This post announces the top three winners from a 600+ submission essay contest on major AI challenges. Jassi Pannu outlines a state-scale plan to end airborne pathogens, Ege Erdil advises growth-focused policies for countries outside the AI supply chain, and Michael Li compares AI labs’ economics to Hong Kong’s MTR model. Each full essay follows the brief winner descriptions.

• Far-UVC lighting infrastructure could cut seasonal flu mortality 60% and add $1T+ to global GDP for a $40-60B/10-year investment, while also blunting engineered pandemic risk.
• Erdil argues countries outside the AI supply chain should pursue standard growth policies (property rights, low capital taxes, light regulation) rather than geopolitical maneuvering to stay economically relevant.
• Li compares AI labs to Hong Kong's MTR, suggesting labs could offset massive compute costs by owning complementary "adjacent" assets rather than relying solely on core product revenue.

Anthropic warns AI may boost economic growth while displacing millions of workers and urges governments to strengthen unemployment benefits, wage support, retraining, and public services now. If AI eventually replaces broad human labor, it proposes new taxes, digital dividends, universal basic income, and other wealth-sharing measures to redistribute gains.

• Anthropic warns AI could drive massive economic growth while eliminating demand for most human labor, and current welfare systems won't adapt fast enough.
• They propose a three-stage framework, with Stage 3 being when machines handle most tasks, output surges, but millions are left without paid work.
• Anthropic urges governments to act now on unemployment benefits, wage support, and retraining, then later consider AI usage levies, wealth-sharing, or universal basic income if mass displacement occurs.
• They caution that such bold redistribution policies will likely face significant delays, lobbying, and loopholes before implementation.

This article discusses the need for new industrial policies to manage the transition to superintelligent AI. It emphasizes the importance of democratic processes in shaping AI's future, ensuring broad access and mitigating risks. The authors argue for proactive measures to ensure that AI benefits everyone and addresses potential disruptions to jobs and society.

• OpenAI is calling for explicit industrial policy to manage the transition to superintelligent AI rather than leaving it to market forces alone
• The company frames democratic governance and broad access as necessary to prevent AI benefits and power from concentrating among a small few
• Past technological transitions show that translating growth into widespread prosperity required deliberate political action, not automatic diffusion, and superintelligence will require similarly ambitious intervention
• The proposal centers on building new institutions and safeguards to keep advanced AI systems controllable and aligned while rethinking the social contract around jobs and economic participation