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Man vs machine – Engineers, not racers, are the true drivers of success in motor sport | Graphic detail | The Economist

Man vs machine
Engineers, not racers, are the true drivers of success in motor sport

Our statistical model finds that neither Lewis Hamilton nor Michael Schumacher is Formula 1’s greatest driverGraphic detailOct 17th 2020 edition


OCT 17TH 2020

https://infographics.economist.com/2020/20201017_GDC100_1/index.html

“I always thought records were there to be broken,” Michael Schumacher, a star Formula 1 (f1) driver, said in 2013. At the time, his record of 91 career f1 victories looked safe: the closest active racer had just 32. Yet on October 11th Lewis Hamilton of Britain equalled the mark. Mr Hamilton is also on pace to tie Mr Schumacher’s record of seven f1 championships later this year.

Mr Hamilton’s ascent has ignited debate over whether he is f1’s best driver ever. Comparing athletes across eras is always hard—especially in motor sports, where a racer depends on his car. Moreover, f1 has regularly changed its scoring system and its number of races, drivers and teams.

However, statistical analysis can address many of these nuances. We have built a mathematical model, based on a study by Andrew Bell of the University of Sheffield, to measure the impact of all 745 drivers in f1 history. It finds that Mr Hamilton’s best years fall just short of those of the all-time greats—but so do Mr Schumacher’s.

The model first converts orders of finish into points, using the 1991-2002 system of ten points for a win and six for second place. It adjusts these scores for structural effects, such as the number and past performances of other drivers in the race. Then, it splits credit between drivers and their vehicles. (Today, f1 has ten teams, each using two drivers and one type of car.)

Disentangling these factors is tricky. Mr Schumacher spent most of his peak at Ferrari, as Mr Hamilton has at Mercedes, leaving scant data on their work in other cars.

However, their teammates varied. And drivers who raced alongside Mr Hamilton or Mr Schumacher tended to fare far better in those stints than they did elsewhere. If Ferrari’s and Mercedes’ engineers boosted lesser racers this much, they probably aided their stars to a similar degree. Because most drivers switch teams a few times, this method can be applied throughout history.

https://infographics.economist.com/2020/20201017_GDC100_2/index.html

Between the two racers with 91 wins, the model prefers Mr Schumacher. He won 1.9 more points per race than an average driver would have done in the same events and cars, edging out Mr Hamilton’s mark of 1.8. Limited to their five best consecutive years, the gap widens, to 2.7 points per race for Mr Schumacher and 2.0 for Mr Hamilton.

This difference stems mostly from the impact of their cars. Both stars raced in the finest vehicles of their day. But 20 years ago, cars from Williams and McLaren were nearly as strong as Ferrari’s. In contrast, Mercedes now towers over its rivals, enabling Mr Hamilton and Valtteri Bottas, his teammate, to coast past lesser cars. Before joining Mercedes, Mr Bottas had never won a f1 race. He now has nine victories.

Yet on a per-race basis, the greats of yesteryear beat both modern stars. Three of the model’s top four drivers stopped racing by 1973; the leader, the Argentine Juan Manuel Fangio, won five titles in the 1950s.

These pioneers had short careers. Fangio started just 51 races, to Mr Schumacher’s 306. However, the model is impressed by them, because the impact of cars relative to drivers has grown over time. On average, it assigns drivers in the 1950s 58% of their teams’ points; today, that share is 19%. Fangio, who was a mechanic by training and won titles using cars from four different firms, was known as “the master”. The masters of modern f1 are engineers who sit behind laptops, not steering wheels. ■

Sources: Ergast.com; F1-Facts.com; “Formula for success: multilevel modelling of Formula 1 driver and constructor performance, 1950-2014”, by Andrew Bell et al., Journal of Quantitative Analysis in Sports, 2016;The Economist

Man vs machine – Engineers, not racers, are the true drivers of success in motor sport | Graphic detail | The Economist

What Do You Miss Most About Touch, During the Pandemic? – The Atlantic

CULTURE

What’s Your Most Important Memory of Touch?

Amid a pandemic that is profoundly decreasing skin-on-skin contact, the author asked people to share their most affecting tactile experiences.KRISTEN RADTKEAPRIL 15, 20203more free articles this monthSign inSubscribe Now

KRISTEN RADTKE
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Only about halfway through the 20th century did American scientists understand that touch was important. Before then, distance was the name of the game. The psychologist John Watson proclaimed that authoritarian parenting sparse on touch was the only way to ensure children would grow into strong, well-adjusted adults. The behavioral scientist B. F. Skinner had his baby daughter sleep and play in a climate-controlled incubator for two years, to help ease the burdens of parenting and to protect her from disease. In orphanages, babies were typically held only while they were fed or bathed. Stringent cleaning routines did cut down on the spread of infection, but no matter how much caretakers scrubbed the cribs, or how much they tried to isolate the children, they found the babies couldn’t kick their colds. Their recovery took longer and longer, if they recovered at all.

We know, now, that touch can influence the immune system and bonds us to one another. But touch is a lot more complicated when much of the world is on lockdown. It’s extremely dangerous for health-care workers, grocery-store workers, and other essential personnel who are not able to stay home. Hugs, back pats, and handshakes already feel like actions a world away. In situations where touch is safe, being intentional with it—utilizing it as we might other supplies we’ve stockpiled—can be essential. For those who are part of a household with other people, thinking about how to receive this necessary touch is “really important, especially [in dealing] with anxiety,” says Melissa A. Fabello, an educator who has studied touch patterns in young women with eating disorders.

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“It’s all about stimulating the response reception in the skin, which leads to a whole physical reaction that slows the nervous system down,” Tiffany Field, the director of the Touch Research Institute, told me. If you’re sheltering alone, Field said, “I’m encouraging people to self-massage, which has the same benefit of activating receptors under your skin. Even just walking around your living room, you’re stimulating the pressure receptors in your feet.”

Thinking about how our relationship with touch might morph amid a pandemic, I asked people to share memories of their most affecting experiences with touch. Their answers demonstrate that many of our most resonant interactions are those we can—literally—feel.


“I used to wash hair at a salon. One woman would moan slightly when I touched her head. She found ways to extend her hair-washing time, which I was already extending because she obviously needed it. One day she told me, ‘My husband is dead and I have no children or grandchildren; you’re the only one who touches me.’”


“There’s this one area of my back on my upper left side, right on the bone, that always itches. I can’t reach it with my own fingers. I’m stubbornly independent, but this itch requires another human hand in order to get relief. And when someone finds the spot (there’s a lot of direction on my end) and scratches it, it is the fiercest, most sincere pleasure. The kind that makes me feel a little in love with whatever hand is at work. Thing is, the more someone scratches, the more intense the itch. Eventually, their hands get tired. And I’m grateful to them for trying, sad they’re gone. The itch might be a nerve-related thing or a dry-skin thing, according to the internet. Honestly, I wonder if my back really itches at all or if I’ve made it up. It’s nice to need a hand, and to miss it.”


“At the end of a 12-step meeting, we stand and grab the hands of strangers or friends on either side of us. Somebody says, “Take us out,” and that means to start a prayer. We pray together, including many of us who don’t believe in God. I feel, always, such gentleness and yet such solid commitment in the way we hold each other. I’ve been at a meeting at least once a week for 26 years, and since we can’t meet in person right now, we’re doing Zoom meetings and phone check-ins. I’m thinking now about the privilege of the circle, how I’ve never worried what was on those hands, and how those palms and fingers saved me.”


“I work with children who are deaf-blind, and I think a lot about one little girl who had developed a lot of self-injurious behaviors, banging and hitting her head constantly. The first time I met her, her teachers and team said that she was very resistant to touch, and would scratch or bite whenever someone approached her. She lay curled up in a ball on a wooden part of the floor, so I sat about four feet away from her and started to rhythmically tap on the floor, pausing every 15 seconds or so. At first, she was startled and curled up tighter, but after a few rounds of this, she started to calm down. I scooted a foot closer and resumed the routine. By the time I got to about a foot from her, she had relaxed completely, and started to explore with her hands. She bumped my knee, and from there found my hand, my arm, and my face. She thought my beard was hilarious, and laughed aloud—the first time her teachers had seen her laugh.”


“When my son died of a drug overdose, everyone kept their distance. For months. Family, friends, even those closest to me were suddenly missing in action and at a loss for words. I felt like a leper—that my grief was somehow contagious. I sat frozen and emotionless in my house, staring at walls for weeks. One afternoon my doorbell rang, and it was a distant friend, someone I barely knew. When I opened the door, she said nothing, but simply wrapped her arms around me. Now, some 16 years later, I remember everything about that moment and how it saved my life.”


“I realized after starting my first sexual relationship—falling asleep spooning—that between the ages of 11 and 19, I had not been cuddled even once. Sleeping with another person and feeling their warmth made me drunk with love, and shocked that I had not had it for so long. I realized that I didn’t want sex as much as I wanted to be cuddled. Now, as a mother, I hope to give my children all the cuddles they’ll consent to during those desert years.”


“I work as an end-of-life doula and death educator, and I recently had a patient who was mostly deaf and blind. At our first meeting, I quickly discovered that the thing he enjoyed most was touch. I could warm up my hands, take his, and he would just coo about how nice it was. The most comforting thing I could do for him was hold his hand. It was really that simple. I think touch is one of the most precious things we can offer another person, and supplying it to others—or denying it—says a lot about how we feel about each other.”


“There is nothing that makes me feel happier than expressing my love through touch. But since moving to a new country, I have nobody to touch, and there’s nobody to touch me. What can I do? I find myself doing the most embarrassing things when I am alone. Sometimes I put my palms on both my cheeks and pretend that someone else is holding my face, because that gesture, that sensation of my face being held, evokes a feeling of being loved for me. Or I clasp my hands when I am falling asleep and pretend someone is holding my hand. It’s so embarrassing to confess that. But it’s true. They say we need to love ourselves first, right? I try to do that.”


“As a graduate student in Iowa City, I joined Iowa’s Brazilian–jiu-jitsu club. It was the dead of winter; the ground had frozen over and would not thaw. We walked to class in parkas. We barely saw bare skin. The first day of jiu-jitsu, by contrast, was a sweaty half-naked mess, full of me and undergraduate boys in a badly insulated room in an old field house. At first it seemed comically uncomfortable to press myself up against 18-year-olds who could have been taking my creative writing classes. But I felt so charged afterward that I started to crave it. We wrapped our bodies around one another for 90 minutes within this structured set of rules. It was animal and exhausting and cognitively difficult, because jiu-jitsu, at which I am very bad, requires so much choreography. It was like reverting to something lost. It made me doubt the way I lived outside that room.”

What’s Your Most Important Memory of Touch? Amid a pandemic that is profoundly decreasing skin-on-skin contact, the author asked people to share their most affecting tactile experiences. KRISTEN RADTKE APRIL 15, 2020

What Do You Miss Most About Touch, During the Pandemic? – The Atlantic

The Math of Prophet. Breaking down the Equation behind… | by Winston Robson | Future Vision | Medium

DEEP DIVE | MACHINE LEARNING | TIME SERIES FORECASTING

The Math of Prophet

Breaking down the Equation behind Facebook’s open-source Time Series Forecasting procedure

Winston Robson

Winston RobsonFollowJun 17, 2019 · 10 min read

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In this Story we examine the ins and outs of the mathematics utilized by Prophet, a time series forecasting tool by Facebook.

Outline

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1) Quick review: What is Prophet?

Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonalityplus holiday effects.

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It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.

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2) How does it work? Prophet Equation

The procedure makes use of a decomposable time series model with three main model components: trendseasonality, and holidays.

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Similar to a generalized additive model (GAM), with time as a regressor, Prophet fits several linear and non-linear functions of time as components. In its simplest form;

y(t) = g(t) + s(t) + h(t) + e(t)

where:

g(t)

  • trend models non-periodic changes (i.e. growth over time)

s(t)

  • seasonality presents periodic changes (i.e. weekly, monthly, yearly)

h(t)

  • ties in effects of holidays (on potentially irregular schedules ≥ 1 day(s))

e(t)

  • covers idiosyncratic changes not accommodated by the model

In other words, the procedure’s equation can be written;

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Modeling seasonality as an additive component is the same approach taken by exponential smoothing… GAM formulation has the advantage that it decomposes easily and accommodates new components as necessary, for instance when a new source of seasonality is identified.

Prophet is essentially “framing the forecasting problem as a curve-fitting exercise” rather than looking explicitly at the time based dependence of each observation.

3) Trend

The procedure provides two possible trend models for g(t), “a saturating growth model, and a piecewise linear model.”

3.1) Saturating Growth Model

If the data suggests promise of saturation — i.e. one is wrestling constraints like: cubed footage, processing power, number of people w/ Internet access— setting growth='logistic' is the move.

Typical modeling of these nonlinear, saturating trends is basically accomplished;

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where:

  • C is the carrying capacity
  • k is the growth rate
  • m is an offset parameter

There are two primary aspects of growth at Facebook (fluctuating carrying capacity and volatile rate of change) that are not captured in this simplified equation, though.

Carrying Capacity v. Time

First, as with many scalable business models carrying capacity is not constant — as “the number of people in the world who have access to the Internet increases, so does the growth ceiling.”

Accounting for this is done by replacing the fixed capacity C with a time-varying capacity C(t).

Rate of Change v. Time

Second, the market does not allow for stagnant technology. Advances like those seen over the past decade in handheld devices, app development, and global connectivity, virtually ensure that growth rate is not constant.

Because this rate can quickly compound due to new products, the model must be able to incorporate a varying rate in order to fit historical data.

We incorporate trend changes in the growth model by explicitly defining changepoints where the growth rate is allowed to change.

Suppose there are S changepoints at times sj, j = 1,…,S.

Prophet defines a vector of rate adjustments;

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where:

  • δis the change in rate that occurs at time sj

The rate at any time t is then the base rate k, plus adjustments up to that time;

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  • This is represented more cleanly by defining a vector;
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  • such that;
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The rate at time t is then k+a(t)ᵀδ. When the rate is adjusted, the offset parameter m must also be adjusted to connect the endpoints of the segments. The correct adjustment at changepoint j is easily computed as;

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At last, the piecewise growth=‘logistic’ model is reached;

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An important set of parameters in our model is C(t), or the expected capacities of the system at any point in time. Analysts often have insight into market sizes and can set these accordingly. There may also be external data sources that can provide carrying capacities,such as population forecasts from the World Bank.

In application, the logistic growth model presented here is a special case of generalized logistic growth curves — which is only a single type of sigmoid curve — allowing the relatively straightforward extension(s) of this trend model to other families of curves.

3.2) Linear Trend with Changepoints

The second — much simpler and default — trend model is a simple Piecewise Linear Model with a constant rate of growth.

It is best suited for problems without a market cap or other max in sight, and is set via growth='linear'.

For forecasting problems that do not exhibit saturating growth, a piece-wise constant rate of growth provides a parsimonious and often useful model.

Modeling the linear trend is easily realized with Prophet. In fact, not adjusting anything usually does the trick;

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where:

  • k is the growth rate
  • δ has the rate adjustments
  • mis the offset parameter

and, to make the function continuous, γj is set to:

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3.3) Automatic Changepoint Selection

If known, the changepoints sj can be specified by the user as dates of product launches and other growth-altering events, or, by default, changepoints may be automatically selected given a set of candidates.

Automatic selection can be done quite naturally with the formulation in either model by putting a sparse prior on δ.

Often, it is advisable to specify a large number of changepoints (e.g. one per month for a several year history) and use the prior:

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where:

  • τ directly controls the flexibility of the model in altering its rate

Critical note: a sparse prior on the adjustments δ has no impact on the primary growth rate k, so as τ progresses to 0 the fit reduces to standard (not-piecewise) logistic or linear growth.

3.4) Trend Forecast Uncertainty

When the model is extrapolated past the history to make a forecast, the trend g(t) will have a constant rate; the uncertainty in the forecast trend is estimated by extending the generative model forward.

The generative model for the trend is that there are;

  • changepoints
  • over a history of T points
  • each of which has a rate change δj∼Laplace(0,τ)

Simulation of future rate changes (that emulate those of the past) is achieved by replacing τ with a variance inferred from data.

In a fully Bayesian framework this could be done with a hierarchical prior on τ to obtain its posterior, otherwise we can use the maximum likelihood estimate of the rate scale parameter:

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Future changepoints are randomly sampled in such a way that the average frequency of changepoints matches that in the history:

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Thus, uncertainty in the forecast trend is measured by assuming the future will see the same average frequency and magnitude of rate changes that were seen in the history. Once λ has been inferred from the data, this generative model is deployed to “simulate possible future trends and use the simulated trends to compute uncertainty intervals.”

Prophet’s assumption that the trend will continue to change with the same frequency and magnitude as it has in the history is fairly strong, so don’t bank on the uncertainty intervals having exact coverage.

As τ is increased the model has more flexibility in fitting the history and so training error will drop. Even so, when projected forward this flexibility is prone to produce wide intervals. The uncertainty intervals are, however, a useful indication of the level of uncertainty, and especially an indicator of over fitting.

4) Seasonality

The seasonal component s(t) provides a adaptability to the model by allowing periodic changes based on sub-daily, daily, weekly and yearly seasonality.

Business time series often have multi-period seasonality as a result of the human behaviors they represent. For instance, a 5-day work week can produce effects on a time series that repeat each week, while vacation schedules and school breaks can produce effects that repeat each year. To fit and forecast these effects we must specify seasonality models that are periodic functions of [time] t.

Prophet relies on Fourier series to provide a malleable model of periodic effects. P is the regular period the time series will have (e.g. P = 365.25 for yearly data or P = 7 for weekly data, when time is scaled in days).

Approximate arbitrary smooth seasonal effects is therefore tied in with a standard Fourier series;

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Fitting seasonality requires estimating the 2N parameters β=[a1,b1,…,aN,bN]ᵀ. This is done by constructing a matrix of seasonality vectors for each value of t in our historical and future data, for example with yearly seasonality and N= 10:

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Meaning the seasonal component is;

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In the generative model, Prophet takes β∼Normal(0,σ²) to impose a smoothing prior on the seasonality.

Truncating the series at N applies a low-pass filter to the seasonality, so, albeit with increased risk of overfitting, increasing N allows for fitting seasonal patterns that change more quickly.

For yearly and weekly seasonality we have found N = 10 and N = 3 respectively to work well for most problems. The choice of these parameters could be automated using a model selection procedure such as AIC.

5) Holidays and Events

Impact of a particular holiday on the time series is often similar year after year, making it an important incorporation into the forecast. The component h(t) speaks for predictable events of the year including those on irregular schedules (e.g. Black Friday or the Superbowl).

To utilize this feature, the user needs to provide a custom list of events. Fusing this list of holidays into the model is made straightforward by assuming that the effects of holidays are independent.

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* not tied to one country

For each holiday i, let Di be the set of past and future dates for that holiday. Then add an indicator function representing whether time t is during holiday i, and assign each holiday a parameter κwhich is the corresponding change in the forecast.

This is done in a similar way as seasonality by generating a matrix of regressors;

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and taking,

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As with seasonality, Prophet uses a prior κ∼Normal(0,ν²).

It is often important to include effects for a window of days around a particular holiday, such as the weekend of Thanksgiving. To account for that we include additional parameters for the days surrounding the holiday, essentially treating each of the days in the window around the holiday as a holiday itself.

Conclusion

Ultimately, Prophet was engineered to help analysts with a variety of backgrounds produce more forecasts with less time invested towards doing so. This was achieved by sticking to a relatively plain model.

After all, “Introduction to Time Series and Forecasting (Springer Texts in Statistics) 3rd ed. 2016 Edition” is 425 pages in length, the “Forecasting at Scale” Prophet paper is 25 pages, and you’ve read this Story in about 10 minutes.

We use a simple, modular regression model that often works well with default parameters, and that allows analysts to select the components that are relevant to their forecasting problem and easily make adjustments as needed.

Thanks for reading; if you’re eager to know more about why Facebook built Prophet, check out this presentation by one of the team leads, Sean Taylor:

https://cdn.embedly.com/widgets/media.html?src=https%3A%2F%2Fwww.youtube.com%2Fembed%2FpOYAXv15r3A%3Ffeature%3Doembed&url=http%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DpOYAXv15r3A&image=https%3A%2F%2Fi.ytimg.com%2Fvi%2FpOYAXv15r3A%2Fhqdefault.jpg&key=a19fcc184b9711e1b4764040d3dc5c07&type=text%2Fhtml&schema=youtube

Continued Reading

Intro to Facebook ProphetEverything you need to know when starting out with Facebook’s time series forecasting tool (w/ walk-thru Example &…medium.comCross validating Prophet at ScaleDistributed Time Series Cross Validation and Hyperparameter Optimization with Daskmedium.com

References

  1. Taylor SJ, Letham B. 2017. Forecasting at scale. PeerJ Preprints 5:e3190v2 https://doi.org/10.7287/peerj.preprints.3190v2
  2. Forecasting at Scale: How and Why We Developed Prophet for Forecasting at Facebook (Lander Analytics ; YouTube)
  3. Robson, Winston A. “The Prophet on Walmart — Comprehensive Intro to FbProphet.” Medium, Future Vision, 9 July 2019, https://medium.com/future-vision/intro-to-prophet-9d5b1cbd674e

The Math of Prophet. Breaking down the Equation behind… | by Winston Robson | Future Vision | Medium

Ken Block’s TERRAKHANA (Extended Cut): The Ultimate Dirt Playground; Swing Arm City Utah – YouTube

How About This Weather? – The Atlantic

TIM LAHAN

The correct answer to the question “How are you?” is Not too bad.

Why? Because it’s all-purpose. Whatever the circumstances, whatever the conditions, Not too bad will get you through. In good times it projects a decent pessimism, an Eeyore-ish reluctance to get carried away. On an average day it bespeaks a muddling-through modesty. And when things are rough, really rough, it becomes a heroic understatement. Best of all, with three equally stressed syllables, it gently forestalls further inquiry, because it is—basically—meaningless.

Small talk is rhetoric too. Americans in particular are small-talk artists. They have to be. This is a wild country. The most tenuous filaments of consensus and cooperation attach one person to the next. So the Have a nice days, the Hot enough for yous, the How ’bout those Metses—they serve a vital purpose. Without these emollient little going-nowhere phrases and the momentary social contract that they represent, the streets would be a free-for-all, a rodeo of disaster.

I was out walking the other day when a UPS truck rumbled massively to the curb in front of me. As the driver leaped from his cab to make a delivery, I heard music coming out of the truck’s speakers—a familiar, weightless strain of blues-rock noodle. There was a certain spacey twinkle in the upper registers, a certain flimsiness in the rhythm section … Yes. It had to be. The Grateful Dead, in one of their zillion live recordings. And I knew the song. It’s my favorite Dead song. “ ‘China Cat Sunflower’?” I said to the UPS guy as he charged back to his truck. A huge grin: “You got it, babe!”

The exchange of energy, the perfect understanding, the freemasonry of Deadhead-ness that flashed instantaneously between us, and most of all the honorific babe—I was high as a kite for the next 10 minutes, projected skyward on a pure beam of small talk..

How About This Weather? – The Atlantic

How Putin Got Into America’s Mind – The Atlantic

How Putin Got Into America’s Mind

He learned the art of destabilizing his opponents from the Stasi, East Germany’s secret police.

A close-up shot of Russian President Vladimir Putin's head and shoulder, against a red background

In August, the Senate Intelligence Committee reported in exhaustive detail how Russia sowed division in the United States and sought to meddle in the 2016 election in favor of Donald Trump. Immediately, Republicans and Democrats battled over whether the Trump campaign had engaged in a “criminal conspiracy” with Russia, or “collusion,” or “cooperation,” or established “ties”—or whether, as the White House claimed, Trump was the victim of a massive liberal conspiracy. Years after 2016, Russian election interference continues to reap dividends for Moscow by turning American against American.

Russian President Vladimir Putin is particularly adept at psychological warfare because he has been practicing it for decades. He learned the art of destabilizing his opponents from the Stasi, East Germany’s secret police. Russia now uses the same techniques. However, it not only targets individuals; it torments entire countries.

In the late 1980s, Putin lived in Dresden, East Germany. On paper, he ran a Soviet-German “friendship house.” In practice, he was a KGB agent, likely helping the Red Army Faction, a left-wing terrorist group, plot attacks in West Germany. The KGB was eager to learn surveillance techniques from the Stasi, and Putin worked closely with the organization (researchers recently discovered Putin’s Stasi card).

