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

Summary

This paper talks about the problems with the current way AI conferences are organized, highlighting issues like too many papers being published, the big carbon footprint from travel, community dissatisfaction, and messy logistics. It suggests a new Community-Federated Conference model as a solution to make these events better and more sustainable.

What's the problem?

The problem is that AI conferences have become overwhelming with too many papers, causing difficulties in keeping quality high. They also create a large environmental impact because many people travel long distances to attend. Plus, many members of the AI community feel unhappy or excluded, and organizing these events has become very complicated.

What's the solution?

The solution proposed is a Community-Federated Conference model, which spreads conference activities across multiple local or regional groups instead of centralizing everything in one place. This approach reduces travel, lowers environmental damage, and helps build a stronger, more inclusive community by making conferences accessible and manageable for more people.

Why it matters?

This matters because AI conferences are important for sharing knowledge and advancing the field, but if they continue to grow unsustainably, they could harm the environment and alienate people. The new model aims to create healthier, fairer, and greener ways for the AI community to come together and collaborate.