Machine Deep Dreaming

This class explores artistic experiments with
emerging technologies related to Artificial
Intelligence and more specifically a subset of AI
called Machine Learning. We will look at hands-on
approaches to working with these Machine Learning
models by interfacing via code and data collection
to look at the impact of these emerging
technologies on human-centric perspectives of
creativity, property and ownership, data
collection, and algorithmic control mechanisms in
cultural production, finance, and surveillance.

The class will take the form of a series of
workshops looking at various machine learning
models in order to explore the future
possibilities and unintended uses in relation to
each student's individual art practices. Topics
include using Generative Adversarial Networks to
generate new images from our own datasets, text to
image generation with Diffusion models,
collaborative writing with GPT, deep fakes with
first order motion, voice-cloning, and other
neural network explorations. We will be learning
some basics of the Python coding language in order
to better understand how these AI models are
constructed.

In addition to workshops, students will engage in
critiques/ discussions around topics related to AI
such as biometric surveillance, predictive
policing algorithms, computer vision,
anthropomorphic projections and cultural
perceptions of AI.