Strengthening Subcommunities: Towards Sustainable Growth in AI Research

Abstract

AI’s rapid growth has been felt acutely by scholarly venues, leading to growing pains within the peer review process. These problems largely center on the inability of specific sub-areas to identify and evaluate work that is appropriate according to criteria relevant to each subcommunity as determined by stakeholders of that sub-area. 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 sub-area to confront the issues specific to their process of academic publication and incentivization. This model has 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.

Publication
ICLR 2022 Workshop on ML Evaluation Standards

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