The Human Edge

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Bibliographic details

• Authors: PABLO PENA
• Published: November 17, 2025

Overview

• Publication: F&D Magazine; PABLO PENA; December 2025.
• Core thesis: Three components of human capital—curiosity, critical thinking, and self-regulation—are crucial complements to artificial intelligence (AI) and help determine whether AI augments or substitutes human capabilities.
• Key implication: Continued investment in and cultivation of these human-capital attributes is necessary to push the knowledge frontier, preserve innovation, and realize the benefits of AI.

Curiosity

• Arguments and examples:
  • Historical thought: Alfred Marshall and Michel Foucault emphasized the centrality of human capital to rising living standards.
  • Thought experiment: Feeding all human-recorded data up to the year 1939 into a large language model (LLM) would not allow the LLM to produce The Beatles’ “Yesterday” because:
  • There would be insufficient information about future creators’ life experiences.
  • A vague prompt (adjectives like melancholic, timeless, elegant, lyrical, intimate) would not narrow possibilities sufficiently.
  • Extension beyond art: LLMs summarize existing studies (e.g., on reducing gun violence in Chicago) but do not empirically design, fund, execute, and evaluate new interventions—human curiosity drives that new research.
  • Peak data concept: We may reach a point when all available information has been incorporated into LLMs (“peak data”); without humans generating new information, LLM outputs will stagnate.
  • Financial-market analogy: Parallels Sanford Grossman and Joseph Stiglitz’s refinement of the efficient market hypothesis—if no one gathers information, prices/information cannot reflect new knowledge; similarly, AI requires humans to produce new knowledge for continued improvement.
• Finding:
  • Curiosity and AI function as complements; AI improves only if humans keep developing new ideas and pushing the knowledge frontier.

Critical thinking

• Distinction between domains:
  • In hard sciences, LLMs can give definitive answers that do not require lay judgment.
  • In social sciences and humanities, LLM outputs remix historical arguments and rarely yield definitive answers; human judgment is necessary.
• Examples of socially meaningful questions where judgment matters: “How do I know someone is in love with me? Is there a God? Should I have children? Who should I vote for in the presidential election?”
• Risks:
  • Campbell’s law: “The more any quantitative social indicator is used for decision-making, the more subject it will be to corruption pressures.”
  • Data poisoning: Widespread reliance on LLMs creates incentives for bad actors to contaminate training data with disinformation, making vigilance and critical thinking essential.
• Finding:
  • Critical thinking is essential to interpret, vet, and apply AI-generated information, especially in social-science contexts vulnerable to manipulation.

Self-regulation

• Argument:
  • AI can produce personalized plans and recommendations (e.g., workout plans, retirement savings advice, alcohol consumption guidance), but outcomes depend on human discipline and follow-through.
• Historical grounding:
  • Adam Smith in The Theory of Moral Sentiments emphasized superior reason and “self-command” to forego present pleasure for greater future benefits.
• Household production and the weakest-link problem:
  • Household production transforms purchases into consumed value through time, effort, and skill; Michael Kremer’s O-ring theory illustrates that other inputs cannot substitute for individual effort when the weakest link fails.
  • As AI’s informational quality improves, the limiting factor will increasingly be human ability to implement known best actions.
• Finding:
  • The benefits of self-regulation will grow as AI becomes better at supplying relevant information, making cultivation of self-discipline a higher-return investment.

Human capital (integration and future scenarios)

• Development:
  • Curiosity, critical thinking, and self-regulation are forms of human capital that grow when environments (schools, workplaces) encourage questioning, reflection, and autonomy; environments that discourage these traits erode them.
• Singularity scenarios (two speculative paths):
  • Adversarial scenario: Humans and machines are adversaries (e.g., The Matrix); each generation’s human capital is the means of resistance, prioritizing its accumulation.
  • Coexistence scenario: AI and humans peacefully coexist; interactions might resemble humans working for large organizations—AI aggregates greater brainpower but compensates humans for their knowledge and skills. Some people may prefer AI-free, low-tech communities relying on member human capital.
• Historical stages of technological change:
  • Mechanization of agriculture, automation of manufacturing, and “algorithmization” of services each freed and demanded human capital in different areas.
  • Displaced human capital in one stage supported the next stage’s boom (e.g., mechanized agriculture enabled manufacturing boom; automated manufacturing enabled services boom); AI is poised to enable the next boom.
• Contemporary evidence:
  • Firms (example cited: Meta) recruiting human talent with large compensation packages to develop more powerful AI technologies indicate the ongoing importance of human capital.
• Finding:
  • Investing in human capital remains a strong policy priority across scenarios; human capital will remain relevant in new and hard-to-foresee ways and will create value in future sectors.

Podcast and author note

• Podcast summary:
  • Pablo Peña and journalist Rhoda Metcalfe discuss the article in the December issue of Finance & Development; Peña argues that critical thinking and curiosity will keep humans “in the driver’s seat” despite AI’s performance.
• Author:
  • PABLO PENA is an associate instructional professor in the University of Chicago’s economics department and author of Human Capital for Humans: An Accessible Introduction to the Economic Science of People.

Source: The Human Edge, PABLO PENA; December 2025.

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