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John Maeda on Computational Evolution

John Maeda discusses his multifaceted identity as a technologist, artist and designer with Peter Bauman (Monk Antony). Maeda emphasizes the importance of a multidisciplinary approach to innovation and creativity, while reflecting on the transforming needs of artists in the age of AI.

Peter Bauman: Which are you first—a technologist, artist or designer? How do these roles inform the others?

John Maeda: I don't see myself as belonging to just one category. My journey as a technologist, artist, and designer weaves together, each thread informing the other. Technology shapes my art and design, while creativity and aesthetics influence my approach to technology. This blend of disciplines gives me a unique perspective in my projects and leadership.
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Embracing a multidisciplinary approach, drawing from various fields, is essential to fostering true innovation and creativity.

‍Peter Bauman: That same multidisciplinarity perhaps showed you how code can be used to create new, unseen forms. In the mid-90s, you presciently recognized that artists needed better tools, creating Design By Numbers at MIT. What do they need today?

John Maeda: I believe that artists need tools that go beyond conventional design solutions. These tools should help artists overcome the fear of failure, embrace technical challenges, appreciate historical context, and question assumptions. This is especially the case in this new age of AI-enabled creativity—what do computational art skills mean when everyone can code without learning how to program? I think the answer lies in more designers mastering the science of AI itself.

Peter Bauman: This “new age of AI-enabled creativity” you mentioned appears to engender more skepticism and fear than previous tech breakthroughs. As a witness to the rise of the early Web and now AI, how would you compare public sentiment to their respective beginnings? Are you more excited or concerned about the rise of AI?

John Maeda: I am genuinely excited about the rise of AI, much like I was during the early days of the World Wide Web. It's essential for individuals and organizations to understand and adapt to this new technology, embracing change and learning from what this new kind of AI can offer. It’s especially important to understand what it cannot do. One can only understand that by writing software that leverages LLMs [large language models] and other kinds of AI models.
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I’m reminded of my favorite saying by General [Eric] Shinseki: “If you don’t like change, you’re going to like irrelevance even less.”

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Peter Bauman: You study leaders you admire, like Shinseki, to learn from their styles. What were the keys to directing and recruiting the legendary Aesthetics + Computation Group at MIT, where you created Design By Numbers and oversaw the team that made Processing?

John Maeda: I believe the secret to my success was having the good fortune of recruiting the right people onto the team. In the Silicon Valley startup universe, it's often said that the first few hires determine whether or not you'll make it to your series A round. My luck came from bringing aboard people who had the rare courage to listen to themselves and who believed more in themselves than in me. Over time, I realized how important this approach was. To this day, I always tell my direct reports—after sharing my thoughts on what they should do—to always remember, "Don't listen to me!"

Peter Bauman: You were asked recently about your inspirations and your answer included the following: “I'm a big fan of the Processing team leaders and where they've taken the idea of computational design and art into this century: Casey Reas, Ben Fry, Dan Shiffman, Lauren McCarthy.” What’s next for computational art in the subsequent quarter of this century?

John Maeda: My guess is that everything we thought would be computational design and art is going to change for the better. One limitation of the computational creativity movement’s broader adoption was computer programming and being able to understand mathematics in practice.
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The good programmers will only get better and the novice programmers will have a chance at creating computational works that would have been previously impossible for them to achieve in their lifetime.

These days, I find myself building new p5.js applets using GPT-4o and wishing I had the magic crayon of LLMs much sooner in my career.
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Peter Bauman: You mention how needing to program limited computational creativity's adoption. But how will latent diffusion models and the hyperproliferation of images affect digital aesthetics?

John Maeda: Before the Internet, if you wanted a beautiful handmade oil painting, it was no easy task. You had to hope there was an artist in your vicinity who had the right piece in their inventory or was willing to take a commission. Good art that made you happy was scarce. And then suddenly, you could access any artist in the entire world. Suddenly, every average artist in your vicinity who was charging a little more than you had hoped was out of business. Why? Because you had other choices available to you. And now, with latent diffusion models, any style of any object you want is now available to you for just a few pennies and within increasingly slimming seconds.
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To compete with these models, I believe that artists will need to get very, very fast at whatever challenging aesthetic they may wield in an age when expectations for speed of execution turn upside down.

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Peter Bauman: How would you advise artists to go about that? Many of your ideas are anchored in simplification. Which of your ten laws of simplicity is most important for artists and writers as they negotiate a world of AI-created instant images and text?

