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theadmiringbog · 5 years ago

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I had a fragile but agreeable life: a job as an assistant at a small literary agency in Manhattan; a smattering of beloved friends on whom I exercised my social anxiety, primarily by avoiding them.

I wanted to make money, because I wanted to feel affirmed, confident, and valued. I wanted to be taken seriously. Mostly, I didn’t want anyone to worry about me.

Conversation with the cofounders had been so easy, and the interviews so much more like coffee dates than the formal, sweaty-blazer interrogations I had experienced elsewhere, that at a certain point I wondered if maybe the three of them just wanted to hang out.

They wore shirts that were always crisp and modestly buttoned to the clavicle. They were in long-term relationships with high-functioning women, women with great hair with whom they exercised and shared meals at restaurants that required reservations. They lived in one-bedroom apartments in downtown Manhattan and had no apparent need for psychotherapy. They shared a vision and a game plan. They weren’t ashamed to talk about it, weren’t ashamed to be openly ambitious. Fresh off impressive positions and prestigious summer internships at large tech corporations in the Bay Area, they spoke about their work like industry veterans, lifelong company men. They were generous with their unsolicited business advice, as though they hadn’t just worked someplace for a year or two but built storied careers. They were aspirational. I wanted, so much, to be like—and liked by—them.

It was thrilling to watch the moving parts of a business come together; to feel that I could contribute.

What I also did not understand at the time was that the founders had all hoped I would make my own job, without deliberate instruction. The mark of a hustler, a true entrepreneurial spirit, was creating the job that you wanted and making it look indispensable, even if it was institutionally unnecessary.

I wasn’t used to having the sort of professional license and latitude that the founders were given. I lacked their confidence, their entitlement. I did not know about startup maxims to experiment and “own” things. I had never heard the common tech incantation Ask forgiveness, not permission.

I had also been spoiled by the speed and open-mindedness of the tech industry, the optimism and sense of possibility. In publishing, no one I knew was ever celebrating a promotion. Nobody my age was excited about what might come next. Tech, by comparison, promised what so few industries or institutions could, at the time: a future.

“How would you explain the tool to your grandmother?” “How would you describe the internet to a medieval farmer?” asked the sales engineer, opening and closing the pearl snaps on his shirt,

Good interface design was like magic, or religion:

The first time I looked at a block of code and understood what was happening, I felt like nothing less than a genius.

Anything an app or website’s users did—tap a button, take a photograph, send a payment, swipe right, enter text—could be recorded in real time, stored, aggregated, and analyzed in those beautiful dashboards. Whenever I explained it to friends, I sounded like a podcast ad.

four-person companies trying to gamify human resources

... how rare the analytics startup was. Ninety-five percent of startups tanked. We weren’t just beating the odds; we were soaring past them.

While I usually spent sleepless nights staring at the ceiling and worrying about my loved ones’ mortality, he worked on programming side projects. Sometimes he just passed the time between midnight and noon playing a long-haul trucking simulator. It was calming, he said. There was a digital CB radio through which he could communicate with other players. I pictured him whispering into it in the dark.

At the start of each meeting, the operations manager distributed packets containing metrics and updates from across the company: sales numbