How online images fuel gender bias

In a pioneering study, Guilbeault and colleagues examined how gender bias is conveyed through online images versus text and its impact on users. They focused on a simple measure of bias: the frequency with which women or men are associated with specific professions (e.g., doctor or nurse) and social roles (e.g., neighbor or friend). The researchers analyzed nearly 350,000 images from Google Images and used AI to examine billions of words from Google News to study gender bias in both occupations and social roles.