At UX Collective, Alex Klein shares three capabilities designers need to build for the AI era:

  1. AI strategy: how can we use AI to solve legit customer problems (not just bolted-on “we have AI!” features)?
  2. AI interaction design: what new experiences (and risks) does AI introduce?
  3. Model design: prompt-writing means that designers can collaborate with engineers to guide how algorithms work; how can we use designerly skills to improve models?

I agree with all of it, but I share special excitement around the new problems and emerging interaction models that AI invites us to address and explore. I love the way Klein puts it, and why I’m sharing his article here:

We’ve moved from designing “waterslides,” where we focused on minimizing friction and ensuring fluid flow — to “wave pools,” where there is no clear path and every user engages in a unique way.

Over the past several years, the more that I’ve worked with AI and machine learning—with robot-generated content and robot-generated interaction—the more I’ve had to accept that I’m not in control of that experience as a designer. And that’s new. Interaction designers have traditionally designed a fixed path through information and interactions that we control and define. Now, when we allow the humans and machines to interact directly, they create their own experience outside of the tightly constrained paths we’re accustomed to providing.

We haven’t completely lost control, of course. We can choose when and where to allow this free-form interaction, blending those opportunities within controlled interaction paths. This has some implications that are worth exploring in both personal practice and as an industry. We’ve been working in all of these areas in our product work at Big Medium:

  • Sentient design. This is the term I’ve been using for AI-mediated interfaces. When the robots take on the responsibility for responding to humans, what becomes possible? What AI-facilitated experiences lie beyond the current fascination with chatbots? How might the systems themselves morph and adapt to present interfaces and interaction based on the user’s immediate need and interest? This doesn’t mean that every interface becomes a fever dream of information and interaction, but it does mean moving away from fixed templates and set UI patterns.

  • Defensive design. We’re used to designing for success and the happy path. When we let humans and robots interact directly, we have to shift to designing for failure and uncertainty. We have to design defensively, consider what could go wrong, how to prevent those issues where we can, and provide a gentle landing when we fail.

  • Persona-less design. As we get the very real ability to respond to users in a hyper-personalized way, do personas still matter? Is it relevant or useful to define broad categories of people or mindsets, when our systems are capable of addressing the individual and their mindset in the moment? UX tools like personas and journey maps may need a rethink. At the very least, we have to reconsider how we use them and in which contexts of our product design and strategy. As always, let’s understand whether our tools still fit the job. It might be that the robots tell us more about our users than we can tell the robots.

These are exciting times, and we’re learning a ton. At Big Medium, even though we’ve been working for years with machine learning and AI, we’re discovering new interaction models every day—and fresh opportunities to collaborate with the robots. We’re entering a new chapter of user experience and interaction design. It’s definitely a moment to explore, think big, and splash in puddles—or as Klein might put it, leave the waterslide to take a swim in the wave pool.

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