AI Business Models, Rare Earths, and China's Economic Challenges

In this episode of Econ 102, Erik Torenberg and economist Noah Smith analyze the potential impacts of AI on GDP and productivity, referencing Darren Acemoglu's framework and discussing whether AI will replace, augment, or create new tasks for humans. They explore recent data suggesting a slight acceleration in labor productivity since the advent of ChatGPT, while also acknowledging studies indicating that many companies have not yet seen productivity increases from AI implementation. The conversation shifts to the possibility of an AI-driven capex boom and bust, drawing parallels with historical booms in railroads and telecoms, and questions whether AI's value creation will translate into value capture for AI companies, comparing it to industries like farming and airlines. They also discuss China's macroeconomic challenges, including the real estate bust, over-competition in industries like electric vehicles, and deflation, and consider potential policy recommendations.