Missing histories affecting our digital future
Keywords:gender, machine learning, augmented reality, AI
This art project examines non-binary and transgender identity through training machines to generate art based on Greek and Roman statuary. The statuary is binary in nature and appeals to the concept of pinnacles of masculinity and femininity but what of those of us who fall between, what of transgender bodies, gender non-conforming and non-binary bodies and intersex bodies?
Image recognition algorithms have a difficult time classifying people who fall outside the binary, those who don’t pass as cisgender and those who present in neutral or subversive ways. As image recognition becomes more prevalent, we need to have a past and a future for everyone who doesn’t fit neatly into one of the only two boxes on offer. We need to open up the categories, allow people to self-identify or to scrap the concept of gendering people mechanically all together.
As a spatial installation, Hidden Worlds also explores the embodiment of interactive augmented reality bodies in the space between physical and digital worlds. I have worked with a classifier and some deliberately abstract figure works, generated by machine, to explore where gender is assigned in the process and what it looks like when you aren’t neatly classified, and the disconnect that is felt when misgendered. The generated captions have flipped around gender and as the figure resolves and each section is submitted to the narrative writer you see a different set of pronouns, a disconnection between what you see and what you hear. I will explore the assumptions we make about classical art; the way it can inform how we represent gender minorities going forward and how art can illustrate the gaps that exist in the training of these important machine learning systems.
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