Amir Afshar

Tolerance is key to the way we build our surroundings.  This extra room is intrinsic to our ability to navigate through space safely. The promise of the future is something different, an efficient city powered by machines.  Could a built environment devoid of human error allow the city to reclaim space? How would our cities change with the advent of automation ?

The Origins of Average : Average as Ideal

As an astronomer in the early 1800s, Adolphe Quetelet was one of the few people that used the system of averaging we know today.  At the time, telescopes were very inaccurate and so when measuring the orbits of planets, astronomers would mark down perceived movements on thin glass plates beside them as they stared up into the sky. They would then divide the sum of all the marks by the number of marks and use this average as their result. Their method was the only way that astronomers mitigated for the errors of their equipment. Enthralled by the possibilities of statistics, Quetelet began to apply the same logic elsewhere, outside the realms of astronomy; to people.

Having come across a dataset of the chest sizes of 5000 Scottish Soldiers, Quetelet applied the same averaging method and found that the average chest size was 39 and ¾ inches.  For Quetelet this did not just represent the average chest size however, it represented the “true” chest size of a Scottish soldier.  He believed that in people, this figure represented less of an average and more of a Platonic Ideal.

Unlike the rotation of the planets, Quetelet believed that human averages carried with them an intrinsic moral mandate ; if everyone were optimally fed and lived under the same environmental conditions, surely they would achieve the average. Furthermore, he stated, it was the duty of society to strive for the continual improvement of the average of the group.

Quetelet went on to apply his methods to other data sets and in so doing highlight further patterns in society.  From marriages to suicides, his findings cast doubt on what people had considered free will and this lead to questions around whether there could be “laws of society” much like “laws of physics”.

The Myth Of The Average Person

Several decades later and after numerous losses to the Confederacy, Abraham Lincoln ordered the Civil War Study.  Adhering strictly to Quetelet’s principles, Lincoln gathered data from his men and used it to form as many averages he could, enabling his army to ration food, design weapons and even determine custom uniform sizes. The Civil War Study became the basis of standardization and mass production in the US military and in 1926, the first airplane cockpit was designed based on the dimensions of the average man as determined by the study.  By the end of WW2, the US Army had begun recruiting hundreds more pilots but with this had come an unprecedented increase in the number of accidents and deaths.  For many years the reasons for this increase in fatalities remained a mystery and eventually it was decided that the 1920s cockpit must’ve been too small and that a new average should be taken. Gilbert S Daniels was appointed to the task. While conducting his research into the new 1950s average male, Daniels measured thousands of airmen on 10 critical physical dimensions. Not a single one of them fit all 10 dimensions of the “average male”. Daniels realised that by designing for the average dimensions, the army had in fact been designing for no one. As a result of his discovery, military engineers redesigned cockpits so that everything was adjustable, allowing for much more flexibility in size.  In turn, pilot performance improved and fatalities were reduced.

What had become clear was that design could not be based around an “average person”, but had to be able to accommodate people outside the average because in the end, no one is really average..

A Loose-Fit City

The notion of the average also informs the way that our cities are designed.  No one walks, drives or indeed navigates space in quite the same way and allowances are factored into the urban fabric to absorb this range.  Within the streetscape, there are a multitude of spaces of transient occupation, moments of tolerance designed to allow for the performance variability between users of the city.  The dimensions of a car lane for example, determined by the DVLA, leave space either side of the vehicles that pass through it.  Driving down the lane, vehicles swerve right 5 and left, touching and returning.. Or the pavement, the delineation between vehicle and human; first introduced as a counter to the Great Manure Crisis of 1894, today span often wider distances and remain elevated, sometimes even with the addition of bollards.  These safety mechanisms embedded in the fabric of our surroundings act as a reminder of our lack of repeatability in tasks.  They highlight our intrinsic flaws; invisible signs of human error.

The Promise Of Precision

Automation is upon us and brings with it the possibility of ultimate precision. AI and machine vision are advancing to such a degree that they are not only beginning to match human capability but indeed to exceed it.  As human unpredictability is removed from jobs and machines take over, repeatability can be introduced where it could not be before. Subsequently, spaces can begin to be determined by the dimensions needed and need no longer absorb the slack of human error.  With these rapid advances in technology, the city too will be able to reclaim space, ‘a little here, a little there’.  As the space adds up, it will become clear that there was a huge amount of space set aside for our unpredictability. Once transient neglected spaces, will these modern day gores become valuable real estate in an ever intensifying urban fabric?

Will they accommodate the programmes associated with the technology; drone ports for last mile delivery or drive-thru arcades for self-driving vehicles? Or will they simply cater to the ever growing population, changing the layout and density of our cities? Crucially, what new architectural typologies emerge as we take back these idiosyncratic spaces and transition into an age of precision?


1. Machine vision algorithm output. SegNet, 2016.
2.  Automated street marking. Unknown.
3. Dream Life Of Driverless Cars (still). ScanLAB, 2015.
4. HumanScale 1,2,3. Niels Diffrient, 1973.
5. The Space Between. Author’s own, 2016.
6. Union Army uniforms. War of the Rebellion Atlas, 1895.