People are Just as Weird and Poor as Ever —Just Not on Chip Heath or Adam Mastroianni's Feeds
The epistemological blindness of tenure
Dearest reader - A few weeks ago, I shared a note that while writing MAKING NUMBERS COUNT with Chip Heath, it became very clear that we were living in different realities. He was a long-time tenured professor who charged $ for workshops in addition to the millions he made from his books; I was—and remain!—an unaffiliated freelance writer. When discussing the advance for MNC with his literary agent, she reminded me “you know, this isn’t a lot of money to him.” You know, the life-changing money that let me buy a house.
Data, Data Everywhere
Chip suggested that we write about saving $1,000 a month in your 20s as the ultimate retirement hack.1 In addition to being chump change to a guy like him, it was a no-brainer of a Great Idea to pass along. He had data. Alas, all measures of the economy are incomplete: stock market indices measure the wealth of companies, not people. Median and mean income say nothing about affordability, living expenses, or how many people are trying to live off of that wage. The GDP doesn’t measure unpaid work—the domestic economy—which includes the things that people need to do to survive.
The brain has two main needs: conserve energy (including its own usage!) and accomplish its goals. Given these biological constraints, thinking is costly; uncertainty is uncomfortable; rewards and relief matter. At some point, we need to stop refining the model and get on with things.2
So, consider this: even on a millisecond-by-millisecond basis, our brain is lazy. We like information that’s easy to process—things that feel true and sound right—and are less skeptical of what confirms our beliefs. Confirmation bias isn’t just motivated reasoning—it’s energy-efficient, and affects our attention and perception.3
Disconfirming evidence requires more work—it threatens our coherent view of ourselves and the world—so we avoid it.
We say things like “There’s no way of randomly sampling all of society and objectively measuring its deviance over time. The data we don’t have might contradict the data we do have. But it would have to be a lot of data, and it would all have to point in the opposite direction.”
It’s easier to ignore a single piece of information than it is to turn our world upside down.
Our brain processes ideas that align with our existing beliefs, social identity, or self-concept more fluently—and that makes them feel more credible. And don’t forget, we’re the über-social animal whose brain evolved to live in caves and eat berries with our tribe, which is why other people’s input is what makes something objective.4
Tenure creates a predictable information ecosystem & worldview
Back to the save $1,000 hack: Chip wasn’t just looking at data, he was getting his information from lived experience—and yes, he knew a lot of people from different backgrounds… but they had all ended up at Stanford. Bestselling authors. Professors. Heads of tech companies. People who were honored to be in his presence, and therefore affable. Affluent neighbors.
Tenured professors are very far removed from the lived experience of what it’s like to be an “average” American: they have a sense of economic stability, strong ties to an untold number of well-connected people, and are held in high regard by the general population—even if their internal monologue still squeaks “NERD!!!” on occasion.
Humans are amazingly adaptable, our brains ever-shifting in response to conditions and experiences, and my life has probably shaped my brain into the opposite of a tenured professor: I understand what it’s like to have a fundamental sense of instability, to have one’s worldview shaped by a parent with mental illness, to be isolated, ignored, and told that I should “aim lower.” (I was deeply in debt and living with two roommates in Queens when we began working together.)
I felt like I had to code-switch, while working with Chip, whose worldview and information were all coming from data.
To him, a white guy with tenure born in 1963, there was nothing wrong with all of the data. But median and mean income don’t take expenses into consideration. Qualitative information matters; polls matter. But economic data—like all data that most professors deem up-to-snuff—reflects the system of measurement. That apparatus was built decades ago, by universities, government agencies, demographers, and sociologists—mostly male, mostly white, mostly middle-class, mostly WEIRD (in the anthropological sense). They measured what they thought mattered. They measured what they could measure.
“All models are wrong, but some are useful.” - George Box
Epistemic Blindness: You Don’t Know What You Don’t Know
“How would someone in their 20s actually save $1,000 a month?” I asked, before making a spreadsheet to deduct taxes and tally rent, health care, prescriptions, water, electricity/gas, internet, fuel, phone, car payments, car insurance, parking, food, random household items, subscriptions, etc., etc. Chip also hadn’t factored in how much student loan payments would be for the recently-graduated—the very tuition that paid his salary. His estimates were off for everything.
I did the math. I looked up the price of all the things. I showed my work.
And it made him so uncomfortable that he stopped me.
The “save $1,000 a month, it’s easy” story is prelude for what Adam Mastroianni got wrong in his viral “The Decline of Deviance” essay. Lookie at this subtitle:
1. Data is Necessarily Incomplete
Data from every sector of society is pointing strongly in the same direction: we’re in a recession of mischief, a crisis of conventionality, and an epidemic of the mundane.
As someone who was chronically offline for the past few years, THERE ARE PLENTY OF WEIRD DEVIANTS EVERYWHERE. Data is not divine. I say this after a few years of doing workshops on data storytelling and consulting—as someone who wrote a book on data—and reading amazing books like Invisible Women and all about the cultural history of numbers and the scientific process. We think that wisdom is connecting the dots of data:
And yet! The best magic trick that data plays—and frequently—is to convince us of a piece of information’s superiority and objectivity. But the very act of collecting data is an act of omission and curation, of boiling life down to something that can be counted. What we deem worthy of measuring says a lot more about the perspectives and incentives of those doing the measuring than reality itself. Reality contains an overwhelming amount of data, and we overemphasize the aspects of it that are easily measurable or quantifiable:
2. You can’t use longitudinal data to measure CURRENT weirdness
When you only write about data that has been tracked by legacy institutions over decades, you automatically focus on aspects of life that were measured by those not-representative-of-most-people-people decades ago: mostly WEIRD. Mostly men in government or academic jobs. We don’t have cults today, but we have the Flat Earth movement and the Manosphere and MLMs. Serial killers? Down, yes, sure. Doxxing, identity theft, revenge porn—all up from zero.
3. Accessibility Can Look Like Conformity
“The internet ain’t interesting anymore,” says Adam. For my first book, I interviewed Derek Sivers, who sold his company CD Baby for $25 million.
In 1993, when Sivers’ roommate—a multimedia studies major at New York University—mentioned the Internet, Sivers’ curiosity flared up yet again. “But of course right away I wanted to figure out how to make ‘World Wide Web’ pages of my own... there wasn’t much to it. Even though I had no computer experience at the time, making basic HTML tags was really no harder than making a Word document,” he says.
Sivers was a pioneer in the internet’s early halcyon days, when its relative difficulty of use required you to be a bit of a genuine nerd to be online at all; there were no spambots or marketing Ponzi schemes to sully the entire notion of leaving links, just a bunch of well-intentioned nerds with stuff to share.
The early-days internet seemed more interesting because websites were individual passion projects by the technologically-minded; today, the act of publishing a website has been relatively democratized: all you need is a template!
To reach as broad of an audience as possible, companies need to follow inclusive design principles, since people with accessibility needs need to reach the same information. Think: low-bandwidth (mobile-friendly; non-speedy internet-friendly); reader-accessible (vision-impaired); easy to navigate (neurodivergent); easy to translate.
4. Mostly, it’s about money & bandwidth
Mostly, the post reminded me of the difference that having money makes on one’s worldview—and how much tenure blinds you to the reality of most people.
Why aren’t people doing drugs? Maybe young people aren’t drinking or doing drugs as much today—it’s expensive, they’re poor, and there’s a real lack of third spaces. They’re more aware of the health effects because of parental drug abuse. I’m a former 12-stepper currently in Oregon, where psilocybin mushrooms are legal-ish5, so likely have a weird view of it all.
Weirdness on LinkedIn? We don’t want to post something that would get us fired. Weirdness on Instagram? It’s there, but it’s not on the popular feeds. That’s the point.
People are staying put? People aren’t moving because it’s expensive. [And since when did “moving” become deviant? ]
No one would ever be able to replicate this, says Adam. “The sculptor Arturo di Modica ran away from his home in Sicily to go study art in Florence. He later immigrated to the US, working as a mechanic and a hospital technician to support himself while he did his art. Eventually he saved up enough to buy a dilapidated building in lower Manhattan, which he tore it down so he could illegally build his own studio—including two sub-basements—by hand, becoming an underground artist in the literal sense. He refused to work with an art dealer until 2012, when he was in his 70s.
How much do dilapidated buildings in lower Manhattan cost these days? Does Mastroianni know how hard it is to get a job today? What are the odds that a female artist would be able to have this career?
Culture isn’t Flattening—Just Big Budget Culture
He cites an essay in the New York Times Magazine about the flattening of culture. As my friend says: if you want to learn what editors think, read the article; if you want to learn what readers think, read the comments.
Here’s the top comment from that article:
This seems to be ignoring the elephant in the room. What the majority of people experience as art is dictated by institutions (like MOMA) that gatekeep and tend to focus on what they already know will bring people in or is already popular. Having trouble finding artistic innovation there? Try visiting local galleries across the country. Not pleased with a lack of innovation in writing? Remember that agents and publishers tend to pick up what will make them money. Start reading publications by indie presses. The innovation is out there, it is just not supported by the economic side of the arts.
Culture is stagnating
Is culture stagnating? We are seeing a splintering of attention, and consolidation in who controls that diminishing slice of pie that gets dubbed “pop culture.” The Marvel-ization of cinema is because of money. Ergo, we get Netflix shelling out $300 million dollars for drivel because they’re trying to use data to make safe cultural bets.
Algorithms recommend things that are safe and popular. I first studied this in 2006, while a staff writer at Seattle Weekly, researching a cover story on music algorithms. Algorithms want you to click and buy; most of the time it’s better to show you the new Taylor Swift album than a new artist with a 5% chance of you loving it.
We accuse others of confirmation bias, but it happens to us all—and it starts at attention, not just perception. The more we see something (people are making plenty of money; the world is boring), the more likely we are to believe that it’s true, provided we don’t have anyone hitting us in the face with counterfactuals.
Adam writes: “There’s no way of randomly sampling all of society and objectively measuring its deviance over time. The data we don’t have might contradict the data we do have.” Then instantly says: “But it would have to be a lot of data, and it would all have to point in the opposite direction.”
So: counter me, but only if you can produce the impossible?
Don’t just look at the data—look at what the data isn’t counting. (Hint: it’s a lot.)
Don’t just look at what’s on your feed—look at what other people are actually consuming and interacting with.
Here’s what didn’t reach Chip Heath or Adam Mastroianni’s feeds: the world is weird. People are poor. Instead of discovering a huge thing about reality that no one else noticed, you just pointed out your blind spots.
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I value feedback (suggestions, critiques, positive reinforcement, constructive insults, etc.) at hello@kstarr.com. I also give workshops for businesses on my pillar topics.
Karla Starr (@karlastarr) is the coauthor of Making Numbers Count: The Art and Science of Communicating Numbers. Her first book, Can You Learn to Be Lucky? Why Some People Seem to Win More Often Than Others, was a Fast Company book of the year. She also writes The Starr Report, which you are reading the very end of.
A white male professor with tenure born in 1963? THE ULTIMATE RETIREMENT HACK.
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