During my days at the MIT Media Lab and later as a partner at Silicon Valley venture capital firm Kleiner Perkins, I found that when working with startups and C-level folks at larger companies, the word “design” meant too many things. The first Design in Tech Report emerged from my desire to try to explain design’s impact on industry at all scales—but the question kept coming up about what “design” really meant.
So in the second Design in Tech Report, I defined three kinds of design as a working model to build upon:
- classical design, which pertains to the design of objects we use in the physical world,
- design thinking, which pertains to how organizations learn how to collaborate and innovate using ideation methods, and
- computational design, which pertains to any kind of creative activity that involves processors, memory, sensors, actuators, and the network.
By this measure, there are generally three kinds of designers out there today: classical designers, design thinkers, and computational designers. This framework has proven durable over time, although not lacking an appropriate level of controversy for attempting to simplify a complex and broad professional discipline. That said, it’s allowed me to spend more time putting a spotlight on the most important kind of design out there today: computational design.
But before we dive into that, let’s explore how we got there.
Classical designers are the most common—they are the designers of chairs, posters, fashion, and generally the IRL experiences that we fall in love with. Their intellectual origins are spread over the last few centuries, with the key moment being the Industrial Revolution of the late 1800s.
Mechanized processes and new kinds of fabrication machines powered by steam power, humans, and, later, electricity brought an unprecedented level of scale. But they didn’t create well-designed products—just the quick and easy proliferation of badly designed ones. In the early 1900s, it wasn’t uncommon for a factory to produce large quantities of a hot-water pot that burned your hand when you held it a certain way. Products looked like they came out of a cookie cutter (and they often literally did) and rarely aesthetically fitted with your home decor.
Luckily the Bauhaus school—founded exactly 100 years ago in Germany—provided the foundations of an educational process to serve the Industrial Revolution opportunistically with a set of foundations for how to make better products. It’s how the first “product designers” were born. (And I’m particularly familiar with this history because it was the main subject area of my 1996 doctoral dissertation in the area of industrial design.)
Design thinkers are professional catalysts for collaboration, criticism, and consensus-building. They enable companies to put the customer at the center of their work through putting themselves in the consumer’s shoes and thinking about how to serve their needs.
One would think it somewhat odd that any business might lose sight of its customers—but it’s a quite commonplace occurrence. Why? Because aspiring to understand customers requires an investment in the necessary ethnographic work required to learn about one’s customers as human beings instead of aggregate statistics. Compound that challenge with the need to then bring those complex insights into one’s company amidst each individual’s already busy schedules and priorities, and you are faced with the impossible task of trying to align many human beings’ wants and needs.
Then there’s that now-popular term: “design thinking.” In a sense, “design thinking” originated in paper-based “design methods” for ideation used by the automotive industry in the ‘60s and ‘70s by in-house product-design organizations. These methods were later popularized and refined by design firms like IDEO and frog using sticky notes and markers, and today “design thinking” is now taught at all the major business schools.
Computational designers are creative people who wield their mastery of knowing how software, hardware, and the network all interact. They are the product of the second Industrial Revolution—computing—with the ‘60s having been a turning point for a technology that was originally designed for the military and to support warfare to become invaded by artists.
Just search for “Bell Labs” and “computer art” and you’ll be surprised by what you find there—everything ranging from early computer-graphics experiments to rudimentary virtual reality to pseudo-“AI” for making images. But there were two factors that prevented it all from leaving the labs:
- nobody had computers, and
- computers couldn’t really do a lot.
Fifty years later, we don’t have that problem at all. The supercomputers we now carry in our pockets and purses are connected to even more powerful cloud-based infrastructures of Amazon, Google, Alibaba, and the likes.
But to date there has been no Bauhaus-like moment for computational designers. Places like the MIT Media Lab, Carnegie Mellon’s Entertainment Technology Center (ETC), Stanford’s Center for Computer Research in Music and Acoustics (CCRMA, aka “KARMA”), and NYU’s Interactive Telecommunications Program (ITP) all tried—but it proved to be impossible. Why? Because computation kept evolving at the speed of Moore’s Law. And classical design dogma kept competing with what computational design needed to become.
The future of design
When people wonder why I left MIT, I tell them it was because I wanted to understand design better. I went on to run an institution with the actual word in it (look up what the “D” in “RISD” stands for) to get to the heart of it all. It was also because I was at an institution where the “T” stood for something that I believed was starting to make our world unnecessarily complex: technology.
After I went sufficiently deep in the classical design universe, I headed to Silicon Valley to work with both startups and large tech companies and become immersed in the practice of it all. It’s helped me see what a lot of folks had been telling me for a while: that in this new era of computational design, traditional design education has become irrelevant—which I started to highlight in the first few Design in Tech Reports.
So we shouldn’t expect that the Bauhaus will be re-created for this newer Industrial Revolution the same way it happened before. The nature of the experiences we craft with computation keep changing on a minute-by-minute basis. And even if there were an old-fashioned educational institution out there that could cover 80% of what’s needed today, then by the time it opened its doors, it would only cover 10% of what is needed right now. The field is changing too quickly for traditional institutions to keep up. How will we then ever have a Bauhaus moment for computational design?
The new Bauhaus for the computational era will be driven by open source. I learned this in the late ‘90s when I created a closed system to teach designers how to program called “Design By Numbers.” My then two research team members Ben Fry and Casey Reas thought that the concept could be significantly improved upon and made the popular open-source system Processing. It’s in use everywhere with UCLA and NYU as the hubs of this work.
The new Design in Tech Report puts a spotlight on the Material Design system because it integrates the three kinds of design in an elegant, deep, and open-sourced knowledge base with a complementary set of free tools. More of these kinds of resources need to emerge, and I believe that tech companies have a responsibility today to do so. I am hopeful that more volunteer organizations like WordPress and major companies like Google will continue to, or start on their own to, open source as many of their design efforts as possible to make a Bauhaus moment happen.
What will be the result? We’ll more quickly realize a world with good design for all, and track closer to the speed of Moore’s Law. Why do I believe that possible? A popular interpretation of one of the most popular computer languages in the world, PHP, is “People Helping People”—which carries the ethos of sharing that we need to embody
today more than ever.