US financial institutions are being nuked from orbit pic.twitter.com/YUGtcR1WFm
— š“āā ļø (@calvinfroedge) February 27, 2026
State collapse is inevitable when a society’s leaders are insulated from the negative consequences of their bad decisions.
Mike Shelby
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And Tillis too.
It appears that Trump gave up on Minnesota. No arrests for fraud. ICE retreated. Somalis entrenched and now suing for reparations.
I hope Vance does better than Pence did with COVID-19.
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From Grok:
Projecting job losses due to AI involves synthesizing forecasts from various sources, including Forrester, the World Economic Forum (WEF), McKinsey, Goldman Sachs, and detailed estimates from think tanks like Infinitive. These projections vary based on assumptions about AI adoption rates, economic conditions, and whether they focus on gross displacements (jobs eliminated or automated) or net changes (accounting for new jobs created by AI-driven growth). Most sources emphasize that while AI will displace millions of rolesāparticularly in routine, administrative, and entry-level white-collar workāit will also create opportunities in fields like AI development, data science, and oversight of automated systems.Key caveats:
Based on available data, I’ve synthesized a year-by-year projection for the US, drawing primarily from Infinitive’s granular breakdown (which aligns with broader trends) and extrapolating for 2030 using the observed pattern of accelerating losses (increases of ~50,000 in gains and ~300,000 in losses annually). This assumes continued AI maturation, with displacements outpacing creations in the near term. Figures are approximate and represent AI-attributable impacts.
| Year | Projected Jobs Displaced (Gross Loss) | Projected New Jobs Created (Gross Gain) | Net Change | Key Notes/Sources |
|---|---|---|---|---|
| 2026 | ~600,000 | ~100,000 | -500,000 | Early mainstream adoption in offices; white-collar automation in accounting and marketing. Forrester predicts cumulative buildup to 10.4 million net losses by 2030. forrester.com Infinitive details sector-specific cuts. infinitive.com |
| 2027 | ~900,000 | ~150,000 | -750,000 | Critical mass in finance, healthcare admin, and manufacturing; peak displacement period for many firms. Aligns with McKinsey’s estimate of 12 million occupational shifts needed by 2030. mckinsey.com |
| 2028 | ~1,200,000 | ~200,000 | -1,000,000 | AI embedded in processes like IT support and supply chains; broader unemployment effects emerge. Goldman Sachs notes 6ā7% of US workforce (10ā12 million) could be displaced overall. goldmansachs.com |
| 2029 | ~1,500,000 | ~250,000 | -1,250,000 | Scaling of AI industries, but permanent replacement of traditional roles; cumulative impacts visible nationally. PwC sees up to 30% of jobs automatable by mid-2030s. nexford.edu |
| 2030 | ~1,800,000 | ~300,000 | -1,500,000 | Extrapolated acceleration; new AI ecosystems mature, but losses dominate in routine sectors. Total cumulative displacements from 2026ā2030: ~6 million; net: ~-5 million. Forrester’s 6.1% net loss (10.4 million total by 2030) suggests higher if including pre-2026 trends. forrester.com |
Cumulative Summary (2026ā2030)
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Thank you. Yes, I see it now. Donāt know why I couldnāt open it.
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