Yes, the non-stacking issue in the alignment community is mostly due to the nature of the domain
But also partly due to the LessWrong/AF culture and some rationalist memes. For example, if people had stacked on Friston et. al., the understanding of agency and predictive systems (now called “simulators”) in the alignment community could have advanced several years faster. However, people seem to prefer reinventing stuff, and formalizing their own methods. It’s more fun… but also more karma.
In conventional academia, researchers are typically forced to stack. If progress is in principle stackable, and you don’t do it, it won’t be published. This means that even if your reinvention of a concept is slightly more elegant or intuitive to you, you still need to stack. This seems to go against what’s fun: I think I don’t know any researcher who would be really excited about literature reviews and prefer that over thinking and writing their own ideas. In the absence of incentives for stacking … or actually presence of incentives against stacking … you get a lot of non-stacking AI alignment research.
Yes, the non-stacking issue in the alignment community is mostly due to the nature of the domain
But also partly due to the LessWrong/AF culture and some rationalist memes. For example, if people had stacked on Friston et. al., the understanding of agency and predictive systems (now called “simulators”) in the alignment community could have advanced several years faster. However, people seem to prefer reinventing stuff, and formalizing their own methods. It’s more fun… but also more karma.
In conventional academia, researchers are typically forced to stack. If progress is in principle stackable, and you don’t do it, it won’t be published. This means that even if your reinvention of a concept is slightly more elegant or intuitive to you, you still need to stack. This seems to go against what’s fun: I think I don’t know any researcher who would be really excited about literature reviews and prefer that over thinking and writing their own ideas. In the absence of incentives for stacking … or actually presence of incentives against stacking … you get a lot of non-stacking AI alignment research.