Related papers: The complementary contributions of academia and industry to AI research

The complementary contributions of academia and industry to AI research

URL: http://arxiv.org/abs/2401.10268v1
Date: Thu, 4 Jan 2024 03:08:13 GMT
Title: The complementary contributions of academia and industry to AI research
Authors: Lizhen Liang (Syracuse University), Han Zhuang (Northeastern University), James Zou (Stanford University), Daniel E. Acuna (University of Colorado at Boulder)
Abstract summary: We characterize the impact and type of AI produced by industry and academia over the last 25 years. We find that articles published by industry teams tend to get greater attention, with a higher chance of being highly cited and citation-disruptive. We find that academic-industry collaborations struggle to replicate the novelty of academic teams and tend to look similar to industry teams.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Artificial intelligence (AI) has seen tremendous development in industry and academia. However, striking recent advances by industry have stunned the world, inviting a fresh perspective on the role of academic research in this field. Here, we characterize the impact and type of AI produced by both environments over the last 25 years and establish several patterns. We find that articles published by teams consisting exclusively of industry researchers tend to get greater attention, with a higher chance of being highly cited and citation-disruptive, and several times more likely to produce state-of-the-art models. In contrast, we find that exclusively academic teams publish the bulk of AI research and tend to produce higher novelty work, with single papers having several times higher likelihood of being unconventional and atypical. The respective impact-novelty advantages of industry and academia are robust to controls for subfield, team size, seniority, and prestige. We find that academic-industry collaborations struggle to replicate the novelty of academic teams and tend to look similar to industry teams. Together, our findings identify the unique and nearly irreplaceable contributions that both academia and industry make toward the healthy progress of AI.

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