Yep, another good point, and in principle I agree. A couple of caveats, though:
First, it’s not clear to me that experts would agree on enough dynamics to make these clusters predicatively reliable. There might be agreement on the dynamics between scaling laws and timelines (and that’s a nice insight!) — but the Killian et al. paper considered 14 variables, which (for example) would be 91 pairwise dynamics to agree on. I’d at least like some data on whether conditional forecasts converge. I think FRI is doing some work on that.
Second, the Grace et al. paper suggested that expert forecasts exhibited framing effects. So, even if experts did agree on underlying dynamics, those agreements might not be able to be reliably elicited. But maybe conditional forecasts are less susceptible to framing effects.
Yep, another good point, and in principle I agree. A couple of caveats, though:
First, it’s not clear to me that experts would agree on enough dynamics to make these clusters predicatively reliable. There might be agreement on the dynamics between scaling laws and timelines (and that’s a nice insight!) — but the Killian et al. paper considered 14 variables, which (for example) would be 91 pairwise dynamics to agree on. I’d at least like some data on whether conditional forecasts converge. I think FRI is doing some work on that.
Second, the Grace et al. paper suggested that expert forecasts exhibited framing effects. So, even if experts did agree on underlying dynamics, those agreements might not be able to be reliably elicited. But maybe conditional forecasts are less susceptible to framing effects.