AI & Evolving Disciplinary Norms of Inquiry

Overview

This project seeks to understand how the rapid integration of artificial intelligence is transforming the norms that govern how different scientific and scholarly disciplines produce, justify, and communicate knowledge. It begins from the observation that AI systems are no longer confined to domain-specific applications but are increasingly capable of participating in every stage of inquiry, from hypothesis generation to data analysis and publication. The project investigates whether such general-purpose technologies will enrich discipline centered inquiry or erode it by homogenizing epistemic practices across fields. To answer this, it combines conceptual and empirical methods: convening interdisciplinary workshops to study how diverse disciplines negotiate AI's entry into their practices, and conducting an rich, empirical study of the role of AI in the formal mathematics community as a model case for observing how AI reshapes standards of proof, collaboration, and problem valuation. Together, these efforts aim to produce theoretical understanding, frameworks, and practical guidance for integrating AI into science in ways that preserve the richness and heterogeneity of disciplinary inquiry.