I don’t think my claim is that “FFS is already subsumed by work in academia”: as I acknowledge, FFS is a different theoretical framework than Pearl-based causality. I view them as two distinct approaches, but my claim is that they are motivated by the same question (that is, how to do causal representation learning).
It was intentional that the linked paper is an intro survey paper to the Pearl-ish approach to causal rep. learning: I mean to indicate that there are already lots of academic researchers studying the question “what does it mean to study causality if we don’t have pre-defined variables?”
It may be that FFS ends up contributing novel insights above and beyond <Pearl-based causal rep. learning>, but a priori I expect this to occur only if FFS researchers are familiar with the existing literature, which I haven’t seen mentioned in any FFS posts.
My line of thinking is: It’s hard to improve on a field you aren’t familiar with. If you’re ignorant of the work of hundreds of other researchers who are trying to answer the same underlying question you are, odds are against your insights being novel / neglected.
Scott Garrabrant conceived of FFS as an extension & generalization of Pearlian causality that answers questions that are not dealt well with in the Pearlian framework. He is aware of Pearl’s work and explicitly builds on it.
It’s not a distinct approach as much as an extension.
The paper you mentioned discusses the problem of figuring out what the right variables are but poses no solution (as far as I can tell). That shouldn’t surprise because the problem is very hard. Many people have thought about it but there is only one Garrabrant.
I do agree with your overall perspective that people in alignment are quite insular, unaware of the literature and often reinventing the wheel.
I don’t think my claim is that “FFS is already subsumed by work in academia”: as I acknowledge, FFS is a different theoretical framework than Pearl-based causality. I view them as two distinct approaches, but my claim is that they are motivated by the same question (that is, how to do causal representation learning).
It was intentional that the linked paper is an intro survey paper to the Pearl-ish approach to causal rep. learning: I mean to indicate that there are already lots of academic researchers studying the question “what does it mean to study causality if we don’t have pre-defined variables?”
It may be that FFS ends up contributing novel insights above and beyond <Pearl-based causal rep. learning>, but a priori I expect this to occur only if FFS researchers are familiar with the existing literature, which I haven’t seen mentioned in any FFS posts.
My line of thinking is: It’s hard to improve on a field you aren’t familiar with. If you’re ignorant of the work of hundreds of other researchers who are trying to answer the same underlying question you are, odds are against your insights being novel / neglected.
Scott Garrabrant conceived of FFS as an extension & generalization of Pearlian causality that answers questions that are not dealt well with in the Pearlian framework. He is aware of Pearl’s work and explicitly builds on it. It’s not a distinct approach as much as an extension. The paper you mentioned discusses the problem of figuring out what the right variables are but poses no solution (as far as I can tell). That shouldn’t surprise because the problem is very hard. Many people have thought about it but there is only one Garrabrant.
I do agree with your overall perspective that people in alignment are quite insular, unaware of the literature and often reinventing the wheel.