On the Gap between Adoption and Understanding in NLP


There are some issues with current research trends in NLP that can hamper the free development of scientific research. We identify five of particular concern: 1) the early adoption of methods without sufficient understanding or analysis; 2) the preference for computational methods regardless of risks associated with their limitations; 3) the resulting bias in the papers we publish; 4) the impossibility of re-running some experiments due to their cost; 5) the dangers of unexplainable methods. If these issues are not addressed, we risk a loss of reproducibility, reputability, and subsequently public trust in our field. In this position paper, we outline each of these points and suggest ways forward.

In Findings of the Association for Computational Linguistics: ACL 2021