SOLAR Lab Seminar: Yian Yin, Scientific Production in the Era of Large Language Models

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Yian Yin

Speaker

Yian Yin (Cornell University)

Description

This topic explores scientific production in the era of LLMs, examining the practical and conceptual shifts caused by powerful AI tools. This directly addresses the seminar’s core question of how AI is reshaping research methodologies, forcing a re-evaluation of traditional assumptions about originality, rigor, and contribution in the face of machine-assisted work. See this X thread.

Abstract

Despite growing excitement (and concern) about the fast adoption of generative artificial intelligence (Gen AI) across all academic disciplines, empirical evidence remains fragmented, and systematic understanding of the impact of large language models (LLMs) across scientific domains is limited. 

We analyzed large-scale data from three major preprint repositories to show that the use of LLMs accelerates manuscript output, reduces barriers for non-native English speakers, and diversifies the discovery of prior literatures. However, traditional signals of scientific quality such as language complexity are becoming unreliable indicators of merit, just as we are experiencing an upswing in the quantity of scientific work. 

As AI systems advance, they will challenge our fundamental assumptions about research quality, scholarly communication, and the nature of intellectual labor. Science policy-makers must consider how to evolve our scientific institutions to accommodate the rapidly changing scientific production process.

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