Ira Greenberg, one of the pioneers in generative art, has spent nearly three decades at the intersection of art, science, and technology. He leads the Center of Creative Computation at SMU, championing a philosophy that merges the algorithmic with the artistic.

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—Could you walk us through your creative process, from initial inspiration to the final execution of a piece?

At this point in my practice everything I do is based on a generative process with emergent outcomes. It doesn't matter if I’m using charcoal, paint, code, AI, a piano, words, I enter an ‘empty’ space with (as much as possible) no a priori anything. I do hope to eventually find something worth preserving, so I guess there is one goal. A piece can take 5 minutes or years, I never know. I have drawings on my studio wall that have been there for multiple years, and I have no idea when they’ll be completed (or if they’ll be completed.) 

This lack of conscious agency used to cause me a lot of stress when I was much younger; now I just accept it as the normal rhythm of my practice. A piece is complete when new marks/alterations makes it less engaging to me.

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—As you create with AI and generative systems, do you perceive your relationship with computation as a collaboration? How do you negotiate control and surprise in this partnership?

Computation is a medium for me. Randomization in the system, approximating the chaos of physical materials, enables the medium to suggest possibilities; in that sense, it is a collaborator, as is paint when it drips or smears. The navigation of control vs surprise (chaos) is essentially the creative process, independent of medium for me.

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—In what ways has the iterative process of coding enriched your understanding of creativity and artistic expression?

Iteration of code (with layers of randomization) simply offered a mapping to the physical creative process for me. Standard, more deterministic software, with undo/redo capabilities, does not map as well for me. I do use these tools of course, but in a much less generative way. The recent addition of generative AI into Adobe Photoshop makes it a much more interesting medium for me.

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—How has your visual language evolved as you've transitioned from more traditional forms of art to incorporating advanced programming and generative techniques?

I’m a much broader and more open artist than I was when I was younger. Right out of school I felt there was more of a formula to make successful art. Many of my mentors were strong, charismatic characters, often brilliant, but also dogmatic. It took me years after school and doing my own teaching to learn to deprogram some of this. 

Of course, much of this was also a by-product of how I was raised and the surrounding culture. An area I learned about primarily after school was design. Much of this was motivated by the need to pay the bills, but there were aspects to it that really captivated me, as did more applied design disciplines such as architecture. 

Now, I make work that emerges in my process; sometimes it refers to design, data visualization, painting, or really whatever is suggested. I don’t worry about a specific voice or consistent motif. I just create in the void and pursue what fascinates me. I do think my years of coding and letting go of painting (my old religion) for a while really expanded my sense of what art can be, and with it, a sense of generative freedom. 

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—How do you stay authentic in an era where digital art can be easily replicated or modified?

People have had the capacity to photograph and copy one another’s work for nearly 200 years. Art forgery is an old practice. The fact that AI can approximate styles has no bearing for me on the question of authenticity. 

Yes, there will be bad actors who will try to exploit AI in the marketplace, but time generally fixes all that. Authenticity for me comes from a lifetime of creative practice and a very deep personal impulse to express myself. If you just give me a rock or the world’s greatest supercomputer, I’ll make art based on the inherent limitations and capabilities of the medium. The supercomputer (computation) has become perhaps the most exciting medium of our time, with AI as its latest manifestation.

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—Some of your work is monochromatic, and other series feature randomly assigned colors. How would you describe your relationship to color?

Black, white, gray are colors, just less complex ones perhaps. In painting, I do see color as a different kind of commitment than I do working with color digitally. I’ve been drawing using charcoal a lot the last few years, with an ever growing strong desire to paint, but my circumstances still feel a bit transient, traveling regularly back and forth between Texas and New Mexico, so it’s been easier for me to stick with drawing for the time being. 

Digitally, I don't feel these limitations as much, so it's been great being able to express myself with color this way. In painting, I always felt a strong connection to color, in that I felt I could see and mix it well, and have a pretty strong emotional response to color in my practice.

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—How has embracing failure and uncertainty shaped your creative philosophy?

Making art is really about completely letting go while also simultaneously trying your very hardest. It’s really a ridiculous thing to do, but perhaps the absurdity maps well to our general human condition. I know that every mark, line of code, AI prompt, etc is an approximation of an impulse, or a near miss. However, an accumulation of enough near misses adds up to something perhaps of value, something that reflects interestingly on our human potential. 

People with concerns about AI removing our humanness I think fail to grasp that it is fundamentally our puny existential condition and limitations that are the source of our greatness. Technology in general is about reducing human limitations, so in that sense it’s difficult for me to see us engineering humanness out of our condition.

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—You are the director of the Center of Creative Computation at SMU. In your teaching philosophy, how do you bridge the gap between technical skill acquisition and fostering an artistic voice among your students in the realm of creative computation?

Learning to make art is a lifetime practice; it takes a really long time to know yourself, your tendencies, limitations, gifts, plus integrating all these with the history of the practice, current times you live, and so on. It’s a lot! There are certainly ways to cut corners and limit aspects of the practice to move more quickly, but I’ve never been wired that way. 

I try to find a balance with my students, without putting too much pressure on them (this has changed a lot since I was a young teacher). I really want them to figure out why they’re making art. If they can gain some clarity about this, most of the rest is simply working. We also learn different things at different times and speeds. I want to create a space for these different approaches to flourish and feel comfortable, and hopefully I’m a decent role-model of someone trying to make a life doing this. 

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—Based on your journey, what advice would you give to young creatives interested in exploring the boundaries between art, science, and technology?

Embrace your intellectual fears and challenges, especially if you find them fascinating. Too many artists run from math and quantitative subjects, and the opposite is true as well for more quantitative types. Integration of mind is really what will bring most people a sense of greater purpose and happiness, but it takes hard work and tolerance of a fair amount of discomfort to get there. 

Our current western culture creates so many incentives for early specialization, creating obstacles to integration. Hopefully, advances in AI and blockchain will enable more people to actualize their full human potential. I’m certain society as a whole will benefit from this.