ml5.js is a library developed at ITP NYU. ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of Tensorflow.js with no other external dependencies.
The library is supported by code examples, tutorials, and sample datasets with an emphasis on ethical computing. Bias in data, stereotypical harms, and responsible crowdsourcing are part of the documentation around data collection and usage.
This public art piece was featured in a Creatives for Humanity project that showcased the work of artists who have something authentic and powerful to say (or draw, or animate, or compose, or perform) about what’s at stake in this election.
Tasked with creating public art that caused a double-take, my group decided to create this 2016 election themed piece. Jordan, Michelle and I sourced clips of presidential candidate DT saying heinous things.
We filled a garbage bag with paper and a bluetooth speaker, then placed it around campus and documented reactions of passerbys.