… gender biased algorithms influencing decisions in our society, diversity in the area of machine
learning … Diversity in the development of machine learning technologies could accelerate …

… particularly challenging given the complex way gender ideology is embedded in language.
… of gender bias in training data for machine learning. The work draws upon gender theory and …

… gender and other demographic bias. We focused on evaluating gender bias in traditional
Machine Learning … We identify studying gender bias in facial recognition with advanced deep …

… Discussions between computer scientists and sociologists may improve understanding of
latent gender bias found in machine learning data sets and model predictions. …

… One of the better-known examples of the type of paradox arose during the gender bias
lawsuit in university admissions against UC Berkeley [16]. After analyzing graduate school …

… In our quotidian hiring decisions, generally a gender bias is observed, where usually a male
employee is preferred over a female one. For instance, technical positions at Amazons are …

… gender bias into three separate dimensions: bias when speaking ABOUT someone, bias
when speaking TO someone, and bias … A machine learning model, then, would be unable to …

… -masking as well as each document assigned to a similarity score according to the job
requirements, we will analyze how well a machine learning model can classify the gender-…

… for, gender bias has been conceptualized differently across studies. To date, gender bias in
… In this paper, we intend to put such literature to use for the study of gender bias in MT. We …

… Google Translate’s new feminine and masculine forms for translated sentences exemplifies
how, as this paper also suggests, machine learning translation tools can be debiased, …