I think context and alignment are quite different. I would say context is basically role-specific knowledge. For some roles, like grantmaker, it's very useful to have an in-depth understanding of the technical issues of AI safety, the history of the field, the people and organisations involved, etc. For other roles, like comms, you might need less or different knowledge. For example, if you do comms for an alignment research org, you probably need the technical knowledge to roughly understand what your org is working on so that you can explain it to other people. But you don't need sufficient technical knowledge to be able to predict if it's a viable approach, as an ideal grantmaker might.
Whereas I would say alignment is not just understanding but actually believing. A long history in EA/LW/various AI safety spaces predicts that you'll be committed to AI safety and won't just jump to a better paying job if it comes along.
In my current role (which has nothing whatsoever to do with AI) I think I have pretty good context - I understand the product, I know why we're building it, I know all the key internal and external stakeholders, etc. But I actually think the product is not that great, and if someone came along and offered me a job that was better, I would probably leave.
I suppose I was just thinking about things like MATS, where I've seen people become very worried that it's basically a programme to take really smart people and give them the skills they need to go and work for xAI once their fellowship is done, so it's important to make sure they care a lot about AI safety.
Absolutely agree that everything you've said is really important to succeed. I'd be curious to know how much it is considered a prerequisite for AI safety roles vs generalist roles elsewhere in tech, as opposed to learning these skills on the job.
A few thoughts on this as someone who is even more of a generalist (I work in comms/public affairs at the moment and have no technical skills), and who would like to work on safety if the opportunity came up:
I think people should stop saying that AI safety is "bottlenecked on generalists" or just needs more generalists. If there was truly huge demand for "generalists", presumably you wouldn't have to do months of unpaid work to try and get a job! This sounds more like famously competitive fields like publishing. At least, people should say that the field is bottlenecked on highly skilled generalists.
It's not totally clear to me why generalists should be expected to signal their alignment to this extent. I understand why you'd want this for applicants to technical fellowships. But the risks of a web designer/HR manager/chief of staff going to work on capabilities seems low. In most fields you are expected to give some sort of reason for why you're interested in the role, but the level of signalling here is extreme and rules out 99% of applicants for generalist roles.
I think context and alignment are quite different. I would say context is basically role-specific knowledge. For some roles, like grantmaker, it's very useful to have an in-depth understanding of the technical issues of AI safety, the history of the field, the people and organisations involved, etc. For other roles, like comms, you might need less or different knowledge. For example, if you do comms for an alignment research org, you probably need the technical knowledge to roughly understand what your org is working on so that you can explain it to other people. But you don't need sufficient technical knowledge to be able to predict if it's a viable approach, as an ideal grantmaker might.
Whereas I would say alignment is not just understanding but actually believing. A long history in EA/LW/various AI safety spaces predicts that you'll be committed to AI safety and won't just jump to a better paying job if it comes along.
In my current role (which has nothing whatsoever to do with AI) I think I have pretty good context - I understand the product, I know why we're building it, I know all the key internal and external stakeholders, etc. But I actually think the product is not that great, and if someone came along and offered me a job that was better, I would probably leave.
I suppose I was just thinking about things like MATS, where I've seen people become very worried that it's basically a programme to take really smart people and give them the skills they need to go and work for xAI once their fellowship is done, so it's important to make sure they care a lot about AI safety.
Absolutely agree that everything you've said is really important to succeed. I'd be curious to know how much it is considered a prerequisite for AI safety roles vs generalist roles elsewhere in tech, as opposed to learning these skills on the job.
A few thoughts on this as someone who is even more of a generalist (I work in comms/public affairs at the moment and have no technical skills), and who would like to work on safety if the opportunity came up: