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A Cross-Disciplinary Reading Group

This website serves as a public record for a reading group on art and algorithms being held this fall 2018 for the Columbia community. On this page you’ll find an overview of five meetings held, as well as links to in-depth notes from our discussions.


This event has passed.


Join us for a reflection on algorithms that generate art.

RSVP on Eventbrite.

What is the difference between a set of instructions for a person and a set of instructions for a computer? Is training a neural network an artistic endeavour? How can we analyze a piece of music that can be generated infinitely? In what ways are our preferences mediated by algorithms?

Come see talks, demos, and performances inspired by a semester of debating and discussing the technical and critical issues surrounding algorithms, art, and the act of creation.

1-2pm: Finite and Infinite Art

Poet & professor of digital media Nick Montfort from MIT

Philosopher James P. Carse ends his book Finite and Infinite Games by stating “There is but one infinite game.” There are, however, many infinite works of art — actually, infinitely many. I will describe several types of finite and infinite artworks and relate these to algorithmic, computational artistic practices. There are many infinite (boundless) artworks that are not based on digital computation or even what people would usually describe as “technology,” while there are many finite (bounded) artworks that are computational. Distinguishing these helps explain how computation (as it is employed in music, visual art, and literary art) can be used to explore that which is bounded along with different infinities.

Lightning Talks

2-3pm: Rapid-fire lightning talks

  • Audrey Amsellem: “You Are What You Stream” : Spotify’s Algorithms
  • Katy Gero: “The best way to predict the future is to make it”
  • David Watkins: Recreating Geometry Using a Limited View
  • Jeanne Devautour & Samuel Boury: Random Walks Through Poetry
  • Liz Bailey: Uncanny Display: Algorithmic Art at the Whitney
  • Oscar Chang: Creativity in Automated Drug Discovery
  • Eamonn Bell: Congratulations! You are now an algorithm!
  • Elizabeth Case: 5 Minutes to Glitch Art

3-4pm: Catered reception

Winning art from the Columbia Data Science Institute Data Art Contest will be displayed.

This event is supported by:

Meeting 1: “Algorithm”

This meeting introduces participants to various definitions of “algorithm,” from historical to contemporary mathematics and from computer science. Readings will be chosen to reflect multiple understandings of the term but also to serve as concrete examples of the diversity of modes of argument, standards of proof, notations, and intellectual priorities within the scientific and artistic communities.

Additionally, we’ve selected some pre-computer artwork that is algorithmic in nature to peruse:

Meeting 2: Garbage in; garbage out?

Some generative models of art require large amounts of training data (in this case, pre-existing artworks) before they can be used effectively. If this training data is of poor quality or does not accurately represent the domain being modeled, the algorithm may fail to produce convincing outputs. Readings will capture the difficulty of arriving at intersubjectively acceptable criteria for evaluating the quality of both input data and generated output.


A timely article from 25 Sept, 2018!

Meeting 3: Artificial interlocutors

Artists and corporations have used artificial interlocutors in their live performances, installations, and advertising campaigns, raising interesting questions about agency and artistic identity in an age of algorithms. Conversational agents also lie at the heart of a growing number of communication systems: customer support lines, chatbots, and voice recognition interfaces. Readings in this meeting will explore what artists have learned from the creation of algorithmic collaborators and what designers of conversational agents can learn from the study of art.

And here are some performances and demos to play with:

Meeting 4: Everything new is old

Recognizing the iterative nature of research entails reckoning with its history of provisional and failed attempts to produce art algorithmically. Readings will examine how the resuscitation of “old science” is facilitated by the appearance of new applications and, relatedly, how classical (and potentially problematic) applications and evaluation regimes—canonical generative task framings, old datasets, and competitions—are used to legitimize new algorithmic arts.

And here are a bunch of demos and interactive examples related to these readings:

Meeting 5: Opening black boxes

Contemporary technological developments mean that decisions made by many kinds of algorithms cannot be always be simply interpreted as a chain of reasoning leading from input to output. Readings explore the concept of “interpretation” in both the statistical and hermeneutic sense, and will examine whether new algorithmic techniques ought to cause us to update our understanding of closely related concepts: causality, explanation, explainability, and even moral accountability.

And here are some demos/short reads: