AI Is Exposing The Limits Of Economics

Source: Tyler Cowen

Tyler Cowen is the Holbert L. Harris Professor of Economics at George Mason University, holding degrees from GMU and a PhD from Harvard, and serves as chairman of GMU's Mercatus Center. He co-founded the highly influential Marginal Revolution blog in 2003 and hosts the Conversations with Tyler podcast produced by Mercatus. He has been recognized as one of Foreign Policy's Top 100 Global Thinkers in 2011 and ranked among the world's most influential economists by Prospect magazine in 2023.

Source: The Federalist

The Federalist is an online magazine that blends news reporting with partisan opinion pieces, often using sensational headlines like those criticizing Democrats and defending conservatives. Wikipedia documents controversies including COVID-19 misinformation, 2020 election falsehoods, a 'Black crime' tag, and labor law violations, indicating a pattern of disputed claims. Its commercial model incentivizes engagement on conservative topics, potentially prioritizing ideology over neutral fact-checking.

Source: Stephen Pimentel

Stephen Pimentel is an independent engineer and essayist in the San Francisco Bay Area, writing on philosophy, history, economics, classics, political philosophy, governance futurism, and AI. He has published multiple articles in Palladium since 2020, covering topics like Bronze Age globalization, Medici banking, liberal education, US reform versus China, and pandemic response competence. His LinkedIn posts show technical familiarity with AI, including self-distillation techniques for models like Llama and Qwen.

Source: The Federalist

The Federalist is an American conservative online magazine that has faced controversies, including allegations of COVID-19 pandemic misinformation, publishing falsehoods during the 2020 election, and using a 'Black crime' tag for articles. Its content features partisan articles critical of Democrats, immigration policies, and cultural leftism, raising questions about incentives to prioritize ideological alignment over neutral reporting. No AllSides or Media Bias Fact Check ratings appear in the provided search results.

unverified_claim

Claims "A 2024 paper in the Journal of Financial Economics found that machine learning feeding on raw price data without any theoretical structure derived from marginalist principles successfully predicted stock returns where conventional economic theory had long since given up hope of doing so."

Bolsters the book's thesis that marginalist economics is being displaced by atheoretical ML methods in finance, a key example of decline.

unverified_claim

States "Researchers at MIT and Harvard have designed a method for what they describe as “fully automated social science,” in which LLMs play the roles of both scientist and experimental subject."

Illustrates AI automating economic/social science research, paralleling marginalism's rise and supporting the analogy to a new revolution.

Source Credibility

Published in The Federalist, described by author bio without noting outlet's strong conservative bias and history of controversies (e.g., misinformation on COVID/elections).

Readers may assume neutral analysis without context on outlet's partisan incentives, though this piece is non-political.

Framing

Presents Cowen's critique admiringly as "one of the more honest performances in recent economic writing: a love letter that doubles as an elegy," emphasizing its rigor without noting Cowen's libertarian background or self-interest as Marginal Revolution founder.

Softens potential self-critique by a prominent economist, framing it as objective intellectual history rather than possibly promotional.

Missing Context

Tyler Cowen's book "The Marginal Revolution: Rise and Decline, and the Pending AI Revolution" was self-published on his personal website as a "generative book" designed for AI interaction, with a free PDF available, rather than through a traditional academic or commercial publisher.

Provides context on the book's non-traditional format and distribution, which may affect perceptions of its academic rigor or peer review status.