Highlights from Garrison Lovely's "Obsolete"

I’ve just finished reading Garrison Lovely’s recently released book, “Obsolete.” I wish I had time for a longer review, but I’ll give a brief one and highlight some particularly interesting sections below. I think it’s a great introduction to non-technical readers and even as a pretty dedicated reader of AI policy and news I learned a good bit. It’s deeply, deeply researched and has a good pulse on the alignment community, and Lovely is careful not to understate or overstate his case. The core argument is that AI development should be analyzed through the lens of mass or universal labor displacement, and that a mass movement to shape, pause or freeze development is much more possible, much more positive, and capable of greater breadth of salience and support than is often argued in the alignment community. He makes an, in my opinion, decisive case that “competitive pressures” by themselves don’t dictate that AI development is fated to happen, and certainly not that it’s fated to happen at the pace the frontier labs are setting. But I wish he’d been a bit more careful about the limitations and subtleties of the plan he’s advocating for; I share the concern raised by folks like the AIFP that it’s hard to pause indefinitely at any given point for very long and that the cost to train a model at any fixed intelligence level, once first reached, is falling precipitously, and that many well-capitalized actors currently want to and are able to speed up development precipitously. I think the book somewhat elides the difficulties we’d still have even if this number were close to 0. It was likely impossible to train GPT-6 in 2016, but it may be extraordinarily cheap to train a GPT-6-level model in 2036, and even just extrapolating the current rate of progress naively, it might be extraordinarily cheap to train a ~GPT-8 level model in 2036. That seems like a world where many irresponsible agents are deploying very powerful technology even if we have verification mechanisms prev