AI's Influence on Research Novelty and Economic Growth Explored in New NBER Paper

Toronto, ON – Professor Joshua Gans, a leading economist specializing in innovation and digital strategy, has released a new working paper through the National Bureau of Economic Research (NBER) that delves into the profound impact of artificial intelligence on knowledge creation and long-term economic growth. The paper, titled "Growth in AI Knowledge," proposes a novel general equilibrium model to formalize the trade-off between AI’s ability to span broad knowledge gaps (coverage) and its accuracy. Gans, who holds the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at the Rotman School of Management, University of Toronto, announced the paper’s release, stating in a recent social media post, "It has been a couple of weeks but here’s a new paper…" The NBER Working Paper series is a crucial platform for economists to disseminate their preliminary research findings rapidly, often before formal peer review and journal publication. This allows for timely discussion and feedback within the academic and policy communities. The paper highlights a significant finding: AI fundamentally alters the novelty of research. According to the abstract, when AI systems offer "sufficiently broad coverage," they incentivize "exploratory research that taps into novel, distant areas of knowledge and accelerates long-run growth." Conversely, the research suggests that "limited coverage promotes incremental research that may boost short-term efficiency while dampening the overall advancement of new ideas." Gans's analysis further emphasizes that the nature of knowledge itself—whether it is novel or dense—plays a critical role in determining the growth and welfare implications of AI. The study also examines the influence of market structure, licensing arrangements, and regulatory frameworks, offering policy-relevant insights that aim to reconcile the immediate benefits of AI adoption with the imperative of sustainable long-term economic expansion. This work builds on Gans's extensive research portfolio, which includes influential books like "Prediction Machines" and "Power & Prediction," both exploring the economic implications of AI.