John Maeda shares takeaways from his Design in Tech Report, thoughts on designing with artificial intelligence, and why we should embrace uphill thinking in a world optimized for shortcuts.
Portrait illustration by Lorenzo Gritti.
We find ourselves in an era of paradox. On one hand, AI promises unparalleled efficiency and limitless potential for creatives. On the other, it threatens to spawn a masterful new generation of cookie-cutter designs that could spell the end of many creative careers. So which is true? And how do we reconcile these two contradictory perspectives?
2. How To Speak Machine: Computational Thinking for the Rest of Us (2019) by John Maeda. The accompanying site offers a gentle introduction to AI and ML.
I’ve been talking about AI for a while. In my 2018 and 2019 Design in Tech Reports,¹ I talked about its growing design applications. The response—if any—was minor. Perhaps this was because AI and its capabilities were still fairly nascent, and the technology had a long way to go before it could truly replace design jobs. Fast forward four years, and the topic is unavoidable. The ChatGPT revolution is upon us. And with that, designers worldwide are taking strides to “speak machine.”² They’re learning how to collaborate with AI, training long language models with datasets and fine-tuning their outputs to better align with the designer’s visions—effectively bridging the gap between human creativity and the computational capabilities of AI. Designers do so fully knowing that any magic that they create with this technology may then be easily repeated, with or without them.
But, will I wake up one morning to discover that there’s an AI system named “J0hn M43d4” on Fiverr repping my work for pennies, Black Mirror-style? I’m not worried about it, because I know that’s long been happening of my own accord: In the '90s, I had a certain way of creating images algorithmically that was special at the time. I open-sourced the approach at MIT as a way to get more people to turn what few secrets I had gathered into their own magic.³
But not every magician wants to reveal their secrets—they have livelihoods to protect. So what should a designer in the era of AI’s rapid ascent do? I have good news: There are plenty of things that computers are not good at. And most are things designers really don’t get all that much joy from doing in the first place—mundane tasks like creating endless variations of slides, mockups, and retouches. If the computer could take on some of that work, might it give designers more time to do something else? My dear artist friend Jessie Shefrin once said to me, “By the time you come to the perfect solution, the problem has already changed.” By that thinking, what present-day problems could computers tackle today, so we can focus on tomorrow’s?
To begin, it’s crucial to underline a key difference between ourselves and our robot counterparts: AI, in all its glory, is designed to seek the shortest, most efficient routes. This is its strength. It can evaluate thousands, even millions, of potential paths in the blink of an eye and choose the most “efficient” one. Yet, as we all know, the most efficient solution is not always the most creative one. In fact, I’d argue that the route of greatest efficiency is rarely the most impactful. It might prevent us from reaching a more creatively meaningful destination.
4. “It's time to burn our ships” is a phrase that means the company must cut off all avenues to the old ways of doing things. As leaders taking our people into unknown and potentially hazardous new territories like Cortés did, we need to ensure those we lead understand there is no turning back.
Part of being efficiency-oriented means that AI is constantly seeking out the most common, expected path. By repeating tried and tested solutions, AI is inherently more risk-averse. Particularly when paired with strict guardrails and considerations of AI safety, it will almost always opt for the lowest risk. In many cases in life, that’s a really good thing. However, in the realm of creativity, higher risk may lead to an unexpected higher reward. When people take risks and go out on a limb, they’re forced to think strategically under pressure, yielding unexpected results. What’s that old saying? “Burn the ships!”⁴ When there’s no turning back with a high-risk decision, things get really interesting quickly.
Humans are innately driven to take the adventurous, longer route. Our distinct traits of creativity, innovation, and uphill thinking compel us to explore the unseen, unheard, and untouched, even when it's seen as rationally “wrong” by conventional standards. This shared spirit, found in entrepreneurs, athletes, and artists alike, is demonstrated in our history of remarkable art, groundbreaking discoveries, and revolutionary innovations. This willingness to embrace challenges, endure setbacks, and choose “longcuts” over shortcuts underscores our unique capacity for uphill thinking. Even as AI excels at efficiently executing repetitive tasks, it remains rightfully constrained by our design for safety and lower risks, making it less suited for the daringly imaginative and transformative tasks that creatives undertake. This courage to venture in unconventional directions, to bet the farm on an irrational path, is what differentiates us from today’s AI. The uphill thinking that may seem suboptimal in an AI-centric view is, in essence, the core of human creativity.
Or saying it in Star Trek parlance, to quote my favorite line between Captain Kirk and Captain Picard:
Kirk: I take it the odds are against us and the situation is grim.
Picard: You could say that.
Kirk: You know, if Spock were here, he’d say that I was an irrational, illogical human being by taking on a mission like that. Sounds like fun!
One may ask, can an AI truly understand the sub-optimal, winding, long, hard, high-risk, and effortful journey that humans take to yield great output? To an extent. It’s important to remember that AI is not a sentient being. Currently, there is no direct 1:1 notion of “understanding” in an AI the same way that we humans understand a concept. Instead, AI can be instructed to do things with specificity. Do this thing, don’t do that thing. In that way, it’s no different than computer programming of the past.
What *is* different is that this kind of programming feels a bit like being powered by Vibranium.⁵ It’s a momentous shift, one that has supercharged our technology to a point nearly beyond comprehension. We’ve had similar shifts in the past: There was a time when electricity was the day’s Vibranium. In a world powered by steam engines, the introduction of technology that was completely invisible caused immense excitement and fear. Steam power posed a frightening disruption for the textile industry, as new mills could easily fabricate textiles that would have taken humans months and years to create.
6. The Arts and Crafts movement was an international trend in the decorative and fine arts that developed earliest and most fully in the British Isles during the 1860s and ‘70s and subsequently spread across the British Empire and to the rest of Europe and America.
7. The Luddites were members of a 19th-century movement of English textile workers which opposed the use of certain types of cost-saving machinery, often by destroying the machines in clandestine raids. They protested against manufacturers who used machines in “a fraudulent and deceitful manner” to replace the skilled labor of workers and drive down wages by producing inferior goods.
In response to this industrial revolution, artisans and leaders founded a revolution of their own in the form of the Arts & Crafts movement,⁶ which advocated for “products that not only had more integrity but which were also made in a less dehumanizing way.” Some of their fiercest supporters, self-proclaimed Luddites,⁷ would engage in engage in “frame breaking” (i.e. destroying an automated weaving machine), often getting jailed and fined as a result. But what’s important about the Arts & Crafts movement is how it led to an enlightenment of objects that could only be created by human beings: textiles, furniture, and other items that were so intricately created that no machine could possibly manufacture them.
This image shows the artist's interpretation of the Luddites breaking a loom. The famous poet Lord Byron opposed the Frame Breaking Act of 1812 that would make machine breaking a capital crime, going so far as to defend the frame-breakers with a Taylor Swiftian song. (Wikimedia)
This reverence for human creativity was also reflected in the educational institutions founded during this time, such as the Rhode Island School of Design (RISD).⁸ They pioneered the use of the first wave of “generative art software” in the form of punch cards⁹ for Jacquard looms—the GPUs of the day—and designed distinctive textile patterns that married artistry with new technology.
8. The Rhode Island School of Design (RISD) was founded to support the state’s thriving textiles and jewelry industries in particular, with the first courses of study offered addressing two main areas: Freehand Drawing and Painting and Mechanical Drawing and Design.
9. Each row of punched holes in these cards corresponds to a row of the textile being woven. (National Museums Scotland)
Fast-forward to today, and RISD continues to champion the ethos of the Arts & Crafts movement, serving as a bastion of uphill thinking in our modern digital age. At RISD, students are taught to embrace the complexity of the design process, to not shy away from the long, winding road of creative discovery. This attitude prepares them to venture beyond the efficiency-driven solutions offered by AI and to craft designs with a level of nuance and authenticity that only human touch can achieve. The spirit of RISD is a testament to the enduring value of human creativity, reminding us that while AI has its strengths, there will always be a space carved out for uniquely human endeavors.
So where does AI fit into all this? In the same spaces where efficiency and precision thrive. AI’s proficiency in automation, data analysis, and pattern recognition can streamline mundane tasks, freeing up more time for us to focus on the aspects that demand human ingenuity. We’ve entered the same age as Ruskin and Morris, when we need to create things, software, experiences that only we humans can guide in their evolution. By leveraging AI, we can not only retire our drudgery, but we also amplify our uphill thinking, taking on greater challenges and achieving unprecedented heights.
Noah Levin echoes this ethos in his recent post, and hypothesizes about AI’s potential to open up design to an even greater contribution: “AI will lift this ceiling, leading to more creative outputs made possible by more powerful tools; it will also lower the floor, making it easier for anyone to design and visually collaborate.” The problems we solve today in design have already changed by the time they’ve been addressed. Thus we need to be investing more time and energy into the ever-changing task of seeking and identifying new problems to solve, ones that lead to better outcomes for people. Part of that is continuing to find better ways to work well together, until we’re all working as teams of eminently capable professionals who can finish each others’ sentences.
The more we pedal uphill—navigating the journey, embracing the struggle, and rejoicing in the climb—with AI empowering us to spend more time on that journey, it’s more of a win-win relationship we will build with AI in the creative fields. It gives us more time to take in the scenery and identify opportunities for exploration that may lie just off the beaten path. It frees us to focus on the things that only humans can do: spend a little bit more time than is strictly necessary, in order to end up somewhere unexpected.
American technologist. Product experience leader across consumer and enterprise. Early catalyst for generative art and computational design for commercial applications across Web2 and Web3. First recipient of White House’s National Design Award for algorithmically-generated visualizations informed by data + AI. Noted book author, online influencer, and investor in diverse startups.
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