Casey Reas on Generative Art: How Code Became Language, and Why Community Matters Most

When Casey Reas first began exploring generative art around 2001, the field was vibrant yet intimate—a small collective of dedicated practitioners scattered across the globe, sharing discoveries online with a handful of peers. Fast forward more than two decades, and the landscape has transformed dramatically. What was once a niche pursuit has become a thriving ecosystem encompassing thousands of active creators, theorists, and enthusiasts. Reas, a pioneering generative artist and co-founder of Processing, has been central to this evolution, witnessing and shaping how code-based art is created, taught, and experienced by audiences worldwide.

From Underground to Mainstream: Casey Reas Charts Generative Art’s Journey

The shift from 2001 to the present represents perhaps the most significant inflection point in digital art history. In those early days, only a handful of people in any given region genuinely engaged with the practice. Today, tens of thousands of energetic creators actively participate in generative art. The watershed moment arrived around 2021, when NFT platforms created unprecedented market mechanisms and exposure for this work. What happened was not merely an influx of capital but a convergence of communities—seasoned practitioners of two decades returned to the field with renewed enthusiasm, while simultaneously, waves of newcomers brought fresh perspectives and possibilities.

Casey Reas observed this collision of old and new with particular insight. The veterans who had quietly developed their craft for years rejoined the conversation at the exact moment when entirely new cohorts were discovering algorithmic thinking for the first time. This created what Reas describes as an unprecedented synthesis: engineers began to recognize art as a valid expression of their technical practice, while artists expanded into programming and computational systems. The result was not merely growth but a genuine cross-pollination of disciplines and ideas.

Processing as Philosophy: Reimagining How Artists Think Through Code

To understand Casey Reas’ influence on contemporary digital art, one must return to Processing—the programming environment he co-developed around 2001. Processing was not simply another coding language; it represented a philosophical statement about artistic practice. The environment was specifically designed to make computational thinking accessible to visual creators, allowing artists to generate images from the moment they first wrote code, rather than treating programming as a prerequisite to art-making.

This approach reversed conventional pedagogy. Rather than learning mathematics and abstract logic first, then eventually applying them to creative work, artists encountered code as an immediate, visual, and generative medium. For those already accustomed to systematic and algorithmic thinking—a way of working that artists have employed for centuries—Processing offered a natural bridge. It legitimized the notion that code itself could be an artistic material, no different from paint, film, or sculpture in its expressive potential.

The significance of Processing lay not in its technical specifications but in its cultural permission. By creating an environment where visual feedback was instantaneous, Reas and his collaborators invited a generation of artists to think procedurally and algorithmically without requiring years of computer science training. This democratization of computational creativity became foundational to the explosion of generative art that followed.

Teaching the Fundamentals: Casey Reas’ Educational Vision

When asked how he remains engaged with emerging technologies despite working in a field defined by rapid innovation, Casey Reas offers a counterintuitive answer: he focuses deliberately on fundamentals. Rather than chasing the latest tools or platforms, his teaching at programs like UCLA’s MFA emphasizes core concepts that have remained stable for decades. The logic underlying these fundamentals enables artists to quickly assimilate new technologies whenever they emerge.

This philosophy extends beyond technical instruction. Reas notes that teaching itself keeps him not at the forefront of technology per se, but rather at the forefront of ideas. His students—graduate students and mentees across various programs—consistently introduce novel perspectives on what code can express and how generative systems can expand the boundaries of artistic practice. Working with emerging creators, Reas witnesses the field continuously redefine itself. Where veterans may rely on established assumptions about what generative art is and can be, newcomers push into unexplored territories, deepen existing practices, and propose entirely new directions.

This intergenerational exchange points to something Reas emphasizes repeatedly: the world requires ideas more urgently than it requires technology. Technological advancement happens regardless; what distinguishes eras is the conceptual imagination that shapes how tools are deployed and for what purposes.

