Much of the AI research community remains unaware of the Alignment Problem (according to my personal experience), and I haven't seen much discussion about how to deliberately expand the community (all I've seen to this effect is Scott's A/B/C/D/E testing on alignment articles).
Expanding the number of people aware of (and ideally, working on) the alignment problem is a high-leverage activity: a constant amount of effort spent educating someone in exchange for a chance of recruiting an ally who will work hard at our sides. Another metric by which we should evaluate approaches is whether we have to convince or simply educate; professors and high-status researchers may be more dismissive (possibly due to the inside view, their wariness of strange-sounding ideas, and overconfidence in their long-term predictions), but their influence would be greater. On the other hand, a good friend in a CS or Math under-/post-graduate program may be more receptive.
In my case, I stumbled upon HP:MoR one year ago, read the Sequences, and then read more about Alignment and CEV. I appreciated that Alignment was a serious problem, but it wasn't until I got through Superintelligence that I realized it's basically The Problem. Being in the second year of my doctorate program, I didn't know whether I was "too late" to start learning the math, "too far behind" people like Eliezer to make a difference. What I did know is that everyone can't defect - we need people to put in the work, and we probably need substantially more people doing so.
What happened to me took a lot of time and may be unrealistic to recommend to others. The articles Scott tested seem equally effective; instead, I'd like to discuss what social approaches work best for taking people from friend to friend-who-takes-alignment-seriously (while optimizing against effort expended), and whether this is an efficient use of our time.