by Don Norman
•Think positively, for yourself and for the people you interact with.
Falsely Blaming Yourself
I have studied people making errors—sometimes serious ones— with mechanical devices, light switches and fuses, computer operating systems and word processors, even airplanes and nuclear power plants. Invariably people feel guilty and either try to hide the error or blame themselves for “stupidity” or “clumsiness.” I often have difficulty getting permission to watch: nobody likes to be observed performing badly. I point out that the design is faulty and that others make the same errors, yet if the task appears simple or trivial, people still blame themselves. It is almost as if they take perverse pride in thinking of themselves as mechanically incompetent.
I once was asked by a large computer company to evaluate a brand-new product. I spent a day learning to use it and trying it out on various problems. In using the keyboard to enter data, it was necessary to differentiate between the Return key and the Enter key. If the wrong key was pressed, the last few minutes’ work was irrevocably lost.
I pointed out this problem to the designer, explaining that I, myself, had made the error frequently and that my analyses indicated that this was very likely to be a frequent error among users. The designer’s first response was: “Why did you make that error? Didn’t you read the manual?” He proceeded to explain the different functions of the two keys.
“Yes, yes,” I explained, “I understand the two keys, I simply confuse them. They have similar functions, are located in similar locations on the keyboard, and as a skilled typist, I often hit Return automatically, without thought. Certainly others have had similar problems.”
“Nope,” said the designer. He claimed that I was the only person who had ever complained, and the company’s employees had been using the system for many months. I was skeptical, so we went together to some of the employees and asked them whether they had ever hit the Return key when they should have hit Enter. And did they ever lose their work as a result?
“Oh, yes,” they said, “we do that a lot.”
Well, how come nobody ever said anything about it? After all, they were encouraged to report all problems with the system. The reason was simple: when the system stopped working or did something strange, they dutifully reported it as a problem. But when they made the Return versus Enter error, they blamed themselves. After all, they had been told what to do. They had simply erred.
The idea that a person is at fault when something goes wrong is deeply entrenched in society. That’s why we blame others and even ourselves. Unfortunately, the idea that a person is at fault is imbedded in the legal system. When major accidents occur, official courts of inquiry are set up to assess the blame. More and more often the blame is attributed to “human error.” The person involved can be fined, punished, or fired. Maybe training procedures are revised. The law rests comfortably. But in my experience, human error usually is a result of poor design: it should be called system error. Humans err continually; it is an intrinsic part of our nature. System design should take this into account. Pinning the blame on the person may be a comfortable way to proceed, but why was the system ever designed so that a single act by a single person could cause calamity? Worse, blaming the person without fixing the root, underlying cause does not fix the problem: the same error is likely to be repeated by someone else. I return to the topic of human error in Chapter 5.
Of course, people do make errors. Complex devices will always require some instruction, and someone using them without instruction should expect to make errors and to be confused. But designers should take special pains to make errors as cost-free as possible. Here is my credo about errors:
Eliminate the term human error. Instead, talk about communication and interaction: what we call an error is usually bad communication or interaction. When people collaborate with one another, the word error is never used to characterize another person’s utterance. That’s because each person is trying to understand and respond to the other, and when something is not understood or seems inappropriate, it is questioned, clarified, and the collaboration continues. Why can’t the interaction between a person and a machine be thought of as collaboration?
Machines are not people. They can’t communicate and understand the same way we do. This means that their designers have a special obligation to ensure that the behavior of machines is understandable to the people who interact with them. True collaboration requires each party to make some effort to accommodate and understand the other. When we collaborate with machines, it is people who must do all the accommodation. Why shouldn’t the machine be more friendly? The machine should accept normal human behavior, but just as people often subconsciously assess the accuracy of things being said, machines should judge the quality of information given it, in this case to help its operators avoid grievous errors because of simple slips (discussed in Chapter 5). Today, we insist that people perform abnormally, to adapt themselves to the peculiar demands of machines, which includes always giving precise, accurate information. Humans are particularly bad at this, yet when they fail to meet the arbitrary, inhuman requirements of machines, we call it human error. No, it is design error.
Designers should strive to minimize the chance of inappropriate actions in the first place by using affordances, signifiers, good mapping, and constraints to guide the actions. If a person performs an inappropriate action, the design should maximize the chance that this can be discovered and then rectified. This requires good, intelligible feedback coupled with a simple, clear conceptual model. When people understand what has happened, what state the system is in, and what the most appropriate set of actions is, they can perform their activities more effectively.
People are not machines. Machines don’t have to deal with continual interruptions. People are subjected to continual interruptions. As a result, we are often bouncing back and forth between tasks, having to recover our place, what we were doing, and what we were thinking when we return to a previous task. No wonder we sometimes forget our place when we return to the original task, either skipping or repeating a step, or imprecisely retaining the information we were about to enter.
Our strengths are in our flexibility and creativity, in coming up with solutions to novel problems. We are creative and imaginative, not mechanical and precise. Machines require precision and accuracy; people don’t. And we are particularly bad at providing precise and accurate inputs. So why are we always required to do so? Why do we put the requirements of machines above those of people?
When people interact with machines, things will not always go smoothly. This is to be expected. So designers should anticipate this. It is easy to design devices that work well when everything goes as planned. The hard and necessary part of design is to make things work well even when things do not go as planned.
HOW TECHNOLOGY CAN ACCOMMODATE HUMAN BEHAVIOR
In the past, cost prevented many manufacturers from providing useful feedback that would assist people in forming accurate conceptual models. The cost of color displays large and flexible enough to provide the required information was prohibitive for small, inexpensive devices. But as the cost of sensors and displays has dropped, it is now possible to do a lot more.
Thanks to display screens, telephones are much easier to use than ever before, so my extensive criticisms of phones found in the earlier edition of this book have been removed. I look forward to great improvements in all our devices now that the importance of these design principles are becoming recognized and the enhanced quality and lower costs of displays make it possible to implement the ideas.
PROVIDING A CONCEPTUAL MODEL FOR A HOME THERMOSTAT
My thermostat, for example (designed by Nest Labs), has a colorful display that is normally off, turning on only when it senses that I am nearby. Then it provides me with the current temperature of the room, the temperature to which it is set, and whether it is heating or cooling the room (the background color changes from black when it is neither heating nor cooling, to orange
while heating, or to blue while cooling). It learns my daily patterns, so it changes temperature automatically, lowering it at bedtime, raising it again in the morning, and going into “away” mode when it detects that nobody is in the house. All the time, it explains what it is doing. Thus, when it has to change the room temperature substantially (either because someone has entered a manual change or because it has decided that it is now time to switch), it gives a prediction: “Now 75°, will be 72° in 20 minutes.” In addition, Nest can be connected wirelessly to smart devices that allow for remote operation of the thermostat and also for larger screens to provide a detailed analysis of its performance, aiding the home occupant’s development of a conceptual model both of Nest and also of the home’s energy consumption. Is Nest perfect? No, but it marks improvement in the collaborative interaction of people and everyday things.
FIGURE 2.6.A Thermostat with an Explicit Conceptual Model. This thermostat, manufactured by Nest Labs, helps people form a good conceptual model of its operation. Photo A shows the thermostat. The background, blue, indicates that it is now cooling the home. The current temperature is 75°F (24°C) and the target temperature is 72°F (22°C), which it expects to reach in 20 minutes. Photo B shows its use of a smart phone to deliver a summary of its settings and the home’s energy use. Both A and B combine to help the home dweller develop conceptual models of the thermostat and the home’s energy consumption. (Photographs courtesy of Nest Labs, Inc.)
ENTERING DATES, TIMES, AND TELEPHONE NUMBERS
Many machines are programmed to be very fussy about the form of input they require, where the fussiness is not a requirement of the machine but due to the lack of consideration for people in the design of the software. In other words: inappropriate programming. Consider these examples.
Many of us spend hours filling out forms on computers—forms that require names, dates, addresses, telephone numbers, monetary sums, and other information in a fixed, rigid format. Worse, often we are not even told the correct format until we get it wrong. Why not figure out the variety of ways a person might fill out a form and accommodate all of them? Some companies have done excellent jobs at this, so let us celebrate their actions.
Consider Microsoft’s calendar program. Here, it is possible to specify dates any way you like: “November 23, 2015,” “23 Nov. 15,” or “11.23.15.” It even accepts phrases such as “a week from Thursday,” “tomorrow,” “a week from tomorrow,” or “yesterday.” Same with time. You can enter the time any way you want: “3:45 PM,” “15.35,” “an hour,” “two and one-half hours.” Same with telephone numbers: Want to start with a + sign (to indicate the code for international dialing)? No problem. Like to separate the number fields with spaces, dashes, parentheses, slashes, periods? No problem. As long as the program can decipher the date, time, or telephone number into a legal format, it is accepted. I hope the team that worked on this got bonuses and promotions.
Although I single out Microsoft for being the pioneer in accepting a wide variety of formats, it is now becoming standard practice. By the time you read this, I would hope that every program would permit any intelligible format for names, dates, phone numbers, street addresses, and so on, transforming whatever is entered into whatever form the internal programming needs. But I predict that even in the twenty-second century, there will still be forms that require precise accurate (but arbitrary) formats for no reason except the laziness of the programming team. Perhaps in the years that pass between this book’s publication and when you are reading this, great improvements will have been made. If we are all lucky, this section will be badly out of date. I hope so.
The Seven Stages of Action: Seven Fundamental Design Principles
The seven-stage model of the action cycle can be a valuable design tool, for it provides a basic checklist of questions to ask. In general, each stage of action requires its own special design strategies and, in turn, provides its own opportunity for disaster. Figure 2.7 summarizes the questions:
1.What do I want to accomplish?
2.What are the alternative action sequences?
3.What action can I do now?
4.How do I do it?
5.What happened?
6.What does it mean?
7.Is this okay? Have I accomplished my goal?
FIGURE 2.7.The Seven Stages of Action as Design Aids. Each of the seven stages indicates a place where the person using the system has a question. The seven questions pose seven design themes. How should the design convey the information required to answer the user’s question? Through appropriate constraint and mappings, signifiers and conceptual models, feedback and visibility. The information that helps answer questions of execution (doing) is feedforward. The information that aids in understanding what has happened is feedback.
Anyone using a product should always be able to determine the answers to all seven questions. This puts the burden on the designer to ensure that at each stage, the product provides the information required to answer the question.
The information that helps answer questions of execution (doing) is feedforward. The information that aids in understanding what has happened is feedback. Everyone knows what feedback is. It helps you know what happened. But how do you know what you can do? That’s the role of feedforward, a term borrowed from control theory.
Feedforward is accomplished through appropriate use of signifiers, constraints, and mappings. The conceptual model plays an important role. Feedback is accomplished through explicit information about the impact of the action. Once again, the conceptual model plays an important role.
Both feedback and feedforward need to be presented in a form that is readily interpreted by the people using the system. The presentation has to match how people view the goal they are trying to achieve and their expectations. Information must match human needs.
The insights from the seven stages of action lead us to seven fundamental principles of design:
1.Discoverability. It is possible to determine what actions are possible and the current state of the device.
2.Feedback. There is full and continuous information about the results of actions and the current state of the product or service. After an action has been executed, it is easy to determine the new state.
3.Conceptual model. The design projects all the information needed to create a good conceptual model of the system, leading to understanding and a feeling of control. The conceptual model enhances both discoverability and evaluation of results.
4.Affordances. The proper affordances exist to make the desired actions possible.
5.Signifiers. Effective use of signifiers ensures discoverability and that the feedback is well communicated and intelligible.
6.Mappings. The relationship between controls and their actions follows the principles of good mapping, enhanced as much as possible through spatial layout and temporal contiguity.
7.Constraints. Providing physical, logical, semantic, and cultural constraints guides actions and eases interpretation.
The next time you can’t immediately figure out the shower control in a hotel room or have trouble using an unfamiliar television set or kitchen appliance, remember that the problem is in the design. Ask yourself where the problem lies. At which of the seven stages of action does it fail? Which design principles are deficient?
But it is easy to find fault: the key is to be able to do things better. Ask yourself how the difficulty came about. Realize that many different groups of people might have been involved, each of which might have had intelligent, sensible reasons for their actions. For example, a troublesome bathroom shower was designed by people who were unable to know how it would be installed, then the shower controls might have been selected by a building contractor to fit the home plans provided by yet another person. Finally, a plumber, who may not have had contact with any of the other people, did the installation. Where did the problems arise? It could have been at any one (or several) of these stages. The result may appear to be poor design, but it may a
ctually arise from poor communication.
One of my self-imposed rules is, “Don’t criticize unless you can do better.” Try to understand how the faulty design might have occurred: try to determine how it could have been done otherwise. Thinking about the causes and possible fixes to bad design should make you better appreciate good design. So, the next time you come across a well-designed object, one that you can use smoothly and effortlessly on the first try, stop and examine it. Consider how well it masters the seven stages of action and the principles of design. Recognize that most of our interactions with products are actually interactions with a complex system: good design requires consideration of the entire system to ensure that the requirements, intentions, and desires at each stage are faithfully understood and respected at all the other stages.
CHAPTER THREE
KNOWLEDGE IN THE HEAD AND IN THE WORLD
A friend kindly let me borrow his car, an older, classic Saab. Just before I was about to leave, I found a note waiting for me: “I should have mentioned that to get the key out of the ignition, the car needs to be in reverse.” The car needs to be in reverse! If I hadn’t seen the note, I never could have figured that out. There was no visible cue in the car: the knowledge needed for this trick had to reside in the head. If the driver lacks that knowledge, the key stays in the ignition forever.
Every day we are confronted by numerous objects, devices, and services, each of which requires us to behave or act in some particular manner. Overall, we manage quite well. Our knowledge is often quite incomplete, ambiguous, or even wrong, but that doesn’t matter: we still get through the day just fine. How do we manage? We combine knowledge in the head with knowledge in the world. Why combine? Because neither alone will suffice.
It is easy to demonstrate the faulty nature of human knowledge and memory. The psychologists Ray Nickerson and Marilyn Adams showed that people do not remember what common coins look like (Figure 3.1). Even though the example is for the American one-cent piece, the penny, the finding holds true for currencies across the world. But despite our ignorance of the coins’ appearance, we use our money properly.