Code as Language: The Emotional Architecture of Algorithms

Perhaps the most provocative argument Casey Reas advances concerns the emotional register of code-based art. Many observers assume that abstract work—particularly work generated by algorithmic systems—occupies an emotional void, a realm of pure logic divorced from human feeling. Reas directly contests this assumption.

Code, he argues, is fundamentally a language. Like written English, which accommodates legal documents, poetry, and novels, code can express radically different emotional and conceptual territories. The medium itself is neutral; its expressive capacity depends entirely on the creator’s intention and vision. A programmer might write code that feels cold, mechanical, and detached. Another might harness the same language to create work of profound tenderness. The difference lies not in the medium but in the artist’s consciousness and the ideas they choose to communicate.

Reas references Mark Rothko as an instructive example. Rothko’s paintings are abstract, entirely non-representational, yet viewers who sit with his work experience intense emotional resonance. This happens not because the paintings depict recognizable subjects, but because viewers approach the work with openness, allowing its visual intensity to permeate their consciousness and body. Code-based art functions identically. The medium—whether abstract painting or algorithmic system—does not determine emotional response; rather, the viewer’s willingness to engage deeply, combined with the artist’s intentional communication through form and structure, generates affective experience.

This insight reframes the entire question of art and technology. If code is language, then generative art is not a technological novelty but a continuation of artistic expression—one that simply employs different formal constraints and mechanisms to explore composition, color, movement, and meaning.

Community as Infrastructure: Casey Reas and the Feral File Model

Beyond his individual practice and teaching, Casey Reas has become instrumental in imagining how generative art communities function and evolve. His collaboration with Feral File exemplifies a particular curatorial philosophy: rather than programming exhibitions from above, Feral File invites respected curators to conceptualize shows and select artists. When the curatorial vision is clear and compelling, these curators become connective figures who link artists to one another, fostering genuine community around shared exhibitions.

This model produces what Reas describes as a distinct form of generative art collaboration—one with profound impacts on how participating artists develop their work. The exhibition becomes more than a display; it becomes a node in a network where artists find collaborators, peers, influences, and sometimes their most important audiences. Community, in this formulation, is not incidental to art-making; it is infrastructure that shapes creative possibility.

Waves and Persistence: The Sustainable Future of Digital Art

In reflecting on the trajectory of generative and digital art, Casey Reas employs a wave metaphor. The 1960s witnessed an extraordinary surge of interest in cybernetic art and art-technology fusion. That wave receded. The late 1990s and early 2000s, marked by the emergence of the World Wide Web, generated another wave. Again, enthusiasm waxed and waned. Currently, he suggests, the field is experiencing another wave—one propelled by NFT platforms and broader cultural interest in digital creativity.

Waves are inevitable, Reas observes, and they inevitably transform everything. From an artist’s perspective, however, waves matter less than one’s commitment to the work itself. Whether or not the market flourishes, whether or not institutions devote resources and attention, artists who genuinely care about their practice persist. They create not for external validation but because creation is inseparable from their identity and passion. As the current wave undoubtedly crest and recede, he suggests, the artistic community will be better positioned than ever to sustain and develop the field independently.

The Significance of Marfa: Casey Reas Reflects on Community and Time

When reflecting on the meaning of attending Art Blocks’ Marfa gathering, Casey Reas emphasizes not the artworks or market developments, but the palpable presence of collaborative energy. For decades he created in a quiet, engaged manner. The events of 2021 transformed the lives of countless artists—it was an era of explosive growth, yes, but more significantly, an era of unprecedented interpersonal connection and community formation. Marfa, in this sense, symbolizes the cohesion and infectious energy that collective creation generates.

The special significance of this moment lies not merely in its novelty but in its demonstration that digital art can sustain thriving communities rooted in genuine shared purpose rather than speculation alone. As Casey Reas’ career and philosophy reveal, the future of generative art depends less on technology’s next innovation and more on whether communities continue to find value in algorithmic thinking, code as language, and the enduring human capacity for creative collaboration.