When I worked a FAANG research job, my experience was that it was socially punishable to bring up AI alignment research in just about any context, with exceptions as it was relevant to the team's immediate mission, for example robustness on the scale required for medical decisions (a much smaller scale than AGI ruin, but a notably larger scale, in the sense of errors being costly, than most deep learning systems in production use at the time).
I find that in some social spaces, Rationality/EA-adjacent ones in particular, it's seen as distracting, rude, and low status to emphasize a hobby horse social justice issue at the expense of whatever else is being discussed. This is straightforward when "whatever else is being discussed" is AI alignment, which the inside view privileges roughly as "more important than everything else, with vague exceptions when the mental health of high-value people who might otherwise do productive work on the topic is at stake."
On a medical research team, I took a little too long to realize that I'd implicitly bought into a shared vision of what's important. We were going to save lives! We weren't going to cure cancer–everyone falls for that trap, aiming too high. We're working on the ground, saving real people, on real timescales. Computer vision can solve the disagreement-among-experts problem in all sorts of medical classification problems, and we're here to fight that fight and win.
So you've gathered a team of AI researchers, some expert, some early-career, to finally take a powerful stab at the alignment problem. A new angle, or more funding, or the right people in the room, whatever belief of comparative advantage you have that inspires hope beyond death with dignity. And you have someone on your team who deeply cares about a complicated social issue you don't understand. Maybe this is their deepest mission, and they see this early-engineer position at your new research org as a stepping stone toward the fairness and accessibility team at Brain that's doing the real work. They do their best to contribute in the team's terms of what's valuable, and they censor themselves constantly, waiting for the right moment to make the pivotal observation that there's not a single cis woman in the room, or that the work we're doing here may be building a future that's even more hostile toward people with developmental disabilities, or this adversarial training scheme has some alarming implications when you consider that the system could learn race as a feature even if we exclude it from the dataset, or something.
I think this is a fair analogue to my situation, and I expect more broadly among people already doing AI research toward a goal other than alignment. It's
- Distracting: We have something else we're working on, and that is a deep question, and you probably could push hard enough on me to nerd snipe me with it if I don't put up barriers.
- Rude: It implies that the work we're doing here, which we all care deeply about (right?) is problematic for reasons well outside our models of who we are and what we're responsible for, and challenging that necessitates a bunch of complicated shadow work.
- Low status: Wait, are you one of those LessWrong people? I bet you're anti-woke and think James Damore shouldn't have been fired, huh? And you're so wound up in your privilege bubble that you think this AGI alarmism is more important than the struggles of real underprivileged people who we know actually exist, here, now? Got it.
I'm being slightly unfair in implying that these are literally interactions I had with real people in the industry. This is more representative of my experiences online and in other spaces with less of a backdrop of professional courtesy. At [FAANG company] these interactions were subtler.
This story is meant to provide answers to your questions 1 and 2. As far as question 3 and making a change, I'm bullish on narratives, aesthetics, anthropology and the like as genuine interventions upstream of AI safety. We're in a social equilibrium where only certain sorts of people can move into AI safety without seriously disrupting the means by which their social needs are met. There are many wonderful people in that set, but it is relatively quite small compared to the set of people who, if they were convinced to genuinely try, could contribute meaningfully.
I would guess this doesn't appear to qualify for bonus points for being reasonably low-hanging. I come from an odd place though: personally sufficiently traumatized by my experiences in AI research that in practical terms contributing there is more or less off limits for me for the time being, yet compelled by AGI ruin narratives and experienced with substantial relevant technical background. So at least for me, this is the way forward.
I stream-of-consciousness'd this out and I'm not happy with how it turned out, but it's probably better I post this than delete it for not being polished and eloquent. Can clarify with responses in comments.
Glad you posted this and I'm also interested in hearing what others say. I've had these questions for myself in tiny bursts throughout the last few months.
When I get the chance to speak to people earlier in their career stage than myself (starting undergrad, or is a high schooler attending a mathcamp I went to) who are undecided about their careers, I bring up my interest in AI Alignment and why I think it's important, and share resources for them after the call in case they're interested in learning more about it. I don't have very many opportunities like this because I don't actively seek to identify and "recruit" them. I only bring it up by happenstance (e.g. joining a random discord server for homotopy type theory, seeing an intro by someone who went to the same mathcamp as me and is interested in cogsci, and scheduling a call to talk about my research background in cogsci and how my interests have evolved/led me to alignment over time).
I know very talented people who are around my age at MIT and from a math program I attended; students who are breezing by technical double majors with perfect GPAs, IMO participants, good competitive programmers, etc. Some things that make it hard for me:
The "pay to not race to AGI" would only make sense if there were a smallish pool of replacements ready to step in and work on racing to AGI. This doesn't seem to be the case. The difference it'd make might not be zero, but close enough to be obviously inefficient.
In particular, there are presumably effective ways to use money to create a greater number of aligned AIS researchers - it's just that [give people a lot of money to work on it] probably isn't one of them.