Measuring the Gender Gap in Animated Films Using Computer Vision

I’ve always loved animated films. As a child, I would watch my favorite Disney films repeatedly on my family’s VCR. This was in the days before DVDs, decades before streaming. As an adult, I haven’t grown out of it (there’s nothing to grow out of). In fact, whenever there is a new animated movie in cinemas, I like to treat myself to a viewing. When I compare the films released when I was a kid with the ones produced nowadays, I feel like there are important differences in how stories are told and characters are depicted. It feels like there is more diversity of representation. A few months ago, I decided to find out if that really was the case by using neural networks to measure the equality of gender representation in animated films. While all forms of representation matter (gender, ethnic, social-economic, LGBTQ+…), gender in the traditional binary sense (male and female) is easier to measure, so I started there. Here’s what I found: <ul> <li>The percentage of female faces in animated films is on average lower than the percentage of male faces, although there is an overall positive trend towards more equal gender representation.</li> <li>Gender representation is not becoming more equal uniformly across animated films, but rather movies with female main characters are becoming biased towards female faces to the same extent that films with male main characters are biased towards male faces. </li> <li>When characters appear in a group, the male characters tend to outnumber the female characters. In fact, groups with more than one woman are rare. </li> <li>There are films where the female protagonist exists in a male-dominated world, but none yet where the male protagonist is in a female-dominated world. </li> <li>There is a correlation between equality of representation and fairness of representation. </li> </ul> <a href="https://betterprogramming.pub/measuring-the-gender-gap-in-animation-using-ai-fac738be4b19">Website</a>