Why the best outcome might be "But we already knew that!"
It was a cold winter day in early 1999. I stood in an elevator with three undergraduate classmates from my Psych 225 course in Experimental Psychology.
We'd already ridden up and down several times, from the Memorial Library entrance to the top floor. We had an odd (and perhaps a bit creepy?) mission: We were waiting for a person to get on the elevator alone.
photo by Jason Dent via Unsplash
Finally, one did. Like us, she looked like a student, wrapped up in a hat, scarf and coat, with a backpack loaded with books over one shoulder and a thermos full of coffee in her hand. The elevator doors closed, and we began to ascend in silence.
My classmate dropped a handful of coins on the floor of the elevator, the sound deafening in the enclosed space. He mumbled apologetically and stooped to pick up the coins. The rest of us stood, staring straight ahead.
I felt a nervous giggle form in my chest and immediately suppressed it. My role was to stand, unmoving, with a deadpan expression, and laughter would ruin the experimental setting we had constructed.
The new arrival jumped slightly when the coins hit the floor, and then looked to the rest of the carriage's inhabitants. She glanced back to the coins, back at us, and then stood, shifting her weight, twisting her thermos, staring somewhere between the floor and the ceiling, like she wished she were somewhere else.
photo by Chris Briggs via Unsplash
Testing the bystander effect
The bystander effect refers to the phenomenon where an individual is less inclined to offer assistance when there are passive onlookers present. It’s primarily related to response in emergency situations. The most common example used to illustrate it is the 1968 rape and murder of Kitty Genovese, where an unverified number of neighbors heard Kitty crying for help but no one intervened until it was too late.
The bystander effect is often mentioned in introductory psychology textbooks, and that’s why we found ourselves spending time in a university library elevator: We were attempting to replicate the finding. In most cases dropping change cannot be defined as an emergency situation, but our professor had deemed it relevant enough for us to verify the phenomenon.
We spent the afternoon testing two conditions: One where a single student would drop coins in an elevator with one unknowing participant, and another where a group of us would join, and deliberately avoid helping our clumsy, coin-dropping colleague, thus triggering diffusion of responsibility.
The results were in line with the theory: When the coins were dropped by a student and there were no passive bystanders, the other person would help. When we were present as passive bystanders, the other person would look to us, observe our apathy, imitate our behavior and not bend down to help pick up the coins.
And I was absolutely giddy: We read this thing in a book, we tried it out in the real world - and watched the theory confirm itself, in real time. The bystander effect wasn’t just someone’s one-off explanation for a tragic situation 60 years ago: It seemed to be an actual tenant of human behavior. My mind started spinning. What else did we know? What else could we test? This experience would shape my life.
“But we already knew that!”
Nearly 25 years have passed since I was in that elevator. Behind me stands a long academic research career and a more recent foray into applied research, namely in the form of UX (User Experience) or User Research in tech companies.
A common lament from researchers is that their stakeholders (usually designers, product managers, but also other roles at tech companies) are unimpressed when research turns up something previously known. For example: Your research uncovers a particular challenge users face when onboarding to your product. Or you discover some notable pain points on the user journey. Whatever it is, when you share your findings your stakeholders seem let down. “Tell us something new and exciting,” they say. “We already knew that.”
We knew this all along - or did we? Steve Portigal recently created a video about hindsight bias, or what’s also called “knew it all along” effect. This is our tendency to look back at an event and think the outcome was easily predictable. The advice Steve mentions is to ask: “If you already knew that, why hasn’t the product changed? Why does the issue still persist?”
The joy of validation
But let’s take a step back. Let’s give those stakeholders the benefit of the doubt. Say they did already “know that.” We’ve tested an assumption, and it’s correct. Now isn’t that just the most wonderful thing in the world - you were right!
Not only have you validated your assumption through research, but this process has resulted in a reduction of risk. You can make a more confident decision. Isn’t that a great feeling?
Generating theory is key to scientific inquiry. But so are validating and even falsifying theory. Although validating an assumption about user behavior in the tech world may be a radically different environment than an informal psychology experiment at a university, the principal remains the same: research isn’t just about uncovering shiny new objects. It’s about becoming more certain about what we already know.
From an elevator to the digital product world
Deep in the terminology, rhythms, and culture of the tech world, where digital products come to life and occasionally make billions, we can forget that we are creating solutions for people’s problems. Those people sometimes behave in predictable ways, and we can draw on that knowledge to improve our products.
My joy of validating what was already known began in an undergraduate psych course. Maybe yours can start the next time a researcher tells you that your assumption was correct.