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Throughout the ’70s and ’80s, East Germany worked to repress dissidents, artists, peace campaigners, and church activists. The regime was worried, however, that the usual authoritarian strategies—gulags, physical torture, and tanks on the streets—might damage the country’s reputation. After all, East Germany had promised to uphold human rights as a signatory of the 1975 Helsinki Accords. But East German leader Erich Honecker wasn’t concerned about suppressing the opposition: “There will always be the Stasi.”

The East German secret police developed a method known as Zersetzung or “decomposition” to stamp out rebellion without the use of overt force. The idea was to chip away at a dissident’s sanity so that he would lose the will to resist, or in the words of a Stasi guide, “[provoke] and [enforce] internal conflicts and contradictions within hostile-negative forces that fragment, paralyze, disorganize, and isolate” the opponent. The first step in a campaign was to identify the target’s weak spots—health, family, finances—then strike them over and over. Stasi agents might break into a dissident’s apartment and move the pictures around or change the time on the alarm clock. They might mail a sex toy to a target’s wife or send postcards from an unknown woman demanding child support. They might enlist doctors to give false medical diagnoses or ensure that a manager halted the dissident’s career progress without explanation. The techniques were targeted, flexible, and above all efficient.

Decomposition was designed to unglue a dissident’s psyche. A regime opponent would find himself trapped in a Kafkaesque nightmare. Everywhere he turned, an evil force seemed to be hounding him, even though he could not prove that he had been singled out. Who would believe that the government was secretly stealing his dish towels? Some targets suffered breakdowns and others killed themselves. The writer Jürgen Fuchs, a Stasi victim, called the campaign “an assault on the human soul.”

In recent years, Russia has reportedly used the methods of decomposition against individual journalists and diplomats. Putin’s real innovation has been to weaponize Zersetzung against countries. Much of Moscow’s foreign policy can be understood as a kind of diplomatic decomposition, a grand strategy of gaslighting. After all, Putin faces the same fundamental problem as the East German leadership: how to suppress opposition without overt violence. Moscow wants to restore Russia as a great power and reverse the tide of Western encroachment. But in today’s world of integrated global economies and nuclear deterrence, open aggression is extremely costly—which is why conventional wars between countries are very rare. The answer to this conundrum lies with the Stasi playbook, employed on a much grander scale.

Russia seeks to weaken a foreign adversary from the inside, paralyzing its ability to resist. It partners with a range of allies, such as oligarchs and journalists, and uses a diverse toolbox, including propaganda and cyber attacks. Moscow begins by locating the target country’s weakest point, whether it’s an ethnic, religious, or partisan cleavage. Then Russia manufactures a sense of distrust to destroy the social contract. Whereas the Stasi might break into a man’s apartment in the middle of the night and turn on his electric razor—just to freak him out—Moscow uses hackers and trolls to propagate conspiracy theories and cultivate a skepticism of authority.

Russia’s meddling in the 2016 U.S. election was less about altering the result, and more about messing with America’s sanity—feeding cynicism about the system, encouraging people to second-guess reality, and leaving America too incapacitated to offer much resistance. Since 2016, the Kremlin has continued trying to maximize political division, using troll farms and Facebook to boost both Trump and Bernie Sanders, and attack Joe Biden.

Putin also tried to decompose the European Union by backing far-right nationalist parties such as the French National Rally (formerly the National Front) and the Alternative for Germany, as well as the Leave campaign in the Brexit referendum. Moscow spread false reports of rape by immigrants in Berlin—a classic decomposition technique. Russian operatives were linked to a plot to undermine the parliamentary election in Montenegro in 2016, and stop the Balkan country from entering NATO. (Montenegro eventually joined the alliance in 2017.)

Modern-day Russia isn’t the only country that has tried to destabilize an enemy. Long before Putin came to power, the Soviet Union engaged in what were known as “active measures.” During the Cold War, Moscow spread the rumor that the U.S. government created AIDS as a secret biological weapon. Meanwhile, the United States used Radio Free Europe to sow opposition against communist regimes behind the Iron Curtain.

Russia’s weaponized Zersetzung is unusual, however, in its calibrated use of pressure and its keen awareness of the enemy’s weak spots, especially the vulnerability of democratic societies in an age of social media, populism, and distrust of elites. Just like the Stasi sought to destroy a target’s reputation by blending accurate and damaging information with harmful lies, so Russian media mixes real stories with disinformation to make people doubt the truth, or as the Russian state television network RT slogan says, “Question More.” For its part, Moscow claims that its actions are a defensive measure against Western efforts to decompose Russia and depicts all independent reporting at home as foreign-backed psychological warfare.

Trump is unable to resist Russia’s strategy because he refuses to criticize Putin. But the issue goes beyond Trump: Countering Russia’s tactics would be tough even if the United States had a leader who took the danger seriously. Biden has promised that “if any foreign power recklessly chooses to interfere in our democracy, I will not hesitate to respond as president to impose substantial and lasting costs.” But checking Russia will be easier said than done because of America’s stark polarization. The Russian threat has become yet another partisan issue. Even if Biden wins in November, he could face Republican opposition to any tough response. And although economic sanctions might hurt Russia’s economy, they won’t easily heal the divisions that weaponized decomposition has deepened in America. Putin’s assault on the national soul is working.

How Putin Got Into America’s Mind – The Atlantic

Washington: Images of the Evergreen State – The Atlantic

Washington State is home to more than 7.6 million residents, most living on the western side of the Cascade Mountains. I originally published these photos of Washington last year, dedicating them to my mother and father, who loved their home state, and who had passed away the month before. The warm reactions to that photo story were what inspired me to undertake this larger project, “Fifty,” presenting wide-ranging collections of images of each state in the U.S. I’m happy to now add this collection to the project, and hope you enjoy these glimpses of the landscape of Washington and some of the wildlife and people calling it home.

This photo story is part of “Fifty,” a collection of images from each state of the United States.HINTS: View this page full screen. Skip to the next and previous photo by typing j/k or ←/→.

