Artificial Intelligence and Machine Learning in the Arts is a groundwork-laying introduction to the field of Machine Learning – focusing on its creative applications and social impact. The course looks at accessible Machine Learning tools used for purposes, such as interaction design and composition, that do not require programming.

We will take a close look at several Machine Learning algorithms to see what is being ‘learned’ and how. In the second half of the course, we’ll focus on getting acquainted with development environments that are common in pursuing independent experimentation with Machine Learning.

Throughout the course, we also zoom out and assess some of the big issues that have revealed themselves at the sites of ML adoption related to bias, privacy and positive feedback.

Altogether, the course aims to do the following:

  • Bypass the hype and speculation common to AI as a topic
  • Leverage Humanities/Arts and STEM to build balanced understanding of AI & ML
  • Maintain paths for multiple levels of engagement with the material
  • Frame Machine Learning in the context of “automation” and increase visibility of its use

Course Content

Course Introduction
Data
Algorithms I
Bias
Algorithms II
Algorithms III
Skills for ML
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