Here we go, again
Artificial intelligence can handle the processing of the data intrinsic to every customer. It can also help generate touchpoints spontaneously at a massive scale. We now have the means to make brand relationships contextual at the individual level.
Imagine what that can mean for design: the picture that forms is super intriguing and alluring, at least to me. But to realize this promise one has to shift the focus and practice of design, again.
The picture in my head
Kira is a designer in the not-too-distant future. She's frustrated by how inevitably disconnected her work is from real life. ‘If people could be part of the design process’, she thinks. But there’s a limit to how many projects she is able to work on at once. So she creates an AI version of herself who is just as clever, fast and intuitive.
She names him AI Algo.
At first, Kira asks Algo for suggestions, and notices that his design improvements always work out, and that her products are better because of them. The more they collaborate, the more Algo learns. Kira and Algo’s work speed up, and so do their iterations. They are able to explore more directions. They break new ground.
Eventually, Algo stops needing Kira’s input to generate work. His decisions are almost indistinguishable from her own. Almost. Somehow Algo misses the goal, everytime. He just keeps ending up else.
Kira first thinks Algo might be more than just a tool. For a brief moment she wonders if he's actually alive. Maybe his decisions are conscious, his own. But then, she realizes that Algo’s just wandering without a purpose. What they need is a logic they can share, a way to agree. A language, like math.
She translates her concept into an algorithm, and gives Algo a set of visual elements and some data to process. Algo starts gushing solutions she can approve. One after another, after another.
So he’s not alive. He's smart, but he's not conscious. ‘AIs are intelligent beings that aren't human’, Kira thinks to herself. ‘I can see what he cannot—a future we can create together.’
She takes a sip of coffee and they get to work.
What changes
In the story, Kira realizes that what she and Algo needed was a common logic. Designers live in an analogous world, but machines speak math. Kira can’t inspire Algo to appreciate a butterfly’s beauty, but (with the help of a math formula) she can explain how to generate the pattern in the butterfly’s wings and make it flutter through the air. Sure, Algo can learn we find butterflies beautiful—just not why. Inspiration is still our domain. Whatever the output, relevance still depends on us designers.
What’s new is that, by basing design on algorithmic logic, we can incorporate data to contextualize our work. Everyone’s interests, needs, preferences, and history are captured in data. That information can be the gateway to relationships at the 1:1 scale. Kira can now conceive products that (with Algo’s help) can be individualized to each user or customer, even at a massive scale.
What is also different is how the designer can address scale. Since Bauhaus, our focus has been on how we build. Design systems are borne out of that drive to harmonize design and production. Repeatability in design still prevails, even as we experimented with customization. Algorithmic logic opens the door to using data in the creative process. Kira conceives design systems that Algo can use to merge concept and data to generate independent solutions at scale.
Ultimately, what changes most is that design can be contextual on the individual scale. Through data, we can conceive and generate designs spontaneously, in any environment, and at any moment. Kira and Algo’s system is ready to generate a product, story, or gesture just for me, depending on where I am and what I’m doing.