  • The rolling hills of the Palouse, viewed from Steptoe Butte State Park in Washington State #Justin Reznick Photography / Getty
  • The Spokane River flows through Riverfront Park in downtown Spokane, Washington. #Krumpelman Photography / Shutterstock
  • A winter night atop Mount Spokane #Kendall Rittenour / Shutterstock
  • Wheat fields stand in Peone Prairie, in Spokane County. #JW PNW / Shutterstock
  • A female moose grazes at Turnbull Wildlife Refuge near Cheney, Washington. #Gregory Johnston / Shutterstock
  • Palouse Falls and Palouse River Canyon, near Washtucna #Aaron Eakin / Getty
  • A horse-drawn wheat wagon moves through a field in the Palouse region near Colfax, Washington, on September 7, 2015. Every year, area farmers participate in the old-fashioned Colfax Threshing Bee using only vintage equipment. #Gregory Johnston / Shutterstock
  • A dust devil swirls above a field in eastern Washington. #Frontier Sights / Shutterstock
  • A trail winds down through sagebrush into a valley, during springtime in the Columbia National Wildlife Refuge. A significant part of the Channeled Scablands, these basalt buttes and canyons, were scoured by ancient Ice Age floods. #Lidija Kamansky / Getty
  • Fall colors along the Okanogan River at Shellrock Point in Omak, Washington #Michael C. Weaver / Shutterstock
  • Elk gather to feed at the Oak Creek Wildlife Area Feeding Station in Naches, Washington. #Paula Cobleigh / Shutterstock
  • Fresh snow along the South Fork Snoqualmie River in the Mount Baker-Snoqualmie National Forest #Danita Delmont / Shutterstock
  • Sand blows across a road near dunes outside Pasco, Washington. #Kevin J Salisbury / Getty
  • The landscape near Fields Point Landing on Lake Chelan, with a view looking north to Red Butte and other peaks of the South Methow Mountains #Mark C Stevens / Getty
  • A moss-covered wooden fence stands in the woods near Winthrop, Washington. #Gregory Johnston / Shutterstock
  • A westbound train cruises by Rowland Lake on a large arcing fill just east of Bingen, Washington, in the Columbia River Gorge. #Mike Danneman / Getty
  • A single apple remains hanging in an orchard after all the leaves have fallen from the trees in Yakima, Washington. #Michelle Baumbach / Shutterstock
  • A vineyard near Wapato, with a chapel atop one of its hills #Terry Eggers / Getty
  • Small alpine plants bloom in the foreground with the massive Mount St. Helens volcano in the background. #Bazpics / Getty
  • Water flows from the Diablo Dam on the Skagit River in Whatcom County. #Crady von Pawlak / Getty
  • A stream runs between lakes in the Enchantments, in Washington’s Alpine Lakes Wilderness. #Ed Leckert / Getty
  • A Washington State ferry moves through Elliott Bay, with the Olympic Mountains in the background. #Nadia Yong / Shutterstock
  • The Seattle city skyline, viewed from Elliott Bay #Malorny / Getty
  • Morning breaks over mountains above the Hoh Rain Forest. #Kelly vanDellen / Shutterstock
  • Waves roll in at high tide near La Push, Washington. #Aliaksei Baturytski / Shutterstock
  • A trail winds through the Hoh Rain Forest in Olympic National Park. #CreativeEdge7 / Shutterstock
  • An Alaska state ferry makes its way past islands in Puget Sound, headed toward southeast Alaska and beyond, leaving from Bellingham, Washington. #Edmund Lowe Photography / Getty
  • Tulip fields, photographed from the air above the Skagit Valley in western Washington #Sunset Avenue Productions / Getty
  • A stormy day on San Juan Island, Washington, near Lime Kiln Lighthouse #Edmund Lowe Photography / Shutterstock
  • Whatcom Falls Park, a 240-acre park in Bellingham, Washington #Edmund Lowe Photography / Getty
  • Beacon Rock State Park, located in the Columbia River Gorge #Marshall L. P. / Shutterstock
  • A disused dock on the Columbia River in Cathlamet, Washington #© Alan Taylor
  • Sunlight and shadow play on the Columbia River Gorge on a partly cloudy day. #Mitch Diamond / Getty
  • The sun sets over Kalaloch Beach in Olympic National Park. #

The Sport That’s Like Playing in a Jazz Quartet – The Atlantic

The new NBCUniversal streaming service Peacock is now offering the documentary A Most Beautiful Thing as a free feature. (Details here.) Last week I wrote about the movie, and its surprising timeliness and power, in this article. The film, based on a memoir by Arshay Cooper, is the saga of young men from the West Side of Chicago who in the 1990s formed what appears to have been the first all-Black high-school rowing team in the country.

In response, Peter Gadzinski, previously of Vermont but now living in Europe, writes about the themes of the book and movie, and how different this sport can seem from another country’s perspective.

The Sport That’s Like Playing in a Jazz Quartet – The Atlantic

Through my son I have been introduced to rowing, and it is a great sport.

We have been living in Portugal, where my wife is from, and where our son is going to school, and they have a slightly different take on rowing here that I wish was in America.

First, none of the schools have any sports teams. Sports teams are all organized by town clubs. That means that the whole town can cover the expense, and you can be in the club from literally 8 years old to 80. There is none of this sports-stops-cold when you graduate high school or college. Also, the rowing club out here is open to anyone, with a just fee of $40 a month which is waived for those who can’t afford it, which makes the otherwise very expensive sport of rowing available to everyone.

The other thing here is that they race in all of the types of boats: singles, doubles, fours, and the eight, with one and two oar boats in the doubles and fours. I grew up playing soccer, and like most team sports, it is all about only the first string playing, and everyone else sitting on the bench. By racing in all boat classes, in a meet here it is like a track meet, in that everyone races. Everyone knows what the club “A” boat is, but everyone races in a meet.

The saying is that you put your best and your worst people in the single. The best so that they are not slowed up by lesser people in a multiple seat boat, and the worst, so they don’t slow up anyone in a multiple seat boat. But in a big meet everyone races, from the kids in elementary school, to the “veterans”: the gray haired adults, with even special boats with outriggers for the handicapped. This thing in America where in college it is all about getting a “crew” seat in “the 8” doesn’t exist here, which is good.

But as you pointed out, there is something special and unique about rowing. Once you get past both the expense of it and the preppy reputation of it, there is something very special about it. The way I explain it to people is that the only comparable activity would be to play music in a classical or jazz quartet. You become one group, all together and synchronized. Except in rowing you are breathing a lot harder. It is really something to behold, and something to be part of.

Not only are rowers in perfect mental and physical synchronization when rowing, but due to the extreme motion of their bodies back and forth they are like birds in flight and breathe in and out with their body movements. That means that the entire boat is breathing together as well. There is supposed to be something beneficial to singing together. Rowing together is the same, except with a lot more horsepower.

I had grown up thinking rowing was just some bizarre preppy thing for rich kids. It still is in a lot of America, but in Europe it is a lot more common and public. If I were a billionaire philanthropist I would put all of my money into paying for rowing clubs all over the country. It is a really good thing to do. As the saying goes: “Rowing is a sport, everything else is a game.” Get a bunch of young people to give their all and literally all pull together is a wonderful thing.  There should be more of it.

Update: Another reader, with a military-aviation background, writes in with another comparison:

When reading The Boys in the Boat. I was struck by how much rowing reminded me of flying close formation aerobatics with the Blue Angels. I’m giving copies to my former wingmen for Christmas

The Sport That’s Like Playing in a Jazz Quartet – The Atlantic

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How to Fight Fear With Love – The Atlantic

A man and a woman lean in smiling, holding a smiley face icon between their foreheads
JAN BUCHCZIK
 

We are living in a time of fear. The coronavirus pandemic has threatened our lives, health, and economy in ways most Americans have never experienced. We have no idea what the future will bring. According to the American Psychological Association’s annual “Stress in America” survey, the percentage of people in the U.S. who say that “the future of our nation is a significant source of stress” rose to 83 percent in June 2020, up from 63 percent in 2017.

But even before the pandemic, fear about the future was high and on the rise. Gallup found that the percentage of Americans who had experienced worry “during a lot of the day yesterday” rose from 36 percent to 45 percent from 2006 to 2018; similarly, feelings of stress rose from 46 percent to 55 percent. This matches my personal experience. Given what I write about for a living, it may not be surprising that I start many conversations by asking people about their happiness. If you make the mistake of talking to me on an airplane, that’s where the conversation is going to go. In recent years, I have noticed, people have told me more and more that they are afraid.

People’s fears vary widely. The pandemic aside, the answers I hear are all over the place, from leaders they don’t trust, to environmental problems, to simply being able to support themselves and take care of their families. According to Chapman University’s annual “Survey of American Fears,” almost 74 percent of Americans in 2018 were afraid of corrupt government officials, nearly 62 percent were afraid of pollution in bodies of water, and 57 percent were afraid of not having enough money for the future.

One way of dealing with these fears is to strive to eliminate the threats that caused them. But while social and economic progress is important and possible, there will always be threats to face and things to fear. The way to combat fear within ourselves is with its opposite emotion—which is not calmness, or even courage. It’s love.

The Chinese philosopher Lao Tzu wrote in the Tao Te Ching, “Through Love, one has no fear.” More than 500 years later, Saint John the Apostle said the same thing: “There is no fear in love. But perfect love drives out fear, because fear has to do with punishment. The one who fears is not made perfect in love.”

This is a very strong argument: Love neutralizes fear. It took about 2,000 years, but contemporary neurobiological evidence has revealed that Lao Tzu and Saint John were absolutely on the money.

Fear is a primary emotion processed in the amygdala, a part of the brain that detects threats and signals to the body to produce the stress hormones that make us ready for fight or flight. This is largely involuntary, and, while necessary for survival, is unpleasant (except under controlled circumstances, such as roller coasters). The fear response is also maladapted to modern life. For example, a friend of mine with a large Twitter following once told me that he felt his chest tighten every day as he clicked on the social media app on his phone. His amygdala was alerting him that dangerous threats lay ahead, and he was getting a dose of adrenaline and cortisol in response—even though nothing was likely going to harm him.

However, we have a natural modulator of the hyperactive amygdala: the neuropeptide oxytocin, sometimes called the “love molecule.” Oxytocin is often produced in the brain in response to eye contact and touch, especially between loved ones. The feeling it creates is intensely pleasurable; indeed, life would be unbearable without it. There is evidence that an oxytocin deficit is one reason for the increase in depression during the coronavirus pandemic, with its lockdowns and social distancing.

Oxytocin has also been found to reduce anxiety and stress by inhibiting the response of the amygdala to outside stimuli. If you have loving contact with others, the outside world will seem less scary and threatening to you. What Saint John asserted is literally true: Perfect love drives out fear.

Our current fear problem is not due to a proliferation of threats. Despite all the troubles we face, as my Harvard colleague Steven Pinker has shown, the world of the 21st century is safer for the vast majority of us than the world of previous eras (current pandemic aside). The real issue is that we have too little love in our lives to protect us against our fears.

Americans are getting lonelier. Former Surgeon General Vivek Murthy has written a book about this, and the U.S. Health Resources and Services Administration has declared a “loneliness epidemic,” specifically citing “living alone, being unmarried … no participation in social groups, fewer friends, and strained relationships” as the culprits. Clearly, a lack of relationships makes life’s fears harder to cope with.

It is especially notable that today’s adolescents and young adults enjoy less romantic love than in the past. Research shows that young people are far less likely to date, marry, and have sex than in past generations. According to my own analysis, using the General Social Survey, the percentage of married 20-somethings fell from 32 percent to 19 percent between 1989 and 2016. Meanwhile, the percentage who had not had sex in the past year rose from 12 percent to 18 percent.

The pandemic makes things worse by driving friends and neighbors apart. But our political culture has been doing this as well for some time, with brutal efficiency. In 2016, the Pew Research Center found that people were more likely than before to express negative opinions about others simply because of their affiliation with the opposite political party, and this is especially true among those who are highly engaged in politics. According to a Reuters/Ipsos poll that ran from late 2016 to early 2017, 13 percent of Americans have “ended a relationship with a family member or close friend over the [2016] election.”

The math here is easy: More isolation plus more hostility equals less love; less love equals more fear. To reduce fear, we need to bring more love into our lives. If you’re not sure how to get started, let me suggest the following approach, which starts pretty easy and advances in difficulty.

1. Confess your fear to someone you trust. Many people carry their fears stoically, never sharing them openly with others. Hidden fear often expresses itself obliquely and in unproductive ways, such as hostility or aloofness. It is also a missed opportunity: To confess fear, while scary in and of itself, is an act of vulnerability that stimulates the love you crave, in yourself and in the ones you allow to comfort you.

2. Make your love overt. Today, tell someone you love her or him. Not someone you would normally say that to, but rather to a friend or family member for whom this would not feel natural. The point here is to break a barrier of expression for yourself but in a way that is relatively safe. The more you say “I love you,” the less strange or scary it will feel. It is a small act of courage. The payoff is not just more closeness, but also an increase in your fortitude, which you might need for the next step.

3. Take a risk. Confess your love or admiration for someone who doesn’t know that you have these feelings. This requires particular courage in the case of romantic love, because the risk of personal rejection feels so high—and is even harder if you have no practice with this kind of rejection. It is a direct confrontation of fear with love. But even telling someone you’d like to be friends, or telling a co-worker you admire them, can feel risky, because the feeling could be unrequited. Do it anyway.

If you want, blame the coronavirus: Say the lockdown has made you a little crazy. Or tell the person why you are doing it, and let them comfort you (and see where it goes from there).

4. Love your enemies. This is perhaps the hardest piece of advice, in our polarized ideological climate. But it may also result in an enormous payoff to you personally as well as to the broader culture of contempt we have come to inhabit. Try resolving for a week not to attack anyone over differences of opinion, in person or on social media. Disagreement is fine, but try to have those conversations with understanding and kindness.

I realize that this advice runs counter to today’s culture. If you think someone is wrong, your instinct may be to hate more, to fight harder. But you can’t insult anyone into agreement, and you probably have little or no real power to force others to do your will. Furthermore, antagonism, the opposite of an expression of love, will likely only make your fears worse.

What I’m suggesting isn’t easy. Showing love in the face of fear isn’t a natural reaction. Fear instinctively provokes fight or flight, not tenderness and affection. But remember: Instinct doesn’t care if you are happy. You need to violate your instincts if you want to build a better, less fearful life.

So stand up to your amygdala. Walk toward your fear. Face it, feel it, and love courageously.

via How to Fight Fear With Love – The Atlantic

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The camera always lies – “No Filter” chronicles the rise of Instagram | Books & arts | The Economist

The camera always lies
“No Filter” chronicles the rise of Instagram

Sarah Frier, a reporter for Bloomberg, also offers glimpses of Silicon Valley’s weirdness

Books & artsMay 23rd 2020 edition

No Filter. By Sarah Frier.Simon & Schuster; 352 pages; $28. Random House Business; £20.

On a beachside walk in Mexico in 2010, Kevin Systrom’s girlfriend explained the problem with his new photo-sharing app, then called “Codename”. Professionals might want the world to see their pictures, but her own phone snaps weren’t good enough. Back at the hotel, Mr Systrom coded a quick solution: a filter that gave even the most basic shot a hipster finish. He applied it to a snap of a dog by a taco stand, and uploaded it, making it the first image posted to what became Instagram.

A billion users later, the look in that filtered photo is ubiquitous. Square proportions, high contrast and darkened edges have instantly smartened up profile pictures, holiday albums and advertising campaigns around the world. In “No Filter” Sarah Frier, a technology correspondent at Bloomberg, uses close access to Instagram insiders to give a lively and revealing account of how the world came to see itself through Mr Systrom’s lens.

The tale of nerds who struck gold offers glimpses of Silicon Valley’s weirdness. In the early days Mr Systrom and his co-founder, Mike Krieger, patched errors with their laptops on camping trips and took a call from Justin Bieber when he forgot his password. Later, haggling over Instagram’s sale to Facebook, a crunch negotiation took place over a barbecue at Mark Zuckerberg’s mansion, with the Facebook founder grilling meat he boasted of shooting himself, though he was unsure if it was venison or boar. Mr Systrom went to the Vatican to persuade the ultimate influencer to sign up—and @franciscus obliged.

The sale, for a then-unthinkable $1bn, went sour. At Facebook “every single activity…stemmed from a religious obsession with growth,” writes Ms Frier, who is even-handed but seems closer to Instagram’s founders than Facebook’s high command. As its new owner steered Instagram towards taking ads and making money, some early employees, who had wanted to build “a community centred around the appreciation of art and creativity…instead felt that they had built a mall”. Mr Systrom, a perfectionist who initially oversaw every ad carried on Instagram, personally editing one to make the French fries look crispier, was seen by Facebookers as a precious snob.

As Instagram grew bigger and cooler, Facebook began to act “like the big sister that wants to dress you up for the party but does not want you to be prettier than she is”, complains one Instagram executive. Mr Zuckerberg limited how many people Instagram could hire. He even got cross that its new video app, igtv, had a logo that looked a bit like that of Facebook Messenger. In 2018, after six years of this, Mr Systrom and Mr Krieger quit.

Within this business story are several subplots. One is how Instagram blurred the lines between the personal and the promotional. Snoop Dogg, a rapper, made what may have been the first paid Instagram post in January 2011, when he uploaded a picture of himself “Bossin up wit dat Blast”, a new drink. At least before covid-19 struck, Kim Kardashian could make $1m from a single post to her 157m followers; over 200m users had 50,000 followers or more, enough to make a living as “human billboards”. America’s Federal Trade Commission has said influencers should declare when they are being paid. They often don’t.

Another subplot is how an app that people use to document their life turned into one that determines how they live it. At first this was a virtue. In the early days Instagram began encouraging wholesome outings to scenic spots for users to photograph. But it has become a problem. Some photogenic places, like Norway’s Trolltunga cliff, have been overrun. Worse, the ability to edit photos to perfection has spread insecurity. “I don’t know what real skin looks like any more,” complains Chrissy Teigen, an Instagram star.

All this brought in $20bn for Instagram in 2019, or a quarter of Facebook’s revenue. But perhaps encouragingly, some in the company have come to see perfectionism as a risk to Instagram’s business. Young people have embraced Snapchat and, more recently, TikTok, as networks where they can go unfiltered. There they can post even imperfect shots: of their ordinary selves, their ordinary lives, even an ordinary dog by a taco stand.

via The camera always lies – “No Filter” chronicles the rise of Instagram | Books & arts | The Economist