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Digital art—and the ideas behind it—is not new. Artists have long used instructions and rule-based systems to produce their work, from 13th-century geometric Islamic tiles to 20th-century avant-garde movements. Infinite Images: The Art of Algorithms reveals how some contemporary artists use mathematical principles, chance, and automation to design and work with generative systems. In generative art, the artist creates an automated system to produce the artwork. This might be written instructions for others to follow or a computer program. In the process, they give up some control over the end result. The artist creates the rules, and the system generates the outcomes. This approach, whether analog or digital, enables the artist to experiment with multiple variations within a set of defined constraints—often yielding unexpected results.

Our world is increasingly shaped by algorithms and by media generated by artificial intelligence (AI). This exhibition returns to computer art’s beginnings in the 1960s and also takes a closer look at the wave of generative art that has emerged over the last decade. The works assembled here expose the foundational processes that underlie computer-generated imagery and invite us to reflect on what distinguishes computer-generated art from other media.

Artworks

1. The Imaginary Machine

2. Chance & Control

3. Digital Materiality

4. Coded Nature

Events

Infinite Images: The Art of Algorithms Member Preview

July 11, 2025
5:00 pm

Green Building, Libbey Court Free for All

Member Preview Tour Infinite Images: The Art of Algorithms

July 11, 2025
5:15 pm

Green Building, Canaday Gallery Free for members

The Artist’s New Tools: Art, Code & Generative Systems

July 12, 2025
11:30 am

Green Building, Great Gallery Free for All

Opening Day Tours of “Infinite Images: The Art of Algorithms”

July 12, 2025
1:00 pm

Green Building, Canaday Gallery Free for members, $10 for non-members

Essays

Decoding Generative Art

Julia Kaganskiy, curator of Infinite Images: The Art of Algorithms

Since the dawn of the modern computing era in the mid-twentieth century, artists have worked alongside engineers (and, in fact, often as engineers themselves) to investigate the potential of computational tools and their impact on creativity, culture, and the human experience writ large. At the heart of this pursuit has been a sustained study and engagement with algorithms, generative systems, and automation as both the materials and animating forces that have come to define not just the art of this era, but the cybernetic logic and values that have embedded themselves so deeply into how society understands itself.

Art Making Machines

By Ruby Thelot

“A wall divided horizontally and vertically into four equal parts. Within each part, three of the four kinds of lines are superimposed.”

These are the instructions given to Jerry Orter, Adrian Piper, and Sol LeWitt to execute Wall Drawing 11 at Paula Cooper Gallery in New York in 1969, by LeWitt himself. A clear list of steps—prescriptive and executable. Drawing distilled into idea. Idea existing as a set of rules. Pure concept. The role of the pre-set rules is to “[avoid] subjectivity,” LeWitt explains in his 1967 Artforum essay, “Paragraphs on Conceptual Art”. He adds that, “In conceptual art the idea or concept is the most important aspect of the work. When an artist uses a conceptual form of art, it means that all of the planning and decisions are made beforehand and the execution is a perfunctory affair. The idea becomes a machine that makes the art.”

Towards Ekphrastic Writing for Digital Arts

Regina Harsanyi

When art historians describe visual works, they often use ekphrasis. Ekphrasis can be defined as detail-driven language meant to transport readers or listeners with great vividness to works of art they have otherwise not witnessed. In service of ekphrasis, art history includes a developed, sophisticated vocabulary for discussing traditional materials and processes.

A subfield of artificial intelligence that uses generative models trained on large data sets to create new content—text, images, music, or videos—by mimicking the underlying structures, patterns, and styles of what it was trained on. Popular commercial generative AI tools like ChatGPT, Dall-E, and Midjourney use a chatbot feature where users can prompt the AI system using natural language rather than code. These large-scale systems are trained using trillions of data points collected from the internet and are controversial for the way they appropriate (and imitate) existing intellectual property and for their energy usage and environmental impact.

Art created using autonomous systems like computer algorithms, AI models, or rule-based processes where the artist sets up initial parameters but then allows the system to independently produce or contribute to the

final artwork. The artist designs the process rather than directly creating every element, embracing randomness, complexity, and emergence to produce results that often could not be fully predicted beforehand.

A step-by-step set of instructions or rules for solving a problem or completing a task. A recipe is an algorithm, as is a computer program.

The ability of a computer to simulate human intelligence by performing tasks such as learning, reasoning, problem-solving, and understanding language. AI systems can analyze data, recognize patterns, make predictions, and adapt their behavior based on experience.

Formalized by Claude Shannon in 1948, information theory studies how information is measured, stored, and communicated. It examines the mathematical laws governing data compression, transmission, and error correction. At its core, it defines information as the reduction of uncertainty. It measures how surprising or unpredictable a message is rather than its meaning or importance.

A system that produces unpredictable sequences of numbers. Computers use mathematical algorithms (pseudorandom) or physical processes (true random) to generate these numbers, which are essential for encryption, simulations, games, and creating variety in digital art and other applications.

When simple elements interact to create complex behaviors or patterns that could not be predicted from the individual components alone. It’s how ant colonies organize without a leader, how consciousness arises from neurons, or how water molecules create waves: Something new emerges from simpler parts interacting.