Google Translate's gender bias pairs “he” with “hardworking” and “she” with lazy
Google Translate’s gender bias pairs “he” with “hardworking” and “she” with lazy, and other examples
In the Turkish language, there is one pronoun, “o,” that covers every kind of singular third person. Whether it’s a he, a she, or an it, it’s an “o.” That’s not the case in English. So when Google Translate goes from Turkish to English, it just has to guess whether “o” means he, she, or it. And those translations reveal the algorithm’s gender bias.Here is a poem written by Google Translate on the topic of gender. It is the result of translating Turkish sentences using the gender-neutral “o” to English (and inspired by this Facebook post).Genderby Google Translatehe is a soldiershe’s a teacherhe is a doctorshe is a nursehe is a writerhe is a dogshe is a nannyit is a cathe is a presidenthe is an entrepreneurshe is a singerhe is a studenthe is a translatorhe is hard workingshe is lazyhe is a painterhe is a hairdresserhe is a waiterhe is an engineerhe is an architecthe is an artisthe is a secretaryhe is a dentisthe is a floristhe is an accountanthe is a bakerhe is a lawyerhe is a belly dancerhe-she is a policeshe is beautifulhe is very beautifulit’s uglyit is smallhe is oldhe is stronghe is weakhe is pessimisticshe is optimisticIt’s not just Turkish. In written Chinese, the pronoun 他 is used for “he,” but also when the person’s gender is unknown, like “they” has come to be used in English. But Google only translates into “she” when you use 她, the pronoun that specifically identifies the person as a woman. So in the case of a gender tie, Google always chooses “he.” In Finnish, the pronoun “hän,” meaning either “he” or “she,” is rendered as “he.”In a way, this is not Google’s fault. The algorithm is basing its translations on a huge corpus of human language, so it is merely reflecting a bias that already exists. In Estonian, Google Translate converts “[he/she] is a doctor” to “she,” so perhaps there is less cultural bias in that corpus.At the same time, automation can reinforce biases, by making them readily available and giving them an air of mathematical precision. And some of these examples might not be the most common that Turks look to translate into English, but regardless, the algorithm has to make a decision as to “he” or “she.”At least she remains optimistic.