How to Write a Bias Statement: Recommendations for Submissions to the Workshop on Gender Bias in NLP
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 2 of its 3 references that are in the map. First posted on arXiv 7 Apr 2021.
Builds on
2 of 3 references.
References · 2
Built on by
Citing papers per year: 2021: 2; 2022: 1; 2023: 1; 2024: 0; 2025: 1.
5 papers.
- 2021Gender Bias in Machine Translationcited by 116
- 2021How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translationcited by 11
- 2022Experimental Standards for Deep Learning in Natural Language Processing Researchcited by 9
- 2023Responsible AI Considerations in Text Summarization Research: A Review of Current Practicescited by 2
- 2025Practising responsibility: Ethics in NLP as a hands-on coursecited by 0
- 2025Practising responsibility: Ethics in NLP as a hands-on course31 Dec 2025
- 2023Responsible AI Considerations in Text Summarization Research: A Review of Current Practices18 Nov 2023
- 2022Experimental Standards for Deep Learning in Natural Language Processing Research13 Apr 2022
- 2021How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation28 May 2021
- 2021Gender Bias in Machine Translation13 Apr 2021