An algorithm is only as good as the dataset it was trained on.
Womaness is an algorithmic reflection of what mainstream media has established as femininity: voluptuous silhouettes, blobs of nude hues everywhere, pink as the predominant color. The images in this series constitute a reflection of the cultural context they were born in.
As AI gains momentum in our culture, I felt compelled to use algorithmic art as a way to visualize the way in which women are represented in mainstream media.
The process focused on stereotypical renditions of femininity. With the algorithm's help, thousands of unique images were generated, each made up of genes of images targeted at women, or depicting women.
The result bears a vague resemblance of what we have defined as feminine. Womaness is not the algorithm’s judgement, but a direct reflection of our visual and cultural landscape; one that reflects a history of over-sexualization, objectification and misrepresentation.
As an additional layer of reflection, the small file size of this piece (<1MB) stands in stark contrast with the unfathomable amounts of data required to train AI algorithms, forcing us to think about the environmental and social consequences of maintaining an ever growing computational power.
This piece was selected entry at the 2020 Small Media Festival. Simon Fraser University, Vancouver, CA.