PDF Summary:The Design of Everyday Things, by Don Norman

If you’ve ever pushed a “pull” door or accidentally flipped the wrong light switch, you’ve experienced the impact of bad design. You may have blamed these mistakes on yourself, but in reality, the way we interact with the physical world is often driven by design. From smartphones to stovetops, faucets to fighter jets: Every object we encounter on a daily basis is designed. Good design streamlines our lives and makes everyday tasks easier. Bad design, on the other hand, causes frustration, errors, and even dangerous accidents.

In order to tell the difference, we need to understand how we perceive the objects all around us, and how our brains make sense of that information. Combining the principles of cognitive psychology and engineering makes all of us smarter consumers and helps designers create products that work with users, rather than against them.

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Memory

Memory also impacts our interactions with objects. There are two kinds of knowledge: “knowledge in the head” (memory) and “knowledge in the world," which is anything we don’t have to remember because it’s contained in the environment (like the letters printed on keyboard keys). Putting knowledge into the world frees up space in our memories and makes it easier to use an object.

The knowledge we keep in our heads is only as precise as the environment requires. Most people won’t notice if you change the silhouette on an American penny because we only need to remember the color and size to tell a penny apart from other coins. We’re more likely to notice changes to the portrait on an American dollar bill, because we’re used to relying on that image to help us tell bills apart (since they are identical in size, shape, and color).

Memories can be stored either short- or long-term. Short-term memory is the automatic storage of recent information. We can store about five to seven items in short-term memory at a time, but if we lose focus, those memories quickly disappear. This is important for design: Any design that requires the user to remember something is likely to cause errors.

Long-term memory isn’t limited by time or number of items, but memories are stored subjectively. Meaningful things are easy to remember; arbitrary things are not. To remember arbitrary things, we need to impose our own meaning through mnemonics or approximate mental models. Designers can make this easier for users by making arbitrary information map onto existing mental models (for example, think of the way Apple has kept the location of the power and volume buttons relatively the same with each new version of the iPhone.)

The Error of “Human Error”

Industry professionals estimate that between 75 and 95 percent of industrial accidents are attributed to human error. This number is misleading, since what we think of as “human errors” are more likely outcomes of a system that has been unintentionally designed to create error, rather than prevent it.

Detecting Errors

Errors can be divided into “slips” (errors of doing) and “mistakes” (errors of thinking). Accidentally putting salt instead of sugar in your coffee is a slip—your thinking was correct, but the action went awry. Pressing the wrong button on a new remote control is a mistake—you carried out the action fine, but your thought about the button’s function was wrong.

Most everyday errors are slips, since they happen during the subconscious transition from thinking to doing. Slips happen more frequently to experts than beginners, since beginners are consciously thinking through each step of a task. On the other hand, mistakes are more likely to happen in brand new scenarios where we have no prior experience to pull from, or even familiar scenarios if we misread the situation.

Causes of Error

One major cause of error is that our technology is engineered for “perfect” humans who never lose focus, get tired, forget information, or get interrupted. Unfortunately, these humans don’t exist. Interruptions in particular are a major source of error, especially in high-risk environments like medicine and aviation.

Social and economic pressures also cause error. The larger the system, the more expensive it is to shut down to investigate and fix errors. As a result, people overlook errors and make questionable decisions to save time and money. If conditions line up in a certain way, what starts as a small error can escalate into disastrous consequences.

• Social and economic pressures played a critical role in the Tenerife airport disaster, when a plane taking off before receiving clearance crashed into another plane taxiing down the runway at the wrong time. The first plane had already been delayed, and the captain decided to take off early to get ahead of a heavy fog rolling in, ignoring the objections of the first officer. The crew of the second plane questioned the unusual order from air traffic control to taxi on the runway, but obeyed anyway. Social hierarchy and economic pressure led both crews to make critical mistakes, ultimately costing 583 lives.

Preventing Errors

Good design can minimize errors in many ways. One approach is resilience engineering, which focuses on building robust systems where error is expected and prepared for in advance. There are three main tenets of resilience engineering.

1. Consider all the systems involved in product development (including social systems).
2. Test under real-life conditions, even if it means shutting down parts of a system.
3. Test continuously, not as a means to an end, since situations are always changing.

Constraints

Designers can also use constraints, which limit the ways users can interact with an object. There are four main types of constraints: physical, cultural, semantic, and logical.

Physical constraints are physical qualities of an object that limit the ways it can interact with users or other objects. The shape and size of a key is a physical constraint that determines the types of locks the key can fit into. Childproof caps on medicine bottles are physical constraints that limit the type of users who can open the bottle.

Cultural constraints are the “rules” of society that help us understand how to interact with our environment. For example, when we see a traditional doorknob, we expect that whatever surface it’s attached to is a door that can be opened. This isn’t caused by the design of the doorknob, but by the cultural convention that says “knobs open doors."

When these agreements about how things are done are codified into law or official literature, they become standards. We rely on standards when design alone isn’t enough to make sure everyone knows the “rules” of a situation (for example, the layout of numbers on an analog clock is standardized so that we can read any clock, anywhere in the world).

