Interview with Don Norman, by Bjoern Hartmann, October 2005
Don Norman wears many hats – Professor of Computer Science, Psychology and Cognitive Science at Northwestern University; Visiting Professor at Stanford University; principal of the Nielsen Norman user experience consulting group; and columnist for both ACM Interactions and InteriorMotives magazines. Bjoern Hartmann caught up with Don at his home in downtown Palo Alto to find out how he ended up at Stanford and what he is working on at the moment.
Don: I spent most of my academic career at UC San Diego, then 5 years at Apple, then Hewlett-Packard, then my own company. I followed the lure of a startup to Chicago. The startup folded; I went to Northwestern half-time so I could continue consulting and writing. But one day I was here in Palo Alto having lunch with Tom Kelley (of IDEO) when my wife called to tell me about some interesting real estate - an hour later I had bought a condo. I went back to Northwestern and said "To my great surprise we bought a condo in Palo Alto , so I guess I'm resigning.”
But we worked out an agreement where I teach the fall and the spring at Northwestern. Last Winter I also taught a course with Terry Winograd at Stanford.
My goal is to put structure to the field of design. Design has no real theoretical structure and I'm trying to find one. This is the theme of my past books – “User Centered System Design, “ “The Design of Everyday Things,” “Things That make Us Smart,” and “Emotional Design.” Now I am working on a new, important topic, the "design of intelligent everyday things" or the "psychology of machines." In theory I am writing a book on this topic - in practice it is still a mess. I love to teach courses on topics I don't understand, then afterwards, once I have figured things out, write the books. The best critics are graduate students whose job is to rip apart whatever the professor says. Nothing keeps a professor more honest, more up-to-date. More humble. But once I finish a topic, I become bored with it, so off I go to some new area that I do not (yet) understand.
Bjoern: You have been focusing on technologies in the automobile – which I think of primarily as a space. The car surrounds and contains me. How does that make interaction different from a mobile device that I hold in my hand?
Don: That is what's fascinating about the automobile - is has so many facets. It is a space for transportation; but there's also the driving space, which to the driver is sometimes a chore or a burden, but sometimes the purpose of the whole trip. Then there are the passengers – the car can be a social interaction space, an entertainment space, or a cooperative work place. All of these functions are known by the automobile designers who are adding more and more technology to encompass them. There are 50 to 100 processors and 6 or 7 networks within the automobile, there are ad-hoc networks being studied so cars can communicate with other cars or road infrastructure. It is getting very complex and I am concerned that the people designing this technology do not fully understand the ramifications from the point of view of interaction. Years ago I studied aviation safety and the role that automation played in aviation and I fear that the same errors are being made here.
Bjoern: In previous books you wrote about errors as applied to consumer products; you also mentioned errors in aviation; it seems like the car occupies a middle space.
Don: There was a big effort to look at human error after Three Mile Island which is when I got into the business. There have been fewer studies of other industries. Aviation has been most effective and most of the work comes out of NASA Ames right here [in Mountain View]. They funded me for a long time.
Recently, the medical profession has started to pay attention, but they are still reluctant. Most of us in the error business believe that most errors are system errors - that system designs encourage errors and prevent users from understanding what is going on. The medical system is still heavily involved in a blame regime where you want to find the people who made the error and punish them; but people should freely admit their errors without fear of punishment because it's the only way we can improve the system. But, let me make a different point:. people do make errors but it is because our machinery asks us to behave in ways that are not appropriate.
On top of that, when we automate we tend to automate the easy things. But when it gets difficult, the automation gives up, which is the opposite of what you want.
The question here is: what is attention? What are attentional resources?
The old model of attentional resources was CPU cycles - if I am idling, I am only using a small percentage of cycles and the rest is available anytime I need it. It's a model I helped develop in the 1970s. There is some evidence though that this is not appropriate. Maybe a better model would not be a fixed CPU but a mesh computer, where multiple CPUs are scattered around in a community. If I think [the current task] could be an easy job I get just enough CPUs to do the job. Now if I suddenly need more, I'm screwed. In the first model, I was not using the remaining capacity but it was available for me. But in the second model my attentive resources diminish and when I suddenly need them, they are not there. Some researchers in England are applying this model of “underload” to driving, which I find very intriguing.
The field of automated automobiles is progressing far more rapidly than I have thought possible. We have automated large amounts of the mechanical things in the engine, including shifting, and now the braking and the stability of the automobile, and the speed at which you're going - we have cruise control and adaptive cruise control.
When do you keep these systems on and when do you keep them off? I've heard of several accidents when people thought they were off when they were on and vice versa. Does my rental car have anti skid brakes or not? Do I hit the brakes hard or not? Does the car have stability control? When is your cruise control on or off? You don't have any way of knowing. There is a light that goes on, but the light turns on not to say whether automation is controlling the car, the light tells you whether the cruise control is armed or not which is about as stupid as I can possibly imagine.
Now take the instance of lane keeping control. Honda has a lane keeping control that, when it feels you drifting out of the lane, applies 80% of the torque required to get you back in. Why 80%? Because they want the driver to stay in the loop. Is that really the correct way of doing it? We don't know. What happens when the driver doesn't apply any force? Well the Honda will then warn the driver. What happens when the driver still doesn't respond? The Honda will then disconnect its lane keeping control. Which seems bizarre - isn't that when you might need it most? Then again, if it didn't then driver could just continue to ignore it. These are very complex issues.
Bjoern: You are generally advocating taking a larger systems perspective - how do these automations change the driving for other people? Through repetition I have built up a fairly reliable model how other human drivers will behave in certain situations. Is that going to change? Will I now have to keep different models in my head and judge whether the car in front of me is controlled by a human driver, by automation, or some hybrid?
Don: The most dangerous situations are those with mixed systems, where only some cars have automation capabilities. You can imagine a person gaming an adaptive cruise control system - let’s say there is a big block of cars ahead where he wants to go through so the driver just accelerates right through the middle of the flock, trusting that the automatic system of the other cars will make them move out of the way - unless one of them turns out not to be automated.
Bjoern: This heterogeneous situation seems to be unavoidable.
Don: So we better have really good performance standards. But suppose that driving were indeed completely automated - you wouldn't need lanes, stop signs, traffic lights; you might not need speed limits.
Bjoern: You mentioned in your columns on automobiles and home entertainment systems that these industries are ignorant of lessons learned in other industries before them. One of the positive counter-examples you brought up was user interfaces of personal computers. What were the major lessons learned there and what was the impetus to bring improvement to desktop computing? Can we hope that it's enough to point car and home entertainment industries to these achievements or will things get worse before they get better?
Don: Oh things always get worse before they get better. It's amazing how few people are understanding of these issues. In the computer industry there were two major players - Microsoft and Apple. Both took usability very seriously - Bill Gates has a clear personal interest in this - and Apple, of course, led the industry in insisting upon easy to use, simple products. This emphasis was throughout the company, from the CEO down. I joined Apple under John Scully, who really cared about these things. And Steve Jobs today really cares about it.
Although I had a debate with my wife today how to turn the iPod on or off. My explanation for this difficulty was "bad design." And then my iPod shuffle, which has a really bad design of the on-off/mode switch: not only can I not tell which position the mode switch is in, but it is physically difficult to move the switch. I know it's appropriate to praise Apple and damn Microsoft, but if you actually look at how both work, you'll find that Microsoft spends a lot more effort and time to try and make their systems better and I think they're actually doing quite well given the horrible constraints they face.
The American military also has historically been concerned with usability, especially the Air Force, because of a large number of aviation accidents due to human error. The cockpit is one of the best designed places. It looks complex, but quite often the thing that looks the simplest is the hardest to use and the thing that looks most complicated is the easiest.
Complexity comes with new technology - the engineers or the original creators are so proud that it works at all. For the first automobile, you needed a mechanic to keep it running. Many people drove with the mechanic as passenger. But with the modern computer, despite all its failings, we never had to have the IT person sitting by our side. (Hmm. Maybe we did!) We as consumers make things worse by saying "Wow, I really love it, but why can't it do this other thing?" People who like a technology, often request that it do even more. Eager companies rush to respond – they listen to their customers. The result is the bewildering, confusing state of many mature products: they suffer from extreme featurism.
But these are not technical problems, nor problems of design theory. They are problems of marketing, of the political struggle between competing companies and industries, and of market pressures. So although these have huge impact upon product design, they are not where I can make the most powerful contribution.
I'm only really interested in working on intellectual challenges where I can make a unique difference because I can bring a different point of view or bring together things people haven't thought about. I want to forge ahead. I want to think hard about how we should approach these problems. That’s why my current interest in the design issues of the 21st century: smart, intelligent devices in the automobile and home.
One of my standard approaches to a problem is to take the fundamental, unexamined axioms and reverse them. I was just interviewed by a reported doing a story on the dangers of interruption and distraction. My take was to answer that we have evolved to be interruptible and distractible. I think of it not as distraction, but as attention to change. The problem isn’t that we are continually interrupted, but rater that the technology of interruptions has far too much overhead. The overhead is often far more onerous than the content. So let’s make the interruptions have more content – make it easier to resume afterwards. Someone just asked me how to prevent graffiti. My response is why? Encourage it. It is wonderful folk art. The problem is that it takes place in inappropriate places, so let us make designs that encourage graffiti where it can be appreciated.
I also want to reexamine whatever you think the fundamental axioms are - I like to contradict because you often make great progress that way. Hence my recent paper "human -centered design considered harmful."
Bjoern: So where is the intellectual frontier in home technology?
Don: The frontier is in the use of automation. I discovered an old literature on autonomous agents - how do you instruct them, how do you trust them? Autonomous agents are now a hot topic again in artificial intelligence. And it is happening in the home - one of my old students - Michael Mozer has automated his home with a neural network. He has pointed out that it's sometimes very disconcerting when the home misreads him. Also, Mike may be working late some night and say "Oh my house is expecting me" and feel somehow compelled to get home because of his automated house which is an interesting response.
Bjoern: How far should we take this analogy with human behavior? What is the proper role for projecting personality onto technology or designing technology to behave as if it had certain personality traits?
Don: Let us think about what a personality trait is. A personality trait describes the way people behave in a given situation. So we are automatically designing personalities into our machines, even if we don’t realize it. soon as we design anything that behaves in a particular way, it has a personality. Even if we never thought about it that way. What is the personality of a machine? Is your car a relaxed car? Or is it very tense? The same with my kitchen - how does it respond to my actions?
Bjoern: So personality is inescapable. We cannot but give personality to the things we create.
Don: Yes, exactly. Don't forget that we are very good at interpreting the actions of animate objects and we anthropomorphize what we see - we assign personality and emotion to devices even if they don't have them.
If you think of the emotional system in humans as the information processing system that makes value judgments, well, then a machine should have that too if its autonomous. Now, these emotions don't have to be at all like human ones, but if the machine is to interact with humans, there have to be some commonalities. We display our emotions in our body. And over the many years of evolutions we've evolved use the body signs such as facial expressions, signs of muscle tenseness or relaxation, posture, and signs of approach or avoidance as a communicative device - so facial expressions are a rich communication device. There is no reason for machines to have similar facial expressions or body expressions - except that these might help communicate with people. So if my vacuum cleaner is having trouble, why not communicate that by something akin to facial expressions?
At the moment there is a small robotics community - the best work in my opinion is from Cynthia Breazealat MIT - where people are building real architectures based on emotional structures.
Bjoern: Where do you see the difference between having a robot enact emotions in physical space versus seeing a simulation of the robot or a virtual person on a computer screen?
Don: I think physicality offers a tremendous amount to us. I think what happened during the computer revolution - and this was true of the design world as well – is that people got carried away by virtuality. People were thinking that a computer could do everything we want it to; that a screen could display everything we need; that we wouldn’t need physical knobs and sliders and buttons anymore - we would just draw them on the screen and people would touch them. But it's not the same thing. You cannot touch these without looking. You miss all the powerful haptic and proprioceptive cues. That direction of design was a serious mistake.
Bjoern: I agree with you that we got carried away by the promise of virtuality and convergence. Do you feel we are swinging back towards realizing the importance of the physical? Is the emphasis on virtuality waning?
Don: I think it is part of the normal pendulum swing that we are more physical now. But there are now 6 billion people on the earth and while we are swinging back – while the community I interact with is swinging back - there are ever more new people joining the field completely unaware of the history. They are starting over and they are all going to repeat all the errors. Fields rarely think of looking at other fields - the aviation industry refused to learn from the nuclear power industry, the automobile industry doesn't look at the aviation industry, the home automation industry doesn't look at the others.
If people asked me: ‘are things better designed now or worse?’ My answer is yes. Better and worse. Even though we've made great progress, new people are building new things that are worse than ever before.
I believe that there's a new era of design happening which is about intelligent devices. So I think its time for examining the way how we interact with the autonomous agents, what happens when they fail, how we instruct them, and how we trust them.
Mozer, M. C. (2005). Lessons from an adaptive house. In D. Cook & R. Das. (Eds.), Smart environments: Technologies, protocols, and applications (pp. 273-294). Hoboken, NJ: J. Wiley & Sons. ftp://ftp.cs.colorado.edu/users/mozer/papers/smart_environments.pdf
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