How much ML/CS knowledge is too much? For someone working in AI Policy, do you see diminishing returns to become a real expert in ML/CS, such that you could work directly as a technical person? Or is that level of expertise very useful for policy work?
Hard to imagine it ever being too much TBH. I and most of my colleagues continue to invest in AI upskilling. However, lots of other skills are worth having too. Basically, I view it as a process of continual improvement: I will probably never have “enough” ML skill because the field moves faster than I can keep up with it, and there are approximately linear returns on it (and a bunch of other skills that I’ve mentioned in these comments).
How much ML/CS knowledge is too much? For someone working in AI Policy, do you see diminishing returns to become a real expert in ML/CS, such that you could work directly as a technical person? Or is that level of expertise very useful for policy work?
Hard to imagine it ever being too much TBH. I and most of my colleagues continue to invest in AI upskilling. However, lots of other skills are worth having too. Basically, I view it as a process of continual improvement: I will probably never have “enough” ML skill because the field moves faster than I can keep up with it, and there are approximately linear returns on it (and a bunch of other skills that I’ve mentioned in these comments).