Technology Myths and Urban Legends

Summary: When users don’t clearly understand how systems function, they develop unique (and often incorrect) theories to explain their experiences.

Frequently in user research, we hear people describe how they think technology works. Sometimes those theories are accurate, but most often they are not. Through the many user interviews, field studies, and user testing sessions that we’ve conducted for Nielsen Norman Group’s Life Online project, we heard many technology-related myths.

Technology myth: An (often inaccurate) user-generated theory about how a system functions, based on personal perceptions or second-hand experiences rather than any true understanding of the system’s functionality

We also observed how these myths impact user behavior and spread from user to user, effectively becoming urban legends.

How Technology Myths Develop

It’s human nature to generate explanations for phenomena around us. We form theories about how the world works and why things happen. An explanation makes us feel in control, whether or not that’s true.

Instances of this tendency abound in every ancient culture’s mythology. For example, oceanic storms and earthquakes were destructive and unpredictable to ancient Greek sailors. But if they had an explanation (Poseidon’s anger), then they could exert control on the outcome of the situation (through prayers and sacrifices).

Ancient Greek sailors believing that Poseidon caused dangerous seas because he's angry

Technology myths seem to arise in the same way. Users don’t have a clear understanding of how a system works, so they generate possible explanations that seem logical to them, based on existing knowledge and experience. This phenomenon has been occurring since the early days of personal internet use. In 2000, Andy Cockburn and Steve Jones found that only one participant out of eleven had a correct understanding how the browser’s Back button works. For the rest of the participants, their misunderstanding caused navigation issues as they browsed the web.

In particular, people tend to form myths around what they’re concerned about — for example, privacy, security, or saving money. One woman in our lab study in Kansas City was very worried about information security. “I hate sending information if it’s not secure,” she said. Unfortunately, she didn’t know much about how information technology functions. Whenever she submitted contact information through an online form, she clicked the Back button and manually removed her data from the form fields — even though that content had been already submitted. “It makes me feel like I’m deleting it. It’s probably still on there [the computer] or whatever, but it makes me feel like it’s secure,” she said.

In our usability testing in China, we heard two different theories about how pricing worked on Taobao, the hugely popular shopping platform.

One Chinese participant had heard from a friend that, for the same product, Taobao charged iPhone users more than it charged Android users. He assumed that, since iPhones were more expensive than Android devices, Taobao took advantage of these “richer” customers. As a consequence, he refused to shop on any ecommerce sites on his iPhone. (We informally tested his theory and did not find any difference in Taobao prices between iPhone and Android.)

A different Chinese participant told us that products are cheaper on Taobao’s mobile channels than on its desktop website. (She proved that her theory was actually true by searching for the same products on both desktop and mobile, and finding lower prices on mobile.)

Some technology myths can be at least partially attributed to a sense of distrust that people sometimes have toward digital products. Users have a general awareness and fear that designers and companies seek to manipulate them, so they are on high alert for any evidence of that manipulation.

One participant in a usability test in Raleigh, North Carolina was planning an upcoming vacation to Arizona. While researching flights, she told the facilitator that airline websites track how many times a user performs the same search, (destination and dates) and, for repeat searches, the airlines raise prices for that user because “they know you’re interested.” Clearly, the participant was suspicious that companies are tracking her behavior and taking advantage of it for their own profit. As a consequence, she said she always researches flights on one device, but purchases on another, to keep the website from recognizing her. She also shops only on aggregator sites like Kayak or Orbitz and doesn’t buy flights from airlines directly.

(As an aside, this theory is so popular that Time magazine covered it and Consumer Reports investigated it. Airlines deny the practice, but the results of the investigation seem inconclusive. One author of this article is a sworn believer in this theory and says she’s seen it happen in her own experience. The other author of this article is pretty sure that airlines do not increase prices based on user interest. Even UX consultants aren’t exempt from these technology myths!)

How Technology Myths Impact User Behavior

Users’ beliefs (accurate or inaccurate) about a system form their mental model: their unique, internal understanding of how that system works. That mental model influences the actions the user will take in the system.

When the user’s mental model is substantially different from the reality of the system, UX problems arise. Thus, these technology myths and urban legends, while interesting, can be harmful. Consider the examples above:

  • Removing the text entered in every form submitted online is a waste of time and a reason to avoid filling out forms on the web.
  • Avoiding one channel for fear of increased prices means more planning and less convenience.
  • Switching devices for the same flight search means extra work entering the same information twice.

In all these situations, the end result is a high interaction cost: people need to plan and spend effort getting around the (real or imaginary) hurdles raised in front of them by these myths.

How to Dispel Technology Myths

Most technology myths fall into one of three categories.

  • System-specific: A myth developed specifically about your product or a feature in your UI (e.g., the flight price recommendations on
  • Industry-specific: A myth developed about your industry or larger product type (e.g., airlines)
  • Universal: A myth that applies across products and industries, and that usually relates to some basic element (e.g., form fields)

While researching your users and evaluating your products, watch out for system-specific technology myths. Investigate whether it’s a belief unique to an individual user or is a widespread urban legend. Look for other clues as well: Does the feature generate a lot of questions for your support team or on social media? If so, it’s a good indication that your users are confused about how it works and will come up with their own explanations. The OUR ADVICE box tells users whether they should buy their flight now or wait for prices to decrease. This tool has the potential to generate myths about how it works — it’s a complex feature and it isn’t clear what data informs that recommendation.

If you find a technology myth in your research, consider what it says about your product. If the myth is harmful to your interaction design, change how you communicate that feature to users and show explanation messages to clarify how your system works.

In many cases, it’s better to hide the complexity and show only what users need to know, to avoid confusion. However, the existence of technology myths or urban legends can be a clue that more explicit communication with your users is needed.

Kayak provides a tool tip, with a little information about where the recommendation comes from: data scientists looking at current and past prices. Of course, this explanation is not much informative than saying that the company witch doctor sacrificed a goat at midnight and analyzed its intestines to determine prices, but at least it provides a claim that the recommendation is based on data and expertise, as opposed to paid advertising.

Industry-specific and universal technology myths are more difficult to detect and correct than system-specific myths. These are behaviors and misinterpretations that users picked up from their experiences with other systems. However, all technology myths arise from a lack of understanding. Being aware of these misunderstandings and clarifying through communication is the best approach to counteract any technology myth.

What technology myths have you heard? Share with us at @nngroup #techmyths.