Read the project and its key paper before commenting: arxiv.org/abs/2510.25137 The key takeaway buried between technical jargon is that these figures aren’t m

Read the project and its key paper before commenting: arxiv.org/abs/2510.25137 The key takeaway buried between technical jargon is that these figures aren’t measuring workforce replacement, but task replacement. They aren’t saying AI can replace 12% of the workforce, rather that AI can replace 12% of the work performed, and its associated wage values, expected concentrations, and diverse impacts (across the lower 48). There does not seem to be a more user-friendly visual available to tinker with, at least that I could readily find on mobile. They try to couch this conclusion at the end, stating that workforce displacement isn’t going to happen by AI so much as by decision-makers in government and enterprise. It’s entirely possible to use AI tools to amplify productivity and output and lead to smaller work weeks with better labor outcomes, but we have ample evidence that, barring appropriate carrots and sticks, enterprises will fire folks to keep the profit for themselves while governments will victim-blame the unemployed for “not being current on skills”. This creates a strong disincentive for labor to cooperate with AI, because it’s a lose-lose Prisoner’s Dilemma for them: cooperation will either result in a boost in productivity that hurts those around them through displacement and an increased workload on themselves, or cooperation results in their own replacement in the midst of a difficult job market and broader economy. Cooperation is presently the worst choice for labor, and the authors do a milquetoast job highlighting this reality - but do better than most of their predecessors, at least. Really, it comes back to what I spoke about in 2023 when it comes to AI: the problem isn’t AI so much as a system that will hand its benefits to those of already immense wealth and means, and that is the problem that needs solving immediately.