John Maeda: The third law of simplicity: “Savings in time feel like simplicity.” Visual artists and writers will need to get much faster at delivering their craft in this new age of computational creativity. We’ll all have to learn to use our seconds as carefully as we manage our days and weeks.

‍Peter Bauman: How has AI impacted computation and the major themes of How to Speak Machine in only roughly five years?

John Maeda: As I look back at How To Speak Machine, I realize that it’s a time capsule of the moment right before LLMs landed on earth. All the themes I wrote about in HTSM remain the same in this new era of AI. However, the advent of AI, particularly large language models, has accelerated the pace of computational evolution and magnified the significance of these themes. Concepts like algorithmic thinking, the fusion of human and machine creativity and the importance of understanding machine logic have become even more crucial. AI has not only enhanced computational capabilities but also encouraged us to rethink our interactions with technology, making the insights from HTSM still relevant today.
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‍Peter Bauman: In what ways do you consider your work generative? How do you balance the tension between control and surprise in your practice?

John Maeda: In the 90s, I referred to my work as “reactive” rather than “interactive” in response to the art technology world at the time. My point was that the pieces I made were like living graphical systems that would always respond in real-time and “react” to the user. This reactivity manifested through generative changes in elements' color, shape, direction, or even the overall composition of the artwork. Back then, graphics were often slow, fed off CD-ROMs, so my algorithmically generative pieces stood out. Like all artists, most of the work that made it to the final presentation was the result of experimentation, with many failures and accidents often turning out better than my original idea.

Peter Bauman: It’s comforting to know that someone with your eye is now leading design and AI at Microsoft. How are you shaping the aesthetics of AI in your role?

John Maeda: I am more of a computer programmer than a designer these days. My interest is in developer tools and the unique aesthetics of CLI [command line interface] experiences. It’s a very nerdy notion of beauty, but it’s where I’m feeling the most comfort in my day-to-day work.

‍Peter Bauman: How do you use AI yourself in your workflow? How do you recommend readers adopt AI into their daily lives?

John Maeda: These days, I believe that computational design can achieve two things: 1) eliminating designer toil and 2) ushering in the new era of so-called “zero UI.” On the former front, I’m passionate about automating anything a human designer can do so that they can just give their product management partner an AI microservice and leave the designer alone.

On the latter front, I’ve grown tired of the many information “cockpits” we’ve created that are increasingly difficult to use and so I’m excited to see them all go away or “zero UI” as the approach. Designers and artists can easily participate in #1. A small group of them will be tackling #2.
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‍Peter Bauman: For decades, your career has placed you at the center of art, design and technology. You know the needs of artists and collectors in this space, like digital ownership and royalties. You’ve also often anticipated major tech trends. What is your honest assessment of NFTs?

John Maeda: In the early 2000s, my team at MIT created an early experiment in collaborative digital art-making, which gave me insight into the potential of digital ownership. Openstudio allowed artists to create, share, and remix work while keeping provenance intact and even included a digital currency system for collecting art. Looking back, Openstudio might have been an early precursor to the NFT world. 
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As for what I think of NFTs, I guess I felt they were inevitable.

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Peter Bauman: Your practice has sought to "bridge the gap between computational and non-computational expression." So where does the art mostly lie in your work? The visual aesthetics? Or is it in the system, like many computational artists claim, including your former student Casey Reas?

John Maeda: My art lies in my being a human being. I made the work with my own hands as a creative expression that I felt inside me and wanted to see it outside of my own head and heart. It is in the fact that I made it. How I made it doesn’t matter, besides the fact that it happened. I was here.

‍Peter Bauman: Both times—as a student and then professionally—after leaving MIT, you went to an art school. Do you think that’s a coincidence?

John Maeda: I don’t know if you’d call seeking balance a coincidence. When I get too far along in one space, I tend to need to retreat from it and go into another space. My relationship between design and art versus engineering and science has always been on a continuum. When I venture too far in one direction, I feel the need to go back in the other direction. For that reason, I find it important to note that I recently changed roles at Microsoft and am now a VP of Engineering instead of a VP of Design. Life is funny that way. At least for me.



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John Maeda is an artist, designer, technologist and product experience leader. He was a prominent catalyst for generative art and computational design for cultural and commercial applications across Web2 and Web3. He has authored several books including How to Speak Machine and The Laws of Simplicity. His work is in permanent collections such as Museum of Modern Art, New York. Currently, he is VP of AI & Design at Microsoft.

Peter Bauman (Monk Antony) is Le Random's Editor-in-Chief.