Although they’re less common, semantic and logical constraints are still important. Semantic constraints dictate whether information is meaningful. This is why we can ignore streetlights while driving, but still notice brake lights—we’ve assigned meaning to brake lights (“stop!”), so we know to pay attention and react.

Logical constraints make use of fundamental logic (like process of elimination) to guide behavior. For example, if you take apart the plumbing beneath a sink drain to fix a leak, then discover an extra part leftover after you’ve reassembled the pipes, you know you’ve done something wrong because, logically, all the parts that came out should have gone back in.

The Design Thinking Process

“Design thinking” is the process of examining a situation to discover the root problem, exploring possible solutions to that problem, testing those solutions, and making improvements based on those tests. This process is iterative, which means it is repeated as many times as necessary, each time with slight improvements based on previous iterations.

Design thinking involves two tasks: finding the right problem and finding the right solution. Designers are often hired to solve symptoms, but good designers dig deeper to find the underlying problem before coming up with solutions. To do this, designers run through four stages: observation, idea generation, prototyping, and testing. This process is repeated as many times as necessary to develop the final product.

The observation phase involves gathering information on the people who will use the new design. This is different from market research: Designers want to know what people need and how they might use certain products, while marketers want to know which groups of people are most likely to buy the product.

After observation comes the idea generation phase, where designers brainstorm solutions to the problem. The goal is to generate as many ideas as possible without censoring “silly” ideas, since they might spark valuable discussion. Designers will then create prototypes of the most promising ideas using things like sketches and cardboard models.

Once the prototype is refined, the testing phase begins, where members of the target user group are asked to try out the prototype and give their feedback. Designers then repeat the entire process based on the feedback from the first round of testing. The iterative design thinking process emphasizes testing in small batches with refinement in between rather than waiting until the final product and testing with a much larger group.

Design Thinking in the Real World

In reality, the design process often doesn’t live up to the above ideal. Business pressures are the primary culprit here, since a well-designed product will still fail if it’s over budget and past deadlines. Product development team dynamics are also a challenge. The best teams are multidisciplinary, combining unique knowledge from different fields. However, each team member usually thinks their discipline is the most important.

Diversity among users can also impact design. For users with disabilities, designers can turn to a universal design approach. Universal design creates products that are usable by the widest range of people by designing for the highest need, not the average need. Adopting a universal design approach changes how designers choose the types of people and environments to observe as well as the features they focus on most in the prototyping and testing phases.

This approach is “universal” because if a product, environment, or service is designed with disability access in mind, it will typically also be usable for those without disabilities. For example, curb cuts were originally designed for wheelchair users but are also enormously helpful for anyone pushing a stroller or lugging a suitcase.

Technological Innovation

Economic pressures drive innovation. This can take the form of “featuritis," or the tendency to add more and more features to a product to keep up with competitors. These features ultimately degrade the design quality of the original product. Rather than winning over customers with new features, it’s better to do one thing better than anyone else on the market.

Real quality innovation can be either radical or incremental. Radical innovation involves high-risk, game-changing ideas while incremental innovation makes small improvements to existing products over time. The invention of the automobile was radical—all the small improvements that led to cars as we know them today happened incrementally.

The Future of Technology

Rapid technological innovation raises questions about the future of user experience. The way we interact with objects around us will certainly change in response to new technologies, and cultural conventions will change to reflect that. But human needs will remain the same. For example, the keyboard has evolved from mechanical typewriters to computer keyboards to touchscreen versions, but the need to record written information has stayed the same. In other words, human needs won’t change, but the way they’re satisfied will.

Some people fear that the rise of smart technology is making humans less intelligent because we can delegate even the most basic tasks to machines—and if those machines fail, we are totally helpless. It’s true that some traditional skills are becoming obsolete thanks to new technology, but that process ultimately makes us smarter. The energy saved by not having to create a fire every time we need heat or light or rely on long division for simple calculations can be channeled into higher-level pursuits. Our intelligence hasn’t changed, only the tasks we apply it to. The key is in using technology to do the jobs technology can and should do.

Increased Creation and Consumption

Technological innovation has made it easier than ever for anyone with a computer to create and publish new media. While amateur content creation has gotten easier, creating professional content has gotten harder and more expensive. The accessibility of smart technology levels the playing field, but makes it much harder to find quality, fact-checked content.

For manufacturers, new technologies present a different challenge. The need to entice buyers is a fundamental part of business, because a product that doesn’t sell is a failure, no matter how well designed it is. But while services like healthcare and food distribution are self-sustaining (because there will always be a need for them), durable physical goods are not. If everyone who needs a particular product purchases one, there’s no one left to sell it to; If everyone already owns a smartphone, how do you convince them to buy the new and improved model?

One way manufacturers get around this is through planned obsolescence, the practice of designing products that will break down after a certain amount of time and need to be replaced. This creates a cycle of consumption: buy something, use it until it breaks, throw it away, and buy another. While this cycle is good for business, the waste it generates is horrible for the environment. Thankfully, the combination of new technologies and a growing cultural awareness of sustainability issues is creating a new paradigm. The future of technology involves products designed with both the user and the environment in mind.