Sarah Friend
Perverse Affordances, 2018
Digital images, generative adversarial network
Copyright The Artist
Perverse affordances hails from 2018, which from today's era feels like machine learning deep history. Starting with a bot that crawled large global social media platforms and amassed a custom...
Perverse affordances hails from 2018, which from today's era feels like machine learning deep history.
Starting with a bot that crawled large global social media platforms and amassed a custom dataset of over 10000 screenshots, Friend then used them to train a custom machine learning model. As a final step, Perverse Affordances used the new “social media screenshots” that are generated like wireframes, to imagine new online interactions or possible web layouts.
Taking social media as a location - a place where machine learning algorithms are "watching" our online selves all the time, Perverse Affordances turns the act of "watching" around on itself. How does an algorithm sees an interface? Can we make the platform visible by looking at it with a new (machine) eye?
Starting with a bot that crawled large global social media platforms and amassed a custom dataset of over 10000 screenshots, Friend then used them to train a custom machine learning model. As a final step, Perverse Affordances used the new “social media screenshots” that are generated like wireframes, to imagine new online interactions or possible web layouts.
Taking social media as a location - a place where machine learning algorithms are "watching" our online selves all the time, Perverse Affordances turns the act of "watching" around on itself. How does an algorithm sees an interface? Can we make the platform visible by looking at it with a new (machine) eye?
