# Strengthening Subcommunities: Towards Sustainable Growth in AI Research

arXiv: https://arxiv.org/abs/2204.08377 · HTML: https://mlsanity.com/paper/2204.08377/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 7 references that are in the map.
- First posted on arXiv 18 Apr 2022.

## Builds on (most cited first, 2 of 2)

- [Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment](https://mlsanity.com/paper/2109.09774/) (2021)
- [Avoiding a Tragedy of the Commons in the Peer Review Process](https://mlsanity.com/paper/1901.06246/) (2018)

## Built on by (most cited first, 1 of 1)

- [Group Fairness in Peer Review](https://mlsanity.com/paper/2410.03474/) (2024)

## Abstract (arXiv)

AI's rapid growth has been felt acutely by scholarly venues, leading to growing pains within the peer review process. These challenges largely center on the inability of specific subareas to identify and evaluate work that is appropriate according to criteria relevant to each subcommunity as determined by stakeholders of that subarea. We set forth a proposal that re-focuses efforts within these subcommunities through a decentralization of the reviewing and publication process. Through this re-centering effort, we hope to encourage each subarea to confront the issues specific to their process of academic publication and incentivization. This model has historically been successful for several subcommunities in AI, and we highlight those instances as examples for how the broader field can continue to evolve despite its continually growing size.