I have spent some time over the last few months engaging with moderately informed undergraduates on AI risk (mostly by teaching AI risk arguments in my courses along with enough background material to give them some grounding). If others are interested, I would happily share my takeaways at greater length but I wanted to share a couple of interesting things:
1) Today's college students do not think AI progress has been rapid. Generally, GPT-4 maxed out their internal benchmarks (they don't know it by name obviously but that's the referent), chatbots haven't gotten much better since then as they see it, and 2023 was eons ago in college student time. Working through a project with Claude Code changes nothing because they mostly have zero intuition for what that would have looked like in the past. Their naive mental model if they project progress forward is incremental improvement.
2) My students tend to think that catastrophic risk arguments are designed as (or at least function as) distractions from the "real" issues (jobs, environmental impact, etc.) and that they should not be taken seriously as a result. Nearly all of my students would be very happy to pause AI today, but none of them in response to catastrophic risk.
3) When forced to grapple with the arguments seriously, different discussions with my students independently converged on the view that existential risk was probably a good thing because ordinary people otherwise have zero leverage over AI. That is, if AI leaders genuinely believe there is existential risk (and that, therefore, they will personally die), then this might be a way to get them to stop developing job-killing AI that will otherwise take down the rest of us.
