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If progress in AI is continuous, we should expect record levels of employment. Not the opposite.
My mentality is if progress in AI doesn't have a sudden, foom-level jump, and if we all don't die, most of the fears of human unemployment are unfounded... at least for a while. Say we get AIs that can replace 90% of the workforce. The productivity surge from this should dramatically boost the economy, creating more companies, more trading, and more jobs. Since AIs can be copied, they would be cheap, abundant labor. This means anything a human can do that an AI still can't becomes a scarce, highly valued resource. Companies with thousands or millions of AI instances working for them would likely compete for human labor, because making more humans takes much longer than making more AIs. Then say, after a few years, AIs are able to automate 90% of the remaining 10%. Then that creates even more productivity, more economic growth, and even more jobs. This could continue for even a few decades. Eventually, humans will be rendered completely obsolete, but by that point (most) of them might be so filthy rich that they won't especially care.
This doesn't mean it'll all be smooth-sailing or that humans will be totally happy with this shift. Some people probably won't enjoy having to switch to a new career, only for that new career to be automated away after a few years, and then have to switch again. This will probably be especially true for people who are older, those who have families, want a stable and certain future, etc. None of this will be made easier by the fact it'll probably be hard to tell when true human obsolescence is on the horizon, so some might be in a state of perpetual anxiety, and others will be in constant denial.
The inverse argument I have seen on reddit happens if you try to examine how these ai models might work and learn.
One method is to use a large benchmark of tasks, where model capabilities is measured as the weighted harmonic mean of all tasks.
As the models run, much of the information gained doing real world tasks is added as training and test tasks to the benchmark suite. (You do this whenever a chat task has an output that can be objectively checked, and for robotic tasks you run in lockstep a neural sim similar to Sora that makes testable predictions f... (read more)