The most broadly impactful technologies tend to be the ones that become mundane—cheap, expected, part of the fabric of everyday life. We absorb them into our lives, their presence assumed, their costs negligible. Electricity, phones, televisions, internet, refrigeration, remote controls, power windows—once-remarkable technologies that now quietly improve our lives.
That’s why the aspects of machine learning that excite me most right now are the small and mundane interventions that designers and developers can deploy today in everyday projects. As I wrote in Design in the Era of the Algorithm, there are so many excellent (and free!) machine-learning APIs just waiting to be integrated into our digital products. Machine learning is the new design material, and it’s ready today, even for the most modest product features.
All of this reminds me of an essay my friend Evan Prodromou wrote last year about making software with casual intelligence. It’s a wonderful call to action for designers and developers to start integrating machine learning into everyday design projects.
Programmers in the next decade are going to make huge strides in applying artificial intelligence techniques to software development. But those advances aren’t all going to be in moonshot projects like self-driving cars and voice-operated services. They’re going to be billions of incremental intelligent updates to our interfaces and back-end systems.
I call this _casual intelligence_ — making everything we do a little smarter, and making all of our software that much easier and more useful. It’s casual because it makes the user’s experience less stressful, calmer, more leisurely. It’s also casual because the developer or designer doesn’t think twice about using AI techniques. Intelligence becomes part of the practice of software creation.
Evan touches on one of the most intriguing implications of designing data-driven interfaces. When machines generate both content and interaction, they will often create experiences that designers didn’t imagine (both for better and for worse). The designer’s role may evolve into one of corralling the experience in broad directions, rather than down narrow paths. (See conversational interfaces and open-ended, Alexa/Siri-style interactions, for example.)
Designers need to stop thinking in terms of either-or interfaces — either we do it this way, or we do it that way. Casual intelligence lets interfaces become _and-also_ — different users have different experiences. Some users will have experiences never dreamed of in your wireframes — and those may be the best ones of all.
