Related papers: Position: The Current AI Conference Model is Unsustainable! Diagnosing the Crisis of Centralized AI Conference

Position: The Current AI Conference Model is Unsustainable! Diagnosing the Crisis of Centralized AI Conference

URL: http://arxiv.org/abs/2508.04586v1
Date: Wed, 06 Aug 2025 16:08:27 GMT
Title: Position: The Current AI Conference Model is Unsustainable! Diagnosing the Crisis of Centralized AI Conference
Authors: Nuo Chen, Moming Duan, Andre Huikai Lin, Qian Wang, Jiaying Wu, Bingsheng He,
Abstract summary: This paper offers a data-driven diagnosis of a structural crisis that threatens the foundational goals of scientific dissemination, equity, and community well-being.<n>We identify four key areas of strain: (1) scientifically, with per-author publication rates more than doubling over the past decade to over 4.5 papers annually; (2) environmentally, with the carbon footprint of a single conference exceeding the daily emissions of its host city; and (3) psychologically, with 71% of online community discourse reflecting negative sentiment and 35% referencing mental health concerns.<n>In response, we propose the Community-Federated Conference (CFC) model, which separates peer review, presentation,
Score: 40.70597237357474
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Artificial Intelligence (AI) conferences are essential for advancing research, sharing knowledge, and fostering academic community. However, their rapid expansion has rendered the centralized conference model increasingly unsustainable. This paper offers a data-driven diagnosis of a structural crisis that threatens the foundational goals of scientific dissemination, equity, and community well-being. We identify four key areas of strain: (1) scientifically, with per-author publication rates more than doubling over the past decade to over 4.5 papers annually; (2) environmentally, with the carbon footprint of a single conference exceeding the daily emissions of its host city; (3) psychologically, with 71% of online community discourse reflecting negative sentiment and 35% referencing mental health concerns; and (4) logistically, with attendance at top conferences such as NeurIPS 2024 beginning to outpace venue capacity. These pressures point to a system that is misaligned with its core mission. In response, we propose the Community-Federated Conference (CFC) model, which separates peer review, presentation, and networking into globally coordinated but locally organized components, offering a more sustainable, inclusive, and resilient path forward for AI research.

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