machine translation bias removal tool
DEMO

About this project

We need to talk about bias in machine translation. Translations produced by machines are often biased because of ambiguities in gender, number and forms of address. For example, when translating from English into French, should student be translated as male étudiant or female étudiante? Should you be translated as informal tu or formal vous? Machines often resolve these ambiguities badly and with bias because they don’t know what the user meant.

Fairslator is an experimental application which removes many such biases. Fairslator works by examining the output of machine translation, detecting when bias has occurred, and correcting it by asking follow-up questions such as Do you mean male student or female student? Are you addressing the person casually or politely? Fairslator is a human-in-the-loop translator, built on the idea that you shouldn’t guess if you can ask.

Who is behind it?

Michal Měchura My name is Michal Měchura. I am a freelance language technologist. I started Fairslator because I was frustrated with how badly machine translators handle ambiguous input. No matter how smart the AI gets, some ambiguities will always be unresolvable because there are no clues in the input text. The only way to resolve them is to ask the user to disambiguate. Fairslator is where I’m tinkering with algorithms and UX for doing exactly that.

What next?

Read more about bias and ambiguity in machine translation.
Cover page
We need to talk about bias
in machine translation
The Fairslator whitepaper
Download
Sign up for my very low-traffic mailing list. I'll keep you updated on what's new with Fairslator and what's happening with bias in machine translation generally.
Your address is safe here. I will only use it to send you infrequent updates about Fairslator. I will not give or sell it to anyone. You can ask me to be taken off the list at any time.

Faislator blog

| Status update
What's new with Fairslator #2
Fairslator now speaks French, and other news.
| Gendergerechte Sprache
Kann man das Gendern automatisieren?
Überall Gendersternchen verstreuen und fertig? Von wegen. Geschlechtergerecht zu texten, das braucht vor allem Kreativität.
| Oh là là
Three reasons why you shouldn’t use machine translation for French
But if you must, at least run it through Fairslator.
| Ó Bhéarla go Gaeilge
Tusa, sibhse agus an meaisínaistriúchán ó Bhéarla
Tugaimis droim láimhe leis an mhíthuiscint nach bhfuil ach aon aistriúchán amháin ar gach rud.
| Status update
What's new with Fairslator #1
A new language pair, some new publications, plus what's in the pipeline.
| Machine translation
Finally, an Irish translation app that knows the difference between ‘tú’ and ‘sibh’
It asks you how you want to translate ‘you’.
| Forms of address
Why machine translation has a problem with ‘you’
This innocent-looking English pronoun is surprisingly difficult to translate into other languages.
| Male and female
10 things you should know about gender bias in machine translation
Machine translation is getting better all the time, but the problem of gender bias remains. Read these ten questions and answers if you want to understand all about it.
| Machine translation in Czech
Finally, a translation app that knows the difference between Czech ‘ty’ and ‘vy’!
Wouldn’t it be nice if machine translation asked how you want to translate ‘you’?
| Gender bias in machine translation
Gender versus Czech
In Czech we don’t say ‘I am happy’, we say ‘I as a man am happy’ or ‘I as a woman am happy’.
| Strojový překlad
Představ si, že jseš stroj, který překládá
Proč se překladače nikdy neptají, jak to myslíme?
| German machine translation
Finally, a translation app that knows the difference between German ‘du’ and ‘Sie’!
Wouldn’t it be nice if machine translation asked how you want to translate ‘you’?
| Maschinelle Übersetzung
Stell dir vor, du bist DeepL
Warum fragt der Übersetzer eigentlich nicht, was ich meine?

Fairslator timeline

icon September 2022 — Fairslator was presented and demoed at the Text, Speech and Dialogue (TSD) conference in Brno.
icon August 2022Translations in London are talking about Fairslator in their blog post Overcoming gender bias in MT. They think the technology behind Fairslator could be useful in the translation industry for faster post-editing of machine-translated texts.
August 2022 — A fourth language pair released: English → French.
icon July 2022 — Germany's Goethe-Institut interviewed us for the website of their project Artificially Correct. Read the interview in German: Wenn die Maschine den Menschen fragt or in English: When the machine asks the human, or see this short video on Twitter.
icon May 2022Slator.com, a website for the translation industry, asked us for a guest post and of course we didn't say no. Read What You Need to Know About Bias in Machine Translation »
April 2022 — A third language pair added: English → Irish.
February 2022 — Fairslator launched with two language pairs: English → German, English → Czech. Cries of excitement from everywhere!