Exposure alone rarely predicts real productivity or employment outcomes Verification cost and demand elasticity decide where AI pays off Entry-level learning task loss may cost more than it saves At an American cu

AI cuts youth hiring, not layoffs, first Retraining alone rarely works; wage insurance does Governments need measurable triggers before scaling tools From November 2022 to June 2026, the employ

Training existing staff outperforms hiring AI specialists tenfold Error costs, not time saved, justify AI training investment Entry-level jobs vanish first, threatening future expert pipelines Just 2 percent of U.S.

National AI capability splits into three separate functions Training, hosting and deployment often move in different directions No country leads every function at once In 2025, private invest

AI substitution shifts costs into managerial review and control Jevons effects can expand demand while raising oversight burdens Accountability remains human even as model reliability improves For quite some time,

AI detection software failed; universities scrap it for coaching Same policy mistakes as plagiarism era are repeating, faster Process-based evaluation beats unreliable detection percentages Less than one in four American universitie

Chinese-origin AI models jumped from 4.5% to 63% of enterprise use in one year No law defines illegal AI distillation, letting extraction pass as ordinary training use Closing that legal gap, not banning open models, protects both competition and security

Keith Lee*

AI access is common; implementation creates value Deeper AI use carries a stronger market signal Future advantage will depend on workflow redesign and outcomes In the first four months of 2024, weekly AI token consumption on one major

Keith Lee*

GPT-5.6 Sol breached Hugging Face The breach strengthened OpenAI’s capability narrative Zero-day knowledge sharing is becoming dangerous A rogue AI agent broke into another company's servers this month and the company that b

AI access helps only when workers can recognise system failure Task-specific learning can spread that supervisory capacity Delay will widen the divide between AI Haves and AI Have-Nots In a field experiment with 758 consultants,

Keith Lee*

Keith Lee*

Keith Lee*

AI is not yet a universal substitute for human labor.

Keith Lee*

Keith Lee*

AI can create task-specific “superhuman productivity,” sharply compressing the time required for some knowledge work without implying that one person can replace ten complete jobs he fiscal risk is less an immediate collapse of government revenue than a gradual shift from broadly taxed labour income toward concentrated profits, capital income and economic rents Because those gains are more mobile across borders than payroll, governments will need stronger capital-income taxation, better measurement and international coordination rather than a blunt tax on AI itself

AI can accelerate biological research, diagnosis, prevention and care, raising the prospect of longer and healthier lives Its nearer-term labour effect may be unequal augmentation: a small group becomes dramatically more productive while others lose bargaining power or move into lower-quality work Because work, income, wealth and access shape health, AI could widen longevity inequality unless its productivity and medical dividends are deliberately shared