AI productivity discussion go!

The model seems defensible, but for some reason it isn’t passing the sniff test. Maybe its that the extreme scenario seems wildly optimistic, or that the observed modest productivity gains are framed as either the trend or “just the start of something amazing !”.

The issues are that

1) The median AI use case isn’t increasing productivity but expanding capability and reducing the need to communicate across teams. Ex: if someone needs a dashboard or a ppt designed, now they don’t have to ask another team. AI is substituting for intern and early career workers in someone else’s firm.

This is also borne out in the hiring data.

2) The cases that show maximal productivity gains are when AI is leveraged by experts.

This is a problem, because the evidence for automation gains is poor. AI automation seems to be going to the same place ML projects went to die.

If augmentation is the primary lever that lifts up productivity, and it is dependent on AI being matched to experts, then the limiting factor is expertise.

This makes the fact that AI is both, taking out early career roles AND one shooting education, a divine irony.

Where exactly are those future experts supposed to come from? The ones with taste and the ability to deliver us this AI driven GDP growth?

AI is also setting up a conflict between liability, insurance and productivity, and thats a whole point in itself. However it will be expressed as a drag on productivity.