Artificial intelligence and machine learning have improved convenience and eliminated manual tasks in businesses worldwide. However, the data sets on which these systems are trained threaten to maintain—and even amplify—patterns of gender bias seen throughout history. Failure to remove or address gender bias in AI immediately presents the potential for a dramatically imbalanced future.Â
Furthermore, in a tech force dominated by men, women make up only 22% of AI professionals globally. This lack of gender diversity is replicated in the data sets coded in AI algorithm products, reproducing the gender bias in AI throughout outputs. As a result, it arguably amplifies the current gender divide by spreading and reinforcing harmful stereotypes.Â
As more businesses expand internationally, machine translation (MT) systems increasingly aid or replace human translation. Unfortunately, gender-biased data can be exacerbated when MT systems attempt to translate communications into multiple languages. Without careful research and vital corrections, the implications of gender bias in AI and ML may not be recognized until after the damage is done.
Evolving Challenges in Biased Machine Translation
Machine translation systems train on data that consists of hundreds of millions of sentences. The different languages within these data sets express gender differently. For example, literal translation of English text to Spanish requires a system to assign a masculine or feminine context to words that don’t have such connotations in English. This means words like patient, doctor, executive, or scientist would be masculine or feminine. How we sort these words can have implications that are as seemingly harmless as creating an awkward moment or as damaging as denying an individual certain services based on stereotypes.Â
Men hold three-fourths of all tech jobs and the majority of technical and leadership roles. The lack of gender diversity in this sector is more than an example of gender inequity. It threatens to create ripple effects as data sets continually pick up more unintentional bias. As data sets replicate the current gender biases, the potential for expectations for men to fill these roles threatens to widen the gender gap and further reduce career opportunities for people of other genders in industries like life sciences, tech, and global business.
The Long-Term Implications of Subtle Gender Bias
Machine translation bias can manifest in tone, formality, and pronoun assumption. For example, translations from Hungarian to English require the introduction of pronouns not previously included. Pronouns derived from context frequently associate certain adjectives or roles as masculine or feminine.Â
Translations generated by Google Translate associated the terms clever, reading, teaching, research, and making a lot of money with male pronouns. Meanwhile, the terms beautiful, sewing, cooking, and raising a child were translated with female pronouns. It’s easy to see the implications these examples of gender bias could have on women’s career progression when related industries rely on AI translation.
According to Lenovo’s Data for Humanity report, 88% of business leaders think AI technology will be an important factor in helping their organization unlock the value of data over the next five years. When systems operating on biased algorithms are used in recruitment, financial, and medical industries, serious complications will likely arise. Biases that leak into hiring algorithms, medical treatment programs, and financial application approval algorithms have the potential to pose substantial financial burdens and even health consequences.
The Generational Implications
Unfortunately, history suggests we may not recognize the consequences of these biases until after they occur. Currently, women in the US earn about 83 cents for every dollar earned by men. This number hasn’t changed much in two decades.Â
The gender pay gap doesn’t only impact women and their families. It affects the overall economy by stopping women from reaching their full economic potential. Gender biases promoted by AI and automated translation have the potential to exacerbate serious social and economic consequences for decades.
Localization Professionals Can Champion Bias-Free Content
While machine translation has the potential to contribute to gender biases, better handling of this powerful technology can still make a marked difference.Â
Quality translation and localization depend on human intervention and oversight. Localization professionals who embrace AI technology can bridge the gap between AI development teams and global audiences.Â
AI systems are only as good as the data they train on. However, the data can include hundreds of millions of sentences and images, which would be difficult or impossible for linguists to review manually. Eliminating gender bias requires users to identify risks and entry points where unconscious bias creeps in. Translation professionals can introduce diverse training data and intercept potentially biased content before it reaches the target audience.
Responsible AI Beyond International Women’s Day
The global gender gap score in 2024 stands at 68.5%, meaning the gap is 68.5% closed. Based on current data, closing the gap will take 134 years. Responsible AI and machine translation can potentially reduce the gap instead of widening it.Â
Localization leaders can reap time and cost-saving benefits with machine translation. However, they have a responsibility to ensure that MT doesn’t contribute to harmful biases. Localization experts interested in investing in MT in 2025 can contribute to the reduction of gender bias in AI by demanding transparency, diverse training data, and bias auditing as a standard practice, not just for International Women’s Day but as a permanent commitment to equity.Â
Getting the best possible results from machine translation requires a multifaceted approach. Vistatec offers professional translation and localization services with unmatched precision and accuracy to serve the unique needs of your target audience. Contact us today to see how our approach to translation can transform your business growth.