Smarter AI Product Design Centers the User’s Real Needs

Over the past few years, the tech industry has rushed to plug a new microchip into every device on the assumption that if you can add AI, you should. Smart vision toothbrushes, mood-reading household robots, and a host of physical products are invading consumers’ daily lives, reliant on artificial intelligence to learn, predict, and adjust our behavior.

But as anyone who’s struggled to update the firmware in their fridge knows, AI doesn’t improve every product. Some product designers are asking where the line is between genuine innovation and a solution looking for a problem.

Savannah Kunovsky leads a team of industrial product designers at Ideo, a design consultancy based in San Francisco focused on helping clients unpack when AI becomes a barrier rather than a breakthrough.

Kunovsky spoke with IEEE Spectrum about the pressure to integrate AI in everything, where that integration goes wrong, and what companies can do to determine when an AI integration is—and isn’t—a smart choice.

When AI makes products worse

How much of the current wave of AI integration into physical products is driven by pressure from investors and shareholders to keep up with industry trends?

Savannah Kunovsky: Some of it. Teams come to us feeling pressured to show they’re doing something with AI, sometimes because a CEO has promised the board an “AI story” before the next earnings call, or a competitor has just launched an AI-powered version of their product.

In all cases, the first thing we do is step back and ask who the product is for and what they’re trying to do. Once that’s clear, the role AI should play, whether large, small, or invisible, usually becomes obvious. There is an appetite for this kind of grounding in the industry right now. People want to cut through the hype and see what works in practice.

How do you distinguish between a genuinely helpful AI feature and a gimmick?

Kunovsky: The test for an AI gimmick is the same test we’d apply to any product experience: Does it help someone do what they’re trying to do? Answering that means understanding how people would use the product in the real context they’ll be using it.

Many companies look straight to large language models (LLMs) because that’s top of their mind, but there is a whole AI toolbox to draw from: computer vision, sensor fusion, on-device models, et cetera. Picking the right capability for the task matters as much as deciding whether to use AI in the first place.

As a new interaction paradigm, AI is asking people to change their behavior, so it needs to be simple. When IDEO’s predecessor firm worked on Apple’s first mouse in the early 1980s, the team gave it only one button because people were learning a completely unfamiliar system and the interaction mechanism needed to be effortless.

The wearable Humane AI pin used projection instead of a screen-based display, making a dramatic shift from the smartphone interface users already knew.Angel Garcia/Bloomberg/Getty…