Full time independent deconfusion researcher (https://www.alignmentforum.org/posts/5Nz4PJgvLCpJd6YTA/looking-deeper-at-deconfusion) in AI Alignment. (Also PhD in the theory of distributed computing).
If you're interested by some research ideas that you see in my posts, know that I keep private docs with the most compressed version of my deconfusion ideas in the process of getting feedback. I can give you access if you PM me!
A list of topics I'm currently doing deconfusion on:
Hum, I think I wrote my point badly on the comment above. What I mean isn't that formal methods will never be useful, just that they're not really useful yet, and will require more pure AI safety research to be useful.
The general reason is that all formal methods try to show that a program follows a specification on a model of computation. Right now, a lot of the work on formal methods applied to AI focus on adapting known formal methods to the specific programs (say Neural Networks) and the right model of computation (in what contexts do you use these programs, how can you abstract their execution to make it simpler). But one point they fail to address is the question of the specification.
Note that when I say specification, I mean a formal specification. In practice, it's usually a modal logic formula, in LTL for example. And here we get at the crux of my argument: nobody knows the specification for almost all AI properties we care about. Nobody knows the specification for "Recognizing kittens" or "Answering correctly a question in English". And even for safety questions, we don't have yet a specification of "doesn't manipulate us" or "is aligned". That's the work that still needs to be done, and that's what people like Paul Christiano and Evan Hubinger, among others, are doing. But until we have such properties, the formal methods will not be really useful to either AI capability or AI safety.
Lastly, I want to point out that working on AI for formal methods is also a means to get money and prestige. I'm not going to go full Hanson and say that's the only reason, but it's still a part of the international situation. I have examples of people getting AI related funding in France, for a project that is really, but really useless for AI.
This post annoyed me. Which is a good thing! It means that you hit where it hurts, and you forced me to reconsider my arguments. I also had to update (a bit) toward your position, because I realized that my "counter-arguments" weren't that strong.
Still, here they are:
With all that being said, I'm glad you wrote this post and I think I'll revisit it and think more about it.
Since many other answers treat the more general ideas, I want to focus on the "volontary" sadness of reading/watching/listening sad stories. I was curious about this myself, because I noticed that reading only "positive" and "joyous" stories eventually feel empty.
The answer seem that sad elements in a story bring more depth than the fun/joyous ones. In that sense, sadness in stories act as a signal of deepness, but also a way to access some deeper part of our emotions and internal life.
I'm reminded of Mark Manson's quote from this article:
If I ask you, “What do you want out of life?” and you say something like, “I want to be happy and have a great family and a job I like,” it’s so ubiquitous that it doesn’t even mean anything.
A more interesting question, a question that perhaps you’ve never considered before, is what pain do you want in your life? What are you willing to struggle for? Because that seems to be a greater determinant of how our lives turn out.
Maybe sadness and pain just tell us more about other and ourselves, and that's what we find so enthralling.
Thanks for that very in-depth answer!
I was indeed thinking about 3., even if 1. and 2. are also important. And I get that the main value of these diagrams is to force an explicit and as formal as possible statement to be made.
I guess my question was more about, given two different causal diagrams for the same risk (made by different researchers for example), have you an idea of how to compare them? Like finding the first difference along the causal path, or others means of comparison. This seems important because even with clean descriptions of our views, we can still talk past each other if we cannot see where the difference truly lies.
Great post! I feel these diagrams will be really useful for clarifying the possible interventions and parts of the existential risks.
Do you think they'll also serve for comparing different positions on a specific existential risk, like the trajectories in this post? Or do you envision the diagram for a specific risk as a summary of all causal pathways to this risk?
What about diseases? I admit I know little about this period of history, but the accounts I read (for example in Guns, Germs and Steel) place the advantage in the spread of diseases to the Americas.
Basically, because the Americas lacked many big domesticated mammals, they could not have cities like European ones with cattle everywhere. The conditions of living in these big cities caused the spread of diseases. And when going to the Americas, the conquistadors took these diseases with them to a population which had never experienced them, causing most of the deaths of the early conquests.
(This is the picture from the few sources I've read. So it might be wrong or inaccurate, but if it is, I am very curious of why.)
Thanks for the thoughtful comment!
This sounds like a potentially good analogy, but one has to be careful that it doesn't rely on assumptions that only apply to humans, or to quite bounded agents.
The topics of persuasion (both from AIs and of AIs) is indeed an important topic in alignment. There's a general risk that optimization is very easily spent to push for manipulation of human, whether intentionally (training an AI which actually end up wanting to do something else, and so has reason to manipulate us) or unintentionally (training an AI such that it's incentivized to answer what we would prefer rather than the most accurate and appropriate answer).
For the persuasion of AIs by AIs, there are some initial thoughts around memetics for AIs, but they are not fully formed yet.
Don't know much about this literature, but it makes me think of more structural takes on the alignment problem, that emphasize the importance of the structure of society funneling and pushing optimization, rather than the individual power of agents to alter it.
So, as can be seen above, none of these ideas sounds bad or impossible to make work, but judging them correctly would require far more effort put into analyzing them. Maybe you should apply for the fellowship, especially for behavioral work on which you're more of an expert? ;)
It's a very good question, and shamefully I don't have any answer that's completely satisfying. But here are the next best things, some resources that will give you a more rounded perspective of alignment: