They, Them, Theirs: Rewriting with Gender-Neutral English

TL;DR

This paper introduces a method for rewriting English sentences to be gender-neutral using the singular 'they', achieving high accuracy without human-labeled data, and discusses its practical and ethical implications.

Contribution

It defines a new rewriting task for gender-neutral English, creates an evaluation benchmark, and trains a model with less than 1% word error rate without human-labeled data.

Findings

Model achieves <1% word error rate in gender-neutral rewriting.

Introduces a benchmark for evaluating gender-neutral language models.

Discusses ethical considerations and practical applications.

Abstract

Responsible development of technology involves applications being inclusive of the diverse set of users they hope to support. An important part of this is understanding the many ways to refer to a person and being able to fluently change between the different forms as needed. We perform a case study on the singular they, a common way to promote gender inclusion in English. We define a re-writing task, create an evaluation benchmark, and show how a model can be trained to produce gender-neutral English with <1% word error rate with no human-labeled data. We discuss the practical applications and ethical considerations of the task, providing direction for future work into inclusive natural language systems.