There is No Such Thing as Average Body Size

Below is a very powerful excerpt on why an “average body type” or “average body size” does not exist, taken from Todd Rose’s The End of Average: How We Succeed in a World That Values Sameness:

endofaverage

The End of Average

In the late 1940s, the United States air force had a serious problem: its pilots could not keep control of their planes. Although this was the dawn of jet-powered aviation and the planes were faster and more complicated to fly, the problems were so frequent and involved so many different aircraft that the air force had an alarming, life-or-death mystery on its hands. “It was a difficult time to be flying,” one retired airman told me. “You never knew if you were going to end up in the dirt.” At its worst point, 17 pilots crashed in a single day.

The two government designations for these noncombat mishaps were incidents and accidents, and they ranged from unintended dives and bungled landings to aircraft-obliterating fatalities. At first, the military brass pinned the blame on the men in the cockpits, citing “pilot error” as the most common reason in crash reports. This judgment certainly seemed reasonable, since the planes themselves seldom malfunctioned. Engineers confirmed this time and again, testing the mechanics and electronics of the planes and finding no defects. Pilots, too, were baffled. The only thing they knew for sure was that their piloting skills were not the cause of the problem. If it wasn’t human or mechanical error, what was it?

After multiple inquiries ended with no answers, officials turned their attention to the design of the cockpit itself. Back in 1926, when the army was designing its first-ever cockpit, engineers had measured the physical dimensions of hundreds of male pilots (the possibility of female pilots was never a serious consideration), and used this data to standardize the dimensions of the cockpit. For the next three decades, the size and shape of the seat, the distance to the pedals and stick, the height of the windshield, even the shape of the flight helmets were all built to conform to the average dimensions of a 1926 pilot.

Now military engineers began to wonder if the pilots had gotten bigger since 1926. To obtain an updated assessment of pilot dimensions, the air force authorized the largest study of pilots that had ever been undertaken. In 1950, researchers at Wright Air Force Base in Ohio measured more than 4,000 pilots on 140 dimensions of size, including thumb length, crotch height, and the distance from a pilot’s eye to his ear, and then calculated the average for each of these dimensions. Everyone believed this improved calculation of the average pilot would lead to a better-fitting cockpit and reduce the number of crashes — or almost everyone. One newly hired 23-year-old scientist had doubts.

Lt. Gilbert S. Daniels was not the kind of person you would normally associate with the testosterone-drenched culture of aerial combat. He was slender and wore glasses. He liked flowers and landscaping and in high school was president of the Botanical Garden Club. When he joined the Aero Medical Laboratory at Wright Air Force Base straight out of college, he had never even been in a plane before. But it didn’t matter. As a junior researcher, his job was to measure pilots’ limbs with a tape measure.

It was not the first time Daniels had measured the human body. The Aero Medical Laboratory hired Daniels because he had majored in physical anthropology, a field that specialized in the anatomy of humans, as an undergraduate at Harvard. During the first half of the 20th century, this field focused heavily on trying to classify the personalities of groups of people according to their average body shapes — a practice known as “typing.” For example, many physical anthropologists believed a short and heavy body was indicative of a merry and fun-loving personality, while receding hairlines and fleshy lips reflected a “criminal type.”

Daniels was not interested in typing, however. Instead, his undergraduate thesis consisted of a rather plodding comparison of the shape of 250 male Harvard students’ hands. The students Daniels examined were from very similar ethnic and socio-cultural backgrounds (namely, white and wealthy), but, unexpectedly, their hands were not similar at all. Even more surprising, when Daniels averaged all his data, the average hand did not resemble any individual’s measurements. There was no such thing as an average hand size. “When I left Harvard, it was clear to me that if you wanted to design something for an individual human being, the average was completely useless,” Daniels told me.

So when the air force put him to work measuring pilots, Daniels harboured a private conviction about averages that rejected almost a century of military design philosophy. As he sat in the Aero Medical Laboratory measuring hands, legs, waists and foreheads, he kept asking himself the same question in his head: How many pilots really were average?

He decided to find out. Using the size data he had gathered from 4,063 pilots, Daniels calculated the average of the 10 physical dimensions believed to be most relevant for design, including height, chest circumference and sleeve length. These formed the dimensions of the “average pilot,” which Daniels generously defined as someone whose measurements were within the middle 30 per cent of the range of values for each dimension. So, for example, even though the precise average height from the data was five foot nine, he defined the height of the “average pilot” as ranging from five-seven to five-11. Next, Daniels compared each individual pilot, one by one, to the average pilot.

Before he crunched his numbers, the consensus among his fellow air force researchers was that the vast majority of pilots would be within the average range on most dimensions. After all, these pilots had already been pre-selected because they appeared to be average sized. (If you were, say, six foot seven, you would never have been recruited in the first place.) The scientists also expected that a sizable number of pilots would be within the average range on all 10 dimensions. But even Daniels was stunned when he tabulated the actual number.

Zero.

Out of 4,063 pilots, not a single airman fit within the average range on all 10 dimensions. One pilot might have a longer-than-average arm length, but a shorter-than-average leg length. Another pilot might have a big chest but small hips. Even more astonishing, Daniels discovered that if you picked out just three of the ten dimensions of size — say, neck circumference, thigh circumference and wrist circumference — less than 3.5 per cent of pilots would be average sized on all three dimensions. Daniels’s findings were clear and incontrovertible. There was no such thing as an average pilot. If you’ve designed a cockpit to fit the average pilot, you’ve actually designed it to fit no one.

Daniels’ revelation was the kind of big idea that could have ended one era of basic assumptions about individuality and launched a new one. But even the biggest of ideas requires the correct interpretation. We like to believe that facts speak for themselves, but they most assuredly do not. After all, Gilbert Daniels was not the first person to discover there was no such thing as an average person.

Seven years earlier, the Cleveland Plain Dealer announced on its front page a contest co-sponsored with the Cleveland Health Museum and in association with the Academy of Medicine of Cleveland, the School of Medicine and the Cleveland Board of Education. Winners of the contest would get $100, $50, and $25 war bonds, and 10 additional lucky women would get $10 worth of war stamps. The contest? To submit body dimensions that most closely matched the typical woman, “Norma,” as represented by a statue on display at the Cleveland Health Museum.

Norma was the creation of a well-known gynecologist, Dr. Robert L. Dickinson, and his collaborator Abram Belskie, who sculpted the figure based on size data collected from 15,000 young adult women. Dr. Dickinson was an influential figure in his day: chief of obstetrics and gynecology at the Brooklyn Hospital, president of the American Gynecological Society and chairman of obstetrics at the American Medical Association. He was also an artist — the “Rodin of obstetrics,” as one colleague put it — and throughout his career he used his talents to draw sketches of women, their various sizes and shapes, to study correlations of body types and behaviour.

Like many scientists of his day, Dickinson believed the truth of something could be determined by collecting and averaging a massive amount of data. “Norma” represented such a truth. For Dickinson, the thousands of data points he had averaged revealed insight into a typical woman’s physique — someone normal.

In addition to displaying the sculpture, the Cleveland Health Museum began selling miniature reproductions of Norma, promoting her as the “Ideal Girl,” launching a Norma craze. A notable physical anthropologist argued that Norma’s physique was “a kind of perfection of bodily form,” artists proclaimed her beauty an “excellent standard” and physical education instructors used her as a model for how young women should look, suggesting exercise based on a student’s deviation from the ideal. A preacher even gave a sermon on her presumably normal religious beliefs. By the time the craze had peaked, Norma was featured in Time magazine, in newspaper cartoons, and on an episode of a CBS documentary series, This American Look, where her dimensions were read aloud so the audience could find out if they, too, had a normal body.

On Nov. 23, 1945, the Plain Dealer announced its winner, a slim brunette theatre cashier named Martha Skidmore. The newspaper reported that Skidmore liked to dance, swim, and bowl — in other words, that her tastes were as pleasingly normal as her figure, which was held up as the paragon of the female form.

Before the competition, the judges assumed most entrants’ measurements would be pretty close to the average, and that the contest would come down to a question of millimetres. The reality turned out to be nothing of the sort. Less than 40 of the 3,864 contestants were average size on just five of the nine dimensions and none of the contestants — not even Martha Skidmore — came close on all nine dimensions. Just as Daniels’ study revealed there was no such thing as an average-size pilot, the Norma Look-Alike contest demonstrated that average-size women did not exist either.

But while Daniels and the contest organizers ran up against the same revelation, they came to a markedly different conclusion about its meaning. Most doctors and scientists of the era did not interpret the contest results as evidence that Norma was a misguided ideal. Just the opposite: many concluded that American women, on the whole, were unhealthy and out of shape. One of those critics was the physician Bruno Gebhard, head of the Cleveland Health Museum, who lamented that postwar women were largely unfit to serve in the military, chiding them by insisting “the unfit are both bad producers and bad consumers.” His solution was a greater emphasis on physical fitness.

Daniels’ interpretation was the exact opposite. “The tendency to think in terms of the ‘average man’ is a pitfall into which many persons blunder,” Daniels wrote in 1952. “It is virtually impossible to find an average airman not because of any unique traits in this group but because of the great variability of bodily dimensions which is characteristic of all men.”

Rather than suggesting that people should strive harder to conform to an artificial ideal of normality, Daniels’ analysis led him to a counterintuitive conclusion that serves as the cornerstone of this book: any system designed around the average person is doomed to fail.

Daniels published his findings in a 1952 Air Force Technical Note entitled The “Average Man”?In it, he contended that if the military wanted to improve the performance of its soldiers, including its pilots, it needed to change the design of any environments in which those soldiers were expected to perform. The recommended change was radical: the environments needed to fit the individual rather than the average.

Amazingly — and to their credit — the air force embraced Daniels’ arguments. “The old air force designs were all based on finding pilots who were similar to the average pilot,” Daniels explained to me. “But once we showed them the average pilot was a useless concept, they were able to focus on fitting the cockpit to the individual pilot. That’s when things started getting better.”

By discarding the average as their reference standard, the air force initiated a quantum leap in its design philosophy, centred on a new guiding principle: individual fit. Rather than fitting the individual to the system, the military began fitting the system to the individual. In short order, the air force demanded that all cockpits needed to fit pilots whose measurements fell within the 5-per-cent to 95-per-cent range on each dimension.

When airplane manufacturers first heard this new mandate, they balked, insisting it would be too expensive and take years to solve the relevant engineering problems. But the military refused to budge, and then — to everyone’s surprise — aeronautical engineers rather quickly came up with solutions that were both cheap and easy to implement. They designed adjustable seats, technology now standard in all automobiles. They created adjustable foot pedals. They developed adjustable helmet straps and flight suits.

Once these and other design solutions were put into place, pilot performance soared, and the U.S. air force became the most dominant air force on the planet. Soon, every branch of the American military published guides decreeing that equipment should fit a wide range of body sizes, instead of standardized around the average.

Why was the military willing to make such a radical change so quickly? Because changing the system was not an intellectual exercise — it was a practical solution to an urgent problem. When pilots flying faster than the speed of sound were required to perform tough manoeuvres using a complex array of controls, they couldn’t afford to have a gauge just out of view or a switch barely out of reach. In a setting where split-second decisions meant the difference between life and death, pilots were forced to perform in an environment that was already stacked against them.

Apple’s Pivot: Project Titan

Neil Cybart, the author of the Above Avalon blog, pens the most compelling piece that I have read to date about Apple’s next big thing: Project Titan–“a start-up” within Apple focused on the electric car industry.

Meanwhile, Tim Cook has remained very tight-lipped about Apple’s future, which gives the impression that Apple isn’t working on ground-breaking ideas or products that can move the company beyond the iPhone. Instead of labeling this as a mistake or misstep, Apple’s product secrecy is a key ingredient of its success. People like to be surprised. Another reason Apple takes a much different approach to product secrecy and R&D is its business model. Being open about future product plans will likely have a negative impact on near-term Apple hardware sales. Companies like Facebook and Google don’t suffer from a similar risk. The end result is that there is a legitimate disconnect between Apple’s R&D trends and the consensus view of the company’s product pipeline. Apple is telling us that they are working on something very big, and yet no one seems to notice or care.

The increased R&D spending by Apple over the last couple of years is very telling:

Apple is not spending $10 billion on R&D just to come up with new Watch bands, larger iPads, or a video streaming service. Instead, Apple is planning on something much bigger: a pivot into the automobile industry. 

The word “pivot” has become a buzzword lately, often misused to simply mean change. In reality, pivoting is actually a sign of strength as a company takes what it learns from one business model in one market and applies it a new one with a different business model. Apple would be taking lessons learned from its long-standing view on the world based on the Mac, iPod, and broader iOS lineup to begin selling an electric car.

This sounds incredibly ambitious and bold, and that is the point. Apple wants to move beyond the iPhone. In this regard, pivot seems like the wrong word to use since the iPhone is a very successful product generating more cash flows than the rest of Apple’s product line put together times two. However, it is this success that ultimately serves as the greatest motivation for Apple management to figure out the next big thing.

If you’re at all interested in Apple and the future product pipeline, I highly recommend reading “Apple R&D Reveals a Pivot is Coming.”

On NYC’s Open Data Portal and Parking Tickets

The author of the I Quant NY blog profiles an excellent use of of NYC’s Open Data portal in a post detailing how the city has been systematically ticketing legally parked cars:

As of late 2008, in NYC you can park in front of a sidewalk pedestrian ramp, as long as it’s not connected to a crosswalk.  It’s all written up in the NYC Traffic Rules, and for more detail, take a look at this article.

Is it a problem that drivers don’t realize that there are some extra parking spots they are now allowed to park in?  Not so much.  But, I’ve got a pedestrian ramp leading to nowhere particular in the middle of my block in Brooklyn, and on occasion I have parked there.  Despite the fact that it is legal, I’ve been ticketed for parking there.  Though I get the tickets dismissed, it’s a waste of everybody’s time. And that got me wondering- How common is it for the police to give tickets to cars legally parked in front of pedestrian ramps?  It couldn’t be just me…

In the past, there was not much you could do to stop something like this. Complaining to your local precinct would at best only solve the problem locally.  But thanks to NYC’s Open Data portal, I was able to look at the most common parking spots in the City where cars were ticketed for blocking pedestrian ramps.   It’s worth taking a moment upfront here to praise the NYPD for offering this dataset to begin with.  Though we are behind on police crime data in the city, we are ahead in other ways and the parking ticket dataset is definitely one of them.  

The response from the NYPD that the author received speaks volume (an admission of mistake and a promise to get it right with the proper training):

Mr. Wellington’s analysis identified errors the department made in issuing parking summonses. It appears to be a misunderstanding by officers on patrol of a recent, abstruse change in the parking rules.  We appreciate Mr. Wellington bringing this anomaly to our attention.

The department’s internal analysis found that patrol officers who are unfamiliar with the change have observed vehicles parked in front of pedestrian ramps and issued a summons in error. When the rule changed in 2009 to allow for certain pedestrian ramps to be blocked by parked vehicles, the department focused training on traffic agents, who write the majority of summonses.

Yet, the majority of summonses written for this code violation were written by police officers. As a result, the department sent a training message to all officers clarifying the rule change and has communicated to commanders of precincts with the highest number of summonses, informing them of the issues within their command.

Thanks to this analysis and the availability of this open data, the department is also taking steps to digitally monitor these types of summonses to ensure that they are being issued correctly.

Worth reading in entirety here.

On the 30 Year Anniversary of the Chernobyl Disaster

Today marks the 30th anniversary since the Chernobyl nuclear power plant explosion on April 26, 1986 in Ukraine.

Over the last couple of weeks, I’ve watched a few documentaries that do an excellent job summarizing how the disaster unfolded, the impact the disaster has had on the population of Ukraine and Belarus (as well as other world regions impacted by the nuclear fallout), and the still-ongoing efforts to contain the spread of the radioactivity.

The three documentaries I recommend are below. First, The Battle of Chernobyl (incorrectly titled as “Chernobyl Uncensored” in one YouTube video) is a 2006 documentary (approximately one and a half hours in length) that stars Mikhail Gorbachev, former president of the U.S.S.R., providing excellent commentary throughout:

Second, the documentary Zero Hour creates a minute-by-minute breakdown of the accident at Reactor #4 at Chernobyl (from about an hour before the accident to approximately 48 hours after the accident):

 

Finally, the documentary Chernobyl 3828 is perhaps the most poignant of the documentaries, profiling the 3828 human workers (who came to be known as liquidators or “bio-robots”) that were sent into the most radioactive zone—the roof of the reactor #4—in September 1986 to finish cleaning up the radioactive waste before the sarcophagus over the reactor could be built. There was such high levels of radioactivity in this area that robots sent from Western Europe had their electronics fried in less than 48 hours. The clean-up effort, nevertheless, had to go on—and these bio-robots would sacrifice themselves for the greater cause. These workers received the most lethal doses of the radiation (background radiation of ~8,000 Roentgens), and what is agonizing to watch is the struggle the commander of the operation has to face, knowing that he is ultimately sending these men to their early deaths. The narrator of the documentary, Valeriy Starodumov, worked as a dosimeter scout at the Chernobyl clean-up site; in the documentary, he trains and takes the soldiers to the zone of the highest contamination. And so, a conveyor of bio-robots begins, and Starodumov narrates:

I will take a few hundred people through the zone. I will not know who they are, I will not see their faces behind protective masks and I will never know what is going to happen to them afterwards. It was not me who had made a decision to send these men to the zones of mortal danger, but each night some inexplicable feeling of guilt brings me back to the past. To that first two-minute shift, which has been continues for me for a quarter of century…

 

 

The NFL Schedule is a Massive Optimization Problem

This is a fascinating Los Angeles Times piece that profiles the computing power that is required to generate the NFL schedule. A team of four members and hundreds of computers are used to sift through 26,000+ conditions, with trillions of possible permutations, to generate the 2016 NFL schedule:

With 256 games, 17 weeks, six time slots, five networks and four possible game days — Sunday, Monday, Thursday and Saturday — there are hundreds of trillions of potential schedule combinations. Katz and his team are searching for the single best, and they have as many as 255 computers around the world running 24/7 to find the closest possible match to the ideal slate of games.

The schedules that have come out in the last couple of years are much more sophisticated:

Among the scheduling elements that are factored in now, but were not deeply considered in the old days: How much is a team traveling, and how far? Is someone playing a road game against a team coming off its bye week? Is anyone playing a road game six days after being on the road on a Monday night? Is a club overloaded with consecutive opponents who made the playoffs the previous season? Has a team gone multiple seasons with its bye at Week 5 or earlier?

An incredible optimization problem. The ultimate schedule that was selected was hand-judged against 333 other schedules generated by the computers to make sure it was the most optimal schedule.

Read the rest here. Here is the 2016 NFL schedule.

On the Minecraft Phenomenon

Clive Thompson, writing in The New York Times, profiles the gaming phenomenon that is Minecraft. It’s a really interesting read on the appeal of the game for both children and adults:

Minecraft is thus an almost perfect game for our current educational moment, in which policy makers are eager to increase kids’ interest in the “STEM” disciplines — science, technology, engineering and math. Schools and governments have spent millions on “let’s get kids coding” initiatives, yet it may well be that Minecraft’s impact will be greater. This is particularly striking given that the game was not designed with any educational purpose in mind.

 On how the game teaches kids autonomy, negotiation, and empathy:

But Minecraft is unusual because Microsoft doesn’t control all the servers where players gather online. There is no single Minecraft server that everyone around the world logs onto. Sometimes kids log onto a for-­profit server to play mini­games; sometimes they rent a server for themselves and their friends. (Microsoft and Mojang run one such rental service.) Or sometimes they do it free at home: If you and I are in the same room and we both have tablets running Minecraft, I can invite you into my Minecraft world through Wi-Fi.

What this means is that kids are constantly negotiating what are, at heart, questions of governance. Will their world be a free-for-all, in which everyone can create and destroy everything? What happens if someone breaks the rules? Should they, like London, employ plug-ins to prevent damage, in effect using software to enforce property rights? There are now hundreds of such governance plug-ins.

Worth clicking through to see the illustrations done by Christoph Niemann.

The Difference between Affluent, Rich, and Super-Rich

One of the best things I’ve read this week is Ben Casnocha’s blog post titled “The Goldilocks Theory of Being Rich” on what it means to be rich. In the post, Ben correctly posits that today there’s a very small difference between the rich and the American middle class in terms of quality of life. In the post, Ben differentiates among affluent, rich, and the super-rich…

The actual best part about being super rich, as far as I can tell, is this: You’re more likely to feel like you led a life of meaning. You might not be happy all the time or most of the time, but you will feel like your time on this earth counted for something. One way to distinguish happiness from meaning is that happiness is the day to day bounce of emotions while meaning is what you feel when you step back, take a minute, and reflect on what will go in your obituary. (Here’s my post on meaning vs. happiness.)

How so? The feeling of meaning and making a difference manifests in real, concrete ways. Someone like Meg Whitman can walk the HP campus and see thousands of employees who support their families thanks to employment at HP; she can read stories about the millions of people who use HP products every day to be better at their job. That imbues her life with a sense that her life matters. If you don’t have a corporate campus to walk around—if, for example, you’re an options trader and not a builder of things—fear not. With a supple bank account, you can still take actions that generate meaning. Write big checks to charity and you’ll get thank you notes from the children at the public school you helped. You’ll get enough feel-good ooze from your charitable giving to last you a lifetime. Entrepreneur and billionaire Marc Benioff has said, “Nothing is going to make you feel better. Philanthropy is absolutely the best drug I’ve ever taken.”

I liked this analogy posited by Tim O’Reilly:

…money is like gasoline while driving. You never want to run out, but the point of life is not to go on a tour of gas stations.

The distinction between affluent, rich, and super-rich:

Maybe wealth needs its own Goldilocks porridge story: you want not too much, not too little. And I think that ideal middle ground is the “Rich” category in the hierarchy I opened with. More crudely, this ideal amount of money is termed “fuck-you money.” With fuck you money, you can’t fly around the world on a private jet (so you’re not as rich as the Super Rich) but do you have the power to say fuck you to essentially anyone or anything that doesn’t interest you (which means you’re richer than the merely affluent).

Put another way, if you work on stuff that doesn’t excite you for more than one day a week, in my estimation you do not have fuck-you money. You’re still working for the man. At the other end of the spectrum, if you find yourself being invited to more than a few charity galas a year, worrying about physical and cyber security at your home, and asking a PR person to review your public statements, you have a lot more than fuck-you money and all the corresponding drawbacks.

Definitely worth reading this thought-provoking post in its entirety.