3. The humans involved making/selling them will never spend the necessary money to do it.
4. Even with investment, the number of iterations and years involved to get the same "optimization" result may be excessive.
(Apart from that, I'm generally suspect of evolution-based arguments because they are often structurally identical to saying âGod willed it, so it must trueâ.)
while under the umbrella of evolution, if you really want to boil it down to an optimization procedure then at the very least you need to accurately model human emotion, which is wildly inconsistent, and our selection bias for mating. If you can do that, then you might as well go take-over the online dating market
Large language models are not evolving in nature under natural selection. They are evolving under unnatural selection and not optimizing for human survival.
They are also not human.
Tigers, hippos and SARS-CoV-2 also developed âthrough evolutionâ. That does not make them safe to work around.
https://www.youtube.com/watch?v=mScpHTIi-kM
Putting aside malicious actors, the analogy here means benevolent actors could spend more time and money training AI models to behave pro-socially than than evolutionary pressures put on humanity. After all, they control the that optimization procedure! So we shouldnât be able to point to examples of frontier models engaging in malicious behavior, right?
Seems easy enough, I'm actually pretty confident in even the most incompetent of current world leaders in this particular task.
I'm seeing that these tools are extremely powerful the hands of experts that already understand software engineering, security, observability, and system reliability / safety.
And extremely dangerous in the hands of people that don't understand any of this.
Perhaps reality of economics and safety will kick in, and inexperienced people will stop making expensive and dangerous mistakes.
âThe futureâ is happening because it is allowed in our current legal framework and because investors want to make it happen. It is not âhappeningâ because it is good or desirable or unavoidable.
I think the author is brushing against some larger system issues that are already in motion, and that the way AI is being rolled out are exacerbating, as opposed to a root cause of.
There's a felony fraudster running the executive branch of the US, and it takes a lot of political resources to get someone elected president.
Such a fear mongering position. You can learn to build pipe bombs already. Take any chemical reaction that produces gas and heat and contain it. Congratulations, you have a pipe bomb.
Meanwhile.. just.. ask an LLM if you can mix certain cleaning chemicals safely.
> I see four moats that could prevent this from happening.
Really? Because you just said:
> human brains, which are biologically predisposed to acquire prosocial behavior
You think you're going to constrain _human_ behavior by twiddling with the language models? This is foolishly naive to an extreme.
If you put basic and well understood human considerations before corporate ones then reality is far easier to predict.
The internet produced 4chan. Produced scammers. Produced fraud. Instrumental in spreading child porn. Caused suicides. Many people lost their lives due to bullying on the internet. Many develop have addictions to gaming.
To anyone who has given it some thought, any sufficiently advanced technology usually affects both in good and bad ways. Its obvious that something that increases degrees of freedom in one direction will do so in others. Humans come in and align it.
There's some social credit to gain by being cynical and by signalling this cynicism. In the current social dynamics - being cynical gives you an edge and makes you look savvy. The optimistic appear naive but the pessimists appear as if they truly understand the situation. But the optimists are usually correct in hindsight.
We know how the internet turned out despite pessimists flagging potential problems with it. I know how AI will turn out. These kind of articles will be a dime a dozen and we will look at it the same way as we look at now at bygone internet-pessimists.
This is response not just to this article, but a few others.
If the AI tech keeps going at the direction it's going now, more and more people will start believing the world would be better if the internet and computer had never been invented.
You talk like the internet being a net positive is a given. It really isn't, especially after it's proven that it doesn't democratize power (see Arab Spring, and China, and the US, and everywhere.)
Ask any poor person in India what their sentiment is with tech - it is usually optimism.
> You talk like the internet being a net positive is a given. It really isn't, especially after it's proven that it doesn't democratize power (see Arab Spring, and China, and the US, and everywhere.)
The world is far more democratic now than before and I attribute it to technology because it reduces information asymmetry.
That is fantasy. Information technology has created an unprecedented level of information asymmetry and the gap is widening everyday as the total computing capacity grows.
Before information era, the ruling class was roughly as blind as peasants. Population census took years, and sometimes outright impossible. The opaqueness was two-way. Now it's one way - people in power know everything about the citizens.
I do think that safety is important. I'm particularly concerned about vulnerable people and sycophantic behavior. But I think it's better not to be a luddite. I will give a positively biased view because the article already presents a strongly negative stance. Two remarks:
> Alignment is a Joke
True, but for a different reason. Modern LLMs clearly don't have a strong sense of direction or intrinsic goals. That's perfect for what we need to do with them! But when a group of people aligns one to their own interest, they may imprint a stance which other groups may not like (which this article confusingly calls "unaligned model", even though it's perfectly aligned with its creators' intent). People unaligned with your values have always existed and will always exist. This is just another tool they can use. If they're truly against you, they'll develop it whether you want it or not. I guess I'm in the camp of people that have decided that those harmful capabilities are inevitable, as the article directly addresses.
> LLMs change the cost balance for malicious attackers, enabling new scales of sophisticated, targeted security attacks, fraud, and harassment. Models can produce text and imagery that is difficult for humans to bear; I expect an increased burden to fall on moderators.
What about the new scales of sophisticated defenses that they will enable? And for a simple solution to avoid the produced text and imagery: don't go online so much? We already all sort of agree that social media is bad for society. If we make it completely unusable, I think we will all have to gain for it. If digital stops having any value, perhaps we'll finally go back to valuing local communities and offline hobbies for children. What if this is our wakeup call?
I think the point was never to bring a solution or show any essence of reality. The point was being polemical and signalling savviness through cynicism.
[1] https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing
For the future, try to avoid prevaricating when you actually have a clear sense of what you want to argue. Instead of convincing me that you've weighed both options and found luddism wanting, you just come off as dishonest. If you think stridently, write stridently.
On a serious note, I think they meant TN, as in Torment Nexus, but I could be wrong.
1. Introduction: 33,088 (https://news.ycombinator.com/item?id=47689648)
2. Dynamics: 3,659 (https://news.ycombinator.com/item?id=47693678)
3. Culture: 5,914 (https://news.ycombinator.com/item?id=47703528)
4. Information Ecology: 777 (https://news.ycombinator.com/item?id=47718502)
5. Annoyances: 7,020 (https://news.ycombinator.com/item?id=47730981)
6. Psychological Hazards: 199 (https://news.ycombinator.com/item?id=47747936)
Feedback from early readers was that the work was too large to digest in a single reading, so I split it up into a series of posts. I'm not entirely sure this was the right call; the sections I thought were the most interesting seem to have gotten much less attention than the introductory preliminaries.
I had never heard of you, and this article appeared very biased to me. I found the information ecology piece superior, shame that it went unnoticed; I will try to go through all of them. I admire the breadth of topics youâre covering and appreciate the many sources. Theyâre clearly written in your own voice and that is great to see, I guess I mostly reacted to not being fully aligned with your view.
I suspect that if you'd not broken up the post into a series of smaller ones, the sorts of folks who are unwilling to read the whole thing as you post it section by section would have fed the entire post to an LLM to "summarize".
I still remember his takedown of mongodb's claims with the call me maybe post years and years ago filling me with a good bit of awe.
If âtptacek posts a blog post, I bet it similarly does well, on average, because theyâre a âknown quantityâ around these parts, for example.
1. AI becomes a highly protected technology, a totalitarian world government retains a monopoly on its powers and enforces use, and offers it to those with preexisting connections: permanent underclass outcome
2. Somehow the world agrees to stop building AI and keep tech in many fields at a permanent pre-2026 level: soft butlerian jihad
3. Futurama: somehow we get ASI and a magical balance of weirdness and dance of continual disruption keeps apocalypse in check and we accept a constant steady-state transformation without paperclipocalypse
Its like listening to Christians talking about the rapture.