AI adoption linked to 13% decline in jobs for young U.S. workers: study

Organizations are choosing to eliminate workers rather than amplify them with AI because they'd rather own 100% of diminished capacity than share proceeds from exponentially increased capacity. That's the rent extraction model consuming its own productive infrastructure. The Stanford study documents organizations systematically choosing inferior economic strategies because their rent-extraction frameworks cannot conceptualize workers as productive assets to amplify. This reveals that these organizations are economic rent-seekers that happen to have productive workers, not production companies that happen to extract rents. When forced to choose between preserving rent extraction structures or maximizing value creation, they preserve extraction even at the cost of destroying productive capacity. So what comes next?

What data or special insight do you have as to whether amplifying or eliminating is actually productive?

This argument is vacuous if you consider a marginal worker. Let's say AI eliminates one worker, Bob. You could argue "it was better to amplify Bob and share the gains". However, that assumes the company needs more of whatever Bob produces. That means you could also make an argument "given that the company didn't previously hire another worker Bill ~= Bob, it doesn't want to share gains that Bill would have provided blah blah". Ad absurdum, any company not trying to keep hiring infinitely is doing rent extraction.

You could make a much more narrow argument that cost of hiring Bill was higher than his marginal contribution but cost of keeping Bob + AI is lower than their combined contribution, but that's something you actually need to justify. Or, at the very least, justify why you know that it is, better than people running the company.