Evaluation for Change

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Abstract

Evaluation is the central means for assessing, understanding, and communicating about NLP models. In this position paper, we argue evaluation should be more than that: it is a force for driving change, carrying a sociological and political character beyond its technical dimensions. As a force, evaluation's power arises from its adoption: under our view, evaluation succeeds when it achieves the desired change in the field. Further, by framing evaluation as a force, we consider how it competes with other forces. Under our analysis, we conjecture that the current trajectory of NLP suggests evaluation's power is waning, in spite of its potential for realizing more pluralistic ambitions in the field. We conclude by discussing the legitimacy of this power, who acquires this power and how it distributes. Ultimately, we hope the research community will more aggressively harness evaluation to drive change.

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APA

Bommasani, R. (2023). Evaluation for Change. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 8227–8239). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.findings-acl.522

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