Joel Mokyr, one of the 2025 Nobel Laureates in Economics, has extensively analyzed the mechanisms behind the Industrial Revolution in Britain and Europe. In his key works, The Gifts of Athena, The Enlightened Economy, and Culture of Growth, Mokyr emphasizes the critical role of knowledge institutions. Societies require a “knowledge community” where knowledge is openly debated rather than monopolized. He distinguishes between propositional knowledge (scientific) and prescriptive knowledge (engineering and craft), noting that industrial revolutions require a combination of both. Mokyr also highlights cultural shifts: in early modern Europe, Baconian ideas promoted knowledge innovation as both an honor and duty, enabling science to move from theory to practice.

Mokyr’s analysis resonates with the historical “Great Divergence” debate, which questions why the Industrial Revolution emerged in Europe, not in similarly advanced regions like China’s Jiangnan during the Ming and Qing dynasties. Scholars offer different perspectives: Douglas North emphasized early property rights and modern corporate institutions, Daron Acemoglu pointed to inclusive political and legal systems, while Kenneth Pomeranz highlighted resource constraints, particularly coal availability, as a key economic factor. China’s Jiangnan lacked sufficient local coal, making labor-saving technologies less profitable compared with Britain.

Looking forward, Mokyr’s concept of general-purpose technologies (GPTs) applies to artificial intelligence. Scalable and combinable technologies, like electricity and computing in the past, now include large language models (LLMs), which underpin systems like ChatGPT and DeepSeek. While current AI demonstrates scalability, true Artificial General Intelligence (AGI) remains unrealized, and the race to AGI may define future economic leadership, particularly between the United States and China.

In higher education, Mokyr’s framework encourages integrating propositional and prescriptive knowledge. Universities are urged to adapt curricula and teaching methods to AI-driven innovation, including supervised AI writing and programming exercises, to prepare students for a knowledge economy where AI augments rather than replaces human creativity.