The Paradox of Our Mind’s Averaging of Environmental Data — A TEDx Naqshejahan Experiment
Imagine someone hands you the registration data for about 300 attendees of an event and asks, ‘Tell us what interesting insights you can find in this.’ What would you do?
That was exactly the request I received from Mohammad Zahedi, the organizer of TEDx Naghshe-Jahan (now rebranded as TEDx Esfahan). It felt a bit like being given half a kilo of tomatoes and being told to produce a whole kilo of tomato paste — enough to cook dinner for 300 people at an extravagant party!
It certainly wasn’t a proposal I could easily turn down. So, for several weeks, day and night — at home, at work, lying in bed, even in the shower — my mind was constantly churning, searching for an idea worthy of presenting on the TEDx stage. I pored over the data countless times, hoping that if I looked hard enough, the data itself would speak to me. But with large datasets, it often takes some effort to extract meaningful and impactful stories.
You might find it cliché to hear, but it was actually in the shower one day that I had my ‘aha!’ moment. Over those three weeks, there was really just one thing I kept wrestling with: the average. I was averaging the participants’ ages, their gender distribution, registration times, fees paid, and so on. But that was pretty much it — the data didn’t offer much more.
The core idea that gradually took shape in my mind was to focus on the very concept of averaging, and to highlight the pitfalls this widely-used tool can create in our lives. The average is a statistical instrument that lets us condense a scattered set of data into a meaningful single value — a metric that supposedly represents them all. That’s the standard, almost instinctive definition of average, and it’s hard to find a facet of modern life where some form of averaging isn’t at play.
What’s particularly fascinating is that our brains, too, rely heavily on the concept of averages in many cognitive processes. From the way our visual system perceives colors (often sensing an average of hues) to how we remember people or events (storing and recalling an average impression rather than each detail), our minds are constantly summarizing. This is the very process I tried to explore in my talk, and to demonstrate just how misleading — even erroneous — it can sometimes be.
It was, in fact, my experience collaborating with various companies on data analysis that made me question my trust in this age-old, powerful tool. Averages come with a host of issues, which I touched on in my TEDx talk, aiming to shed light on the subtle but profound impact this mental shortcut has on how we experience and interpret life.
Nobody Is Average — and the Average Is Nobody
The central point of my talk (you can watch it on TED or YouTube in Persian) was that ‘nobody is average and average is nobody.’ By taking averages — especially when it comes to qualitative, human-centric data — we end up hiding the richness of all those individual details, relying on a summary value that matches none of the real data points.
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This mental miscalculation can create cognitive and emotional tension. But why does this happen? Why does our brain, with its unique ability to average, sometimes blunder so dramatically? That’s the question I set out to answer, though I won’t rehash my entire talk here — I’d rather encourage you to watch it instead. However, I’d like to share an interesting experiment we conducted while preparing the talk, in collaboration with the TEDx organizers.
Testing the ability of participants’ minds to average and discover a contradiction in it
To back up the main idea of my presentation, I needed a real-life experiment with real people to show that, in some scenarios, our brains are actually quite poor at averaging. And what better community for this experiment than the TEDx attendees themselves? We designed a short form with four questions, and — thanks to the organizers — emailed it to all registered participants at TEDx Esfahan. Of course not everyone responded, but we had a statistically sufficient sample to draw some basic conclusions.
My central hypothesis proposes a contradictory function of the brain when mentally averaging external data. It performs with high accuracy under one set of conditions, yet with significant inaccuracy under another.
Our brains tend to be extremely precise at averaging quantitative data from our environment, but when it comes to qualitative questions, accuracy drops dramatically. To test this hypothesis, we developed two sets of questions. In the first set, people were asked to estimate what they thought the average weight and average happiness level were among other TEDx attendees. In the second set, participants reported their own actual data — so we could use both sets for comparison. The two data points were: the participants’ own weight (a clear, quantitative metric) and their self-reported satisfaction or happiness level (a more qualitative variable). The questions were:
Set One: Guess the averages
- On average, how many out of ten TEDx NaghsheJahan participants report feeling happy in their lives?
- What do you estimate is the average weight (in kilograms) of TEDx Naghshe Jahan participants?
Set Two: Share your actual data
- Do you feel happy in your life?
- How much do you weigh?
I hope the distinction between these questions is clear. The first asks people to estimate the average of a real dataset, while the second gathers the real numbers, allowing us to directly compare perceived versus actual averages and see how well people’s instincts line up with reality.
The results were pretty much as I expected
Let’s look at the first question: people’s weight. The true average weight was 72.5 kg, while participants’ estimated average was 72.3 kg — an error margin of just 0.3%. That’s remarkably precise! Our brains are clearly capable of making very accurate predictions about well-understood, quantitative measures like weight, possibly because we have a shared, universal understanding of what weight means — and perhaps because our brains evolved to handle these kinds of tangible metrics.
But when it came to the qualitative variable, the results were strikingly different. On average, 79% of participants said they felt happy in their lives, while their estimate of the happiness of others was just 52% — a staggering 34% gap. That might seem like a reasonable error for a guess, but compared to the accuracy with weight, it highlights an intriguing weakness in our brain’s ability to average qualitative information.
What does this simple experiment show? An unskilled brain in averaging
First, our minds are equipped with a highly precise mathematical tool and often leverage averaging as part of their processing power.
Second, while we’re highly accurate at averaging quantitative metrics like weight, we’re almost hopelessly off the mark with qualitative traits like happiness.
This report is a rundown of the experiment we designed as a proof point for my talk’s central idea. As for how this experiment relates to the concept that ‘nobody is average, and average is nobody,’ I invite you to watch the video for the full story.
You can view the presentation slides on Google Slides.
