Conflicts of Interest in Published NLP Research 2000-2024

TL;DR

This paper analyzes the increasing presence of industry-affiliated authors in NLP research from 2000 to 2024, highlighting a significant rise in conflicts of interest, especially in top-tier conferences, and discusses implications and potential solutions.

Contribution

It provides a comprehensive assessment of conflicts of interest in NLP research over 24 years, quantifying industry involvement and identifying key venues driving this trend.

Findings

27.65% of papers had industry-affiliated authors overall

Over 33% of papers in 2024 involved industry conflicts

Top-tier venues like ACL and EMNLP are main contributors

Abstract

Natural Language Processing research is increasingly reliant on large scale data and computational power. Many achievements in the past decade resulted from collaborations with the tech industry. But an increasing entanglement of academic research and industry interests leads to conflicts of interest. We assessed published NLP research from 2000-2024 and labeled author affiliations as academic or industry-affiliated to measure conflicts of interest. Overall 27.65% of the papers contained at least one industry-affiliated author. That figure increased substantially with more than 1 in 3 papers having a conflict of interest in 2024. We identify top-tier venues (ACL, EMNLP) as main drivers for that effect. The paper closes with a discussion and a simple, concrete suggestion for the future.