The illusion and the curse of knowledge behind the scene.

When I ask you to think about a close relative and tell me about them, you can easily do it and make more or less accurate statements about them. But when I ask you to think about your users… that’s an impossible task. It’s simply not feasible to know hundreds, thousands, or even millions of people well. In such cases, you have two options. Either you pick one well-known customer from the crowd and think about them, or — and this is what matters here — you view them through a concept or a model.

Model

You build this mental model using information gathered from reality and, importantly, by simplifying it. This process is called induction. Later, when you use this model — or let’s say, this “box” — to communicate with your customers or to develop products and services for them, that’s deduction.

Obviously, the more information you gather, the more sophisticated your model becomes.

The problem starts when the model is built from very little information, or when decisions are made solely based on one person’s model or opinion — regardless of everything else. This person is known in the literature as a HIPPO: the Highest Paid Person’s Opinion. Unfortunately, many organizations work like this.

Let’s go back to simplification and the process of creating models. Here’s where humans, as the problem, come into play. The problem is always us. We, humans, tend to distort information. And not just a little, but significantly. What’s more, we do it without even realizing it.

Influencing phenomena

Let me highlight two major biases that significantly influence us, based on my own experience.

The illusion of knowledge

Let me share a brief study in which Frank Keil and his students asked participants to rate how well they understood the functioning of everyday objects like zippers, toilets, and ballpoint pens on a scale from 1 to 7. On average, participants rated their knowledge between 4–5. Then, Frank and his team asked them to explain in detail how these objects work. Most of them had no clue, that their real results were between 1–2.

This is called the illusion of knowledge — we tend to overestimate our knowledge.

What does it mean in relation to clients: We believe we know our users better than we actually do.

The curse of knowledge

In 1990 at Stanford University, Elizabeth Newton divided people into two groups: “tappers” and “listeners”. Each “tapper” was asked to tap the rhythm of a well-known song (e.g. Happy Birthday) on a table while a “listener” tried to guess the song.

Before the task, Elizabeth asked the tappers to estimate what percentage of songs the listeners would guess correctly. The tappers estimated 50%, while the actual result was only 2.5%. A huge difference.

Elizabeth called this the curse of knowledge — we cannot disregard ourselves from what we already know.

What does it mean in relation to clients: We assume users and customers have far more knowledge than they actually do.

I don’t know how you feel, but I am often told by my clients: “We already know enough, what is more a lot about our customers”. To be honest we as designers are not an exception to that.

In my experience, the illusion of knowledge and the curse of knowledge are the primary reasons why companies and clients are reluctant to spend (enough) on research.

Scientific methodologies

Science currently identifies nearly 220 such biases. It would be foolish to think humans are rational creatures. Scientific methodologies have evolved precisely because of our biases, aiming to make experiments and research more objective and rational. The goal is practically to remove humans and their weaknesses from the equation.

AIt is out of question: you should do research. You need to research in order to understand your users better and to refine your model.
Invest in it!

I’m well aware that there are many other factors contributing to why companies don’t spend (enough) on research. If you know of any, feel free to share them in the comments. In the post, I highlighted the two most important biases.

Why don’t they spend (enough) on research? was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.