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LearnOPEN is a minimalist platform that helps you slow the scroll and organize your learning. Save and structure high-quality learning resources into personal dashboards and project-based paths. Explore curated content through interdisciplinary themes that invite deeper thinking and focused engagement.

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Is AI about to wipe out jobs and destroy the middle class—or unlock a new era of shared prosperity? In this explainer, scholars and thought leaders walks through one of the most urgent questions of our time: how AI reshapes work, wages, and the social contract itself. Drawing on the work of Katya Klinova and Anton Korinek (“AI and Shared Prosperity”) and Pascal Stiefenhofer’s modeling of AGI-driven economies, this video unpacks two starkly different futures. One is a “doomer” timeline where advanced AI and AGI function as ultra-cheap capital, driving wages toward zero and hollowing out demand. The other is a steered future, where policy, design choices, and ethical guardrails channel AI toward augmenting human labor, creating new tasks, and supporting broadly shared gains. Rather than treating disruption as inevitable, this video argues that where we land is a choice—about incentives, governance, and who owns and benefits from intelligent machines. Topics covered in this video include: • AI, automation, and the future of work • How AI and AGI can drive wage collapse and inequality • The “technological aristocracy” vs. shared prosperity • Klinova & Korinek’s framework for evaluating AI’s impact on labor demand • The difference between today’s task-specific AI and potential AGI • Policy levers: steering innovation, tax incentives, and regulating displacement • Safety net ideas: Universal Basic Income, public/collective ownership of AI assets • Why we may need to renegotiate the social contract in an AI-driven economy Explore the companion pathway here: https://learnopen.org/pathway/83 Find more explainers, frameworks, and curated learning pathways at LearnOPEN.org, helping build smarter, stronger, and more connected communities.














