What is Generative Art?
Generative art is art created using a set of rules inserted into a system such that the system executes the creation of the artwork, not the artist.
In the context of digital art, rather than the artist manually crafting each detail, they design a set of rules or instructions — i.e., an algorithm — for the computer to follow. The computer then follows these rules to generate unique pieces of art.
This process can produce intricate patterns, abstract designs, and complex images that are often unpredictable and unique. The artist controls the overall direction, but the final outcome is a collaboration between the artist and the computer.
Under this broad definition, a historical example of generative art might be Islamic tiling, where artisans followed intricate rule-based systems to generate geometric designs known as girih. In a more contemporary context, artists like Sol LeWitt, who created instruction-based text art that allowed others to create outputs of the work, also fit within this definition.
In the 1960s, the terms “computer art” and “generative art” were often used interchangeably to describe algorithmically generated artworks. In 1995, Jean-Pierre Hébert, an early pioneer, introduced the term “algorist” to describe artists working creatively with code. Frieder Nake, another leading figure in computer-generated art (about whom, more below), emphasized that the term “algorithmic art” more accurately reflected the revolutionary impact of algorithms on art.
Today, the practice described above is known simply as “generative art,” though the term “algorithmic art” might well make a comeback to distinguish artists working in this vein from artists using GAN or diffusion model AI for image creation.
What follows is a brief introduction to a small selection of influential generative artists, the first half focusing on early pioneers and the second half highlighting more recent examples, specifically artists working on-chain. Generative art is a massive genre with many nuances, a topic that deserves volumes-worth of elaboration, and this post will serve as a mere amuse-bouche to the interested.
Herbert W. Franke
Herbert W. Franke (1927–2022) was a pioneering digital artist, scientist, and writer whose work significantly influenced the field of generative art. With a background in physics and mathematics, Franke began creating digital art in the 1950s using an analog computer he built with a friend.
His early series Dance of the Electrons (1959/62) showcased his innovative use of technology to produce art. In the 1970s, he utilized interactive 3D systems at the Siemens research lab in Germany to create some of the first computer animations and later explored fractal patterns with the DRAKULA series.
Franke’s contributions extended beyond his artwork; he authored seminal books like Computer Graphics, Computer Art (1971) and taught “Cybernetical Aesthetics” at Munich University. In 1979, he co-founded Ars Electronica, a leading institution for new media art.
Throughout his life, Franke continuously adapted to technological advancements, including creating NFTs in his later years. His legacy is preserved through his extensive archive at the ZKM Center for Art and Media and his continued influence on the generative art movement.
Frieder Nake
Frieder Nake is regarded as one of the founding fathers of digital computer art, producing his first works in 1963. Influenced by Max Bense’s Information Aesthetics, Nake’s early work involved creating abstract images using computer programs.
His significant work phases include the compArt ER56 (1963-65), Walk-through-raster (1966), Matrix Multiplication (1967/68), and Generative Aesthetics I (1968/69). Nake first exhibited his drawings in 1965 at Galerie Wendelin Niedlich in Stuttgart and was part of all major international computer art exhibitions.
Nake’s approach to computer art emphasized the process over the outcome. For example, his Matrix Multiplication portfolio involved producing numerical matrices and programming a computer to multiply these numbers to generate visual outputs.
Nake argued that each piece of algorithmic art is merely one instance of the many possible outcomes defined by the algorithm, highlighting the algorithm‘s potential rather than the individual artworks. This perspective was reflected in his statement that computer art transforms the role of the artist, making the human subject almost nonexistent once the boundary conditions for the image are set.
Sol LeWitt
Sol LeWitt (1928–2007) was a pioneering conceptual artist whose instruction-based artwork has played a crucial role in bridging the gap between conceptual art and the emerging field of generative art. Though LeWitt did not use computers, his approach to art-making resonates strongly with the principles of generative art, where the artist sets the parameters, and the execution follows a predefined set of rules or instructions (which is why we are including him in this overview).
LeWitt’s methodology involved creating detailed instructions for others to follow in producing his artworks. This process relinquished the artist’s control over the final outcome, allowing for variations and interpretations by those executing the work.
His Wall Drawings series, which began in the late 1960s, is a prime example of this approach. Each piece consisted of a set of written instructions detailing how to create geometric shapes and patterns directly on walls. The instructions could be executed by anyone, emphasizing the idea that the concept behind the work was more important than the physical act of creating it.
This instruction-based method aligns with the core concept of generative art, where the artist’s role shifts from creator to designer of a system that generates art. His statement that “the idea becomes a machine that makes the art” encapsulates this philosophy and underscores the connection between his work and generative art.
By demonstrating, with the traditional institutional art world context, that art could be generated through a set of instructions, LeWitt provided a conceptual framework that validated and encouraged the exploration of algorithmic processes in art. His work helped bridge the gap between the traditional art world and the then-disregarded realm of computer-generated art, paving the way for future artists to explore the intersection of art and technology.
Vera Molnár
Vera Molnár (1924–2023) was a pioneering figure in digital and algorithmic art, whose work bridged the gap between geometric abstraction and the emerging field of computer-generated art. Born in Budapest and later becoming a celebrated French artist, Molnár was influenced by the geometric purity of Bauhaus artists like Josef Albers and the abstract tenderness of Paul Klee. Her early experiments with algorithmic processes began in 1959 with her machine imaginaire, a conceptual tool — not an actual computer — which she used to predetermine the placement of gridded lines and colors in her art.
Molnár was among the first artists to use computers in her creative process, starting in 1968. She created intricate and mesmerizing visual compositions by writing simple algorithms, a method she described as combining instructions and prohibitions to explore infinite possibilities.
Her notable works include Interruptions (1969), a series generated using the early programming language FORTRAN, and Partition d’une surface de 9 carrés (1995), which played with geometric forms and visual perception. Molnár co-founded the Groupe de Recherche d’Art Visuel (GRAV) in 1961 and continued to push the boundaries of digital art throughout her career, influencing generations of digital artists.
Molnár’s legacy extends beyond her innovative use of technology; she continually emphasized the human element in her work. She viewed the computer as a tool to liberate artists from traditional constraints, allowing them to systematically investigate the infinite field of visual possibilities.
Her recent series, Themes and Variations (2023), created in collaboration with Martin Grasser, showcases her enduring influence and mastery over digital forms. Despite initial resistance from the art world, Molnár’s contributions have been increasingly recognized, culminating in retrospectives and significant exhibitions, including her prominent display at the 2022 Venice Biennale.
Manfred Mohr
Like other generative pioneers, Manfred Mohr’s journey into computer-generated art began in the late 1960s after being profoundly influenced by Max Bense’s Information Aesthetics and the computer music composer Pierre Barbaud. Mohr’s artistic evolution from abstract expressionism to algorithmic geometry marked a significant shift in his career, leading to the creation of his first computer drawings in 1969.
Mohr’s first major solo museum show, “Computer Graphics. Une esthétique programmée” at the Musée d’Art Moderne de la Ville de Paris in 1971, is considered one of the earliest major exhibitions of computer art. This exhibition highlighted Mohr’s innovative approach to art-making, using early computer technology to explore geometric abstraction. His process during this era involved writing code, transferring it to punch cards, and using a pen plotter to execute the drawings, a method that showcased the range of expressions achievable with the limited tools of that time.
Mohr’s work is characterized by its mathematical precision and algorithmic complexity. His early series, such as P-021 (1970–83) and P-190a (1976), feature intricate line drawings that resemble DNA structures or musical scores. This connection to music is no coincidence; before jumping into computer art, Mohr was an action painter and jazz musician. The influence of Barbaud’s computer music and Bense’s theoretical frameworks is evident in Mohr’s art, blending technical rigor with a unique aesthetic vision.
Manolo Gambao Naon
Manolo Gamboa Naon is an Argentine artist known for his innovative approach to generative art, seamlessly blending the influences of twentieth-century art and design with modern digital techniques. His work is characterized by its geometric precision and vibrant use of color, often evoking a sense of both futurism and nostalgia. Naon’s unique ability to merge the past with the present makes his art a compelling bridge into the digital, challenging perceptions that generative art is cold or mechanical.
Naon began creating generative art at a young age, initially experimenting without knowing there was a wider generative community. Over time, he discovered the broader generative art world and honed his skills using tools like Flash and later, Processing.
His works, such as the series bbccclll, demonstrate his mastery of color and composition, drawing clear inspiration from artists like Wassily Kandinsky and Sonia and Robert Delaunay.
Despite working primarily in digital, Naon’s art maintains a tactile, organic quality reminiscent of traditional techniques. His process often involves embracing errors and surprises, allowing these “beautiful errors” to guide and refine his work.
Tyler Hobbs
Tyler Hobbs is one of the most recognized and respected names in the digital art world. Initially a software engineer with a passion for drawing and painting, Hobbs discovered the potential of algorithm-assisted art about a decade ago. He began writing simple programs to create multiple variations on a theme, developing a unique digital aesthetic rooted in non-digital ‘system’ art and Abstract Expressionism.
Hobbs is perhaps best known for his 2021 Fidenza series, a collection of 999 NFTs generated by a single algorithm. This series catapulted him into the spotlight, with one piece selling for $3.3 million. Hobbs has managed to separate his work from the hype, maintaining a reputation for producing art of genuine value. His work has been celebrated for its painterly quality, which blends digital precision with the unpredictable beauty of traditional art.
Hobbs often uses a mechanical plotter armed with a paintbrush, blending hand-crafted elements with machine precision. His collaboration with Dandelion Wist on the QQL allowed users to interact with and tweak the generative algorithm, blurring the lines between artist and audience.
Juan Rodríguez García
With a professional background in architecture, Juan Rodríguez García’s journey into generative art began with 3D modeling using Rhino software and its plug-in, Grasshopper. This initial exposure to creative coding sparked a passion that led him to explore pure programming, eventually discovering Processing as the ideal tool for exploring the abstract design processes that attracted him to architecture in the first place.
Rodríguez García’s work is deeply influenced by his architectural training, as seen in his early sketches that feature abstract shapes reminiscent of architectural forms. His discovery of generative art and the work of Manolo Gamboa Naon profoundly impacted his approach, particularly in the use of color and composition.
Rodríguez García’s work is characterized by a harmonious blend of geometric precision and vibrant color, often paying homage to the chaotic and colorful culture of Mexican cities.
In addition to his artistic practice, Rodríguez García is dedicated to education, teaching creative coding at Universidad Iberoamericana Puebla. He aims to make generative art more accessible and exciting for his students, bridging the gap between traditional art forms and digital innovation.
Eko33
Since 1999, Jean-Jacques Duclaux, known by his artistic moniker Eko33, has been creating generative art, starting with experiments in sound before transitioning to visual forms.
Eko33’s entry into generative art was influenced by the early pioneers of the field, such as Frieder Nake and Vera Molnár. Inspired by their resilience and innovative spirit, Eko33 has embraced new technologies and methods, combining classic generative art with AI in his latest projects. He’s set specific conditions for himself to ensure his work remained authentic, such as training AI models on his own art and ensuring high-resolution outputs suitable for large-scale prints. His dedication to maintaining a connection to the roots of generative art is evident in his use of pen plotters, which symbolize the genesis of contemporary generative art.
Eko33’s process is a blend of control and serendipity, beginning with meditative rituals of collecting mid-century artifacts, sketching, and finally coding. His art is characterized by its complexity and vibrant colors, creating geometric landscapes that evoke deep emotional responses.
Eko33 is an active participant in the NFT space, minting works on various blockchain platforms and participating in significant exhibitions like Le Monde Non Objectif at Unpaired Gallery in Zug, Switzerland. His work continues to push the boundaries of generative art, blending the precision of algorithms with the unpredictable beauty of randomness.
Zach Lieberman
Zach Lieberman is an artist, researcher, and educator known for innovative work that merges art and technology to surprise and engage viewers. He creates performances and installations that transform human gestures into dynamic visual and auditory experiences, such as making drawings come to life, visualizing voices, and converting silhouettes into music. Lieberman’s projects have garnered widespread acclaim, earning him recognition as one of Fast Company‘s Most Creative People and awards such as the Golden Nica from Ars Electronica and Interactive Design of the Year from Design Museum London.
Lieberman’s creative process centers around writing software to produce artwork. He co-created openFrameworks, an open-source C++ toolkit for creative coding that facilitates the development of artistic software. His commitment to education led him to help found the School for Poetic Computation in New York City, where he fosters a community exploring the poetic possibilities of code. Lieberman also co-founded the interaction design company YesYesNo, known for its engaging and magical installations.
As a professor at the MIT Media Lab, Lieberman leads the Future Sketches group, pushing the boundaries of how technology can be used to create new forms of art. His recent work, including his first solo physical exhibition, explores the elegance of simple geometric shapes like circles, drawing inspiration from generative art pioneers such as Vera Molnár. Through his art, Lieberman seeks to humanize technology, making it more accessible and relatable while probing complex questions about the impact of digital tools on culture, creativity, and our understanding of beauty.
Casey Reas
Casey Reas is a trailblazing artist, educator, and programmer whose work has significantly influenced the fields of digital and generative art. Born in 1972 in Troy, Ohio, Reas has built a career that spans the creation of art, the development of groundbreaking tools, and the fostering of communities around digital creativity. He co-created Processing in 2001 with Ben Fry, an open-source programming language and environment that has enabled thousands of artists, designers, and researchers to visualize and share their ideas. Processing has become a cornerstone for digital art, widely recognized for democratizing access to coding in the arts.
Reas’s artistic practice integrates algorithmic thinking with aesthetic exploration, producing works that engage deeply with the history of visual representation and minimalism. His 2021 series CENTURY, for instance, pays homage to 20th-century minimalist art. His work There’s No Distance 2.1 (2021), a looping video using custom code and minimal tools, explores the history of perspective and abstract-geometric painting.
In addition to his artistic endeavors, Reas has made substantial contributions to art education and community building. He founded Feral File in 2021 and has authored influential texts, including Processing: A Programming Handbook for Visual Designers and Artists and Form+Code in Design, Art, and Architecture.
Reas has been a professor at the Department of Design Media Arts at UCLA since 2003, where he continues to inspire and mentor the next generation of digital artists. His work has been exhibited globally, with solo exhibitions at prestigious venues such as the Whitney Museum of American Art and the DAM Gallery in Berlin.
Generative art represents a dynamic intersection of creativity and technology, where the artist’s vision meets the algorithm’s potential. This guide has been a humble foot in the door to an expansive and ever-growing field of artistic inquiry that we encourage readers to explore.
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