How to Write a Bias Statement: Recommendations for Submissions to the Workshop on Gender Bias in NLP
This addresses the problem of insufficient attention to social context in NLP research for workshop participants and the broader community, though it is incremental as it builds on existing workshop practices.
The paper tackles the need for explicit consideration of bias and social implications in NLP research by requiring authors to include bias statements in submissions to the GeBNLP workshop, which was well-received by authors who found the feedback useful. It reports that this initiative will be continued in future workshops.
At the Workshop on Gender Bias in NLP (GeBNLP), we'd like to encourage authors to give explicit consideration to the wider aspects of bias and its social implications. For the 2020 edition of the workshop, we therefore requested that all authors include an explicit bias statement in their work to clarify how their work relates to the social context in which NLP systems are used. The programme committee of the workshops included a number of reviewers with a background in the humanities and social sciences, in addition to NLP experts doing the bulk of the reviewing. Each paper was assigned one of those reviewers, and they were asked to pay specific attention to the provided bias statements in their reviews. This initiative was well received by the authors who submitted papers to the workshop, several of whom said they received useful suggestions and literature hints from the bias reviewers. We are therefore planning to keep this feature of the review process in future editions of the workshop.