A Primer on the Economics of AI from Justin Wolfers скачать в хорошем качестве

A Primer on the Economics of AI from Justin Wolfers

World Knowledge Forum, Korea, November 19 2024 What happens when a “machine of the mind” meets the modern office? Economist Justin Wolfers maps the micro-to-macro story of AI—who’s affected, how productivity scales to GDP, and why ownership and competition determine who captures the gains—plus practical “me-conomics” for students and workers. He distils studies showing that AI supercharges coders, writers, and support teams—speeding tasks 40–56% in studies—while sparking uneven impacts across professions. He walks through the microeconomics (whose jobs change), the macroeconomics (how much GDP could rise), and the political economy (who captures the gains), before offering practical “me-conomics” for students and workers. 📖 Chapters: 00:00 Introduction 01:18 Microeconomics of AI 09:34 Macroeconomics of AI 24:57 Political economy of AI 29:00 Me-conomics of AI Wolfers explains: • Why AI targets cognitive tasks first—and what that means for translators, copy editors, and document triage • How case studies show 40–56% faster coding and writing, with higher quality and happier customers • Why sector exposure varies (law and back-office vs. physical work like cleaning and maintenance) • How micro productivity becomes macro growth via task automation and capital deepening • Why cheaper compute and rapidly falling model costs change the cost-benefit of automation • How reorganization lags (steam, electrification, PCs) explain slow diffusion—and why AI might adopt faster • The role of innovation spillovers when AI boosts researchers, scientists, and creators • Why ownership matters: the same robot helps workers if they own it, displaces them if the boss or a monopolist does • How monopoly pricing and upstream chip bottlenecks can concentrate AI rents • Why competition policy and open markets shape whether gains flow to many or a few • How to make AI a complement, not a substitute: problem-framing, judgment, and critical thinking • Practical prompting: reduce hallucinations, route math to code tools, and raise tone/quality on demand • Daily workflow tip: test one new AI-assisted task each day to compound learning and leverage • What skills to build now: science, critical thinking, originality, and evaluation over easily automated tasks Consequences: AI could spell a new Utopia, or Dystopia. It's how we manage the moment that matters. Allowing monopolies to dominate could shift most of AI’s gains away from workers and slow broad-based prosperity. 👉 Key takeaway: Treat AI as a complement, not a competitor—and build skills (science, critical thinking, judgment) that AI amplifies rather than replaces. Subscribe for straight-shooting econ with Justin Wolfers.