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

TL;DR

The paper argues that the centralized AI conference model is unsustainable due to rapid publication growth, environmental impact, mental health concerns, and venue capacity bottlenecks. It combines quantitative metrics from CSRankings, conference data, and Reddit sentiment analysis to diagnose the crisis and demonstrates misalignment with the four conference goals. It proposes the Community-Federated Conference (CFC), with Layer 1 unified rolling peer review, Layer 2 federated regional hubs, and Layer 3 a digital synchronization layer, to decouple review, dissemination, and community building. The approach aims to reduce travel emissions, ease reviewer workloads, and foster inclusive participation, representing a scalable path for sustainable and equitable AI research. The paper also provides practical implementation details and invites community adoption.

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.

Figures (9)

• Figure 1: Publication growth in AI vs. Other CS Fields over the past decade, with 2030 projections.
• Figure 2: Growth of effective faculties by CS domain.
• Figure 3: Average contribution per effective faculty.
• Figure 4: Geographic distribution of NeurIPS 2024 first authors. Larger and darker blue circles represent a higher concentration.
• Figure 5: Surging carbon emissions from ICML.