Nielsen Norman Group and Northwestern University | norman@nngroup.com
We are failing.
Are products getting more or less usable? Every year products do get better; every year shows a growth in good design. But the number of new products— and most important of all, new product categories—grows even faster. We preach the virtues of good design to the converted, so most of the time our messages fall on deaf ears. Actually, when it comes to the ever-increasing number of new product categories, our messages don’t even reach any ears.
That there is a fundamental mismatch between people and machines is well recognized within the human-centered design discipline. This gives rise to many of our cherished principles about the need for explanation, explicit communication, etc. Such principles are designed to let people know precisely what is expected of them so they might behave appropriately. I call this the “ communicative” strategy.
I believe if a communication failure is widespread, the problem must be in the message. Let me suggest a new approach, one that tries to give the engineers, programmers, and the non-hip design community a different way to think about the issues. The communicative strategy has failed, so let’s try anew.
The problem with the com-
municative approach is that it
puts the battle between people
and technology into technology’s territory. All good debaters and negotiators know that you must control the turf: You have to get the discussion on your own territory, where the terms and frames of reference are in your favor. We have to move away from the technological imperatives and move back to the needs of people—to put the onus on the technology to follow human imperatives, constraints, and behavior.
There are excellent examples we can use to show off the virtues of good design. Consider how the best voice-technology systems work today. Suppose the system has been interacting with a customer over a possible airplane flight and now wishes to know if it should make the reservation. It asks, “Would you like me to reserve this flight for you?” In theory, all the person has to do is say yes or no.
In the early days of voice recognition, some effort was made to train people to respond “properly,” because anything else confused the system. This was forcing human behavior onto technology’s territory. This approach failed.
People have a wide variety of ways of expressing either response. We can say yes by uttering uh-huh, sure, OK, yes, um, yeah, or, “cough...wait...um... that’s fine.” And we can express no by uttering no, no way, sorry, uh-uh. Moreover, people could
very well say other things, such as what, not now, later, which flight was that, make it a later flight… etc. Or imagine someone saying “Oh, I don’t know, maybe, um, well sure. Yes. Do it.” A simple word-spotting program is apt to hear the “know” and think the person said “no.”
Today good systems accept all of these utterances (and many more). Moreover, even if the system can’t understand the response, it does not blame the person; it asks for assistance in understanding. So with that last complex utterance, it might ask: “I believe you said yes; is this correct?” These systems do not ask people to accommodate the technology; they ask the technology to accommodate people.
The systems follow several principles. One is to constrain the task domain so much that only a few responses are likely, and the system can interpret all of them. This is the kind of flexibility I call compliant and tolerant. Another is to try to infer the customer’s intention, and to try to satisfy the intention, regardless of the words spoken. This is effective when it works, but it can be dangerous— when it’s wrong, it can be very wrong. But where the task is well understood and constrained, all of these approaches work extremely well.
Unfortunately, many of our systems today are rigid and unbending. I still find it surpris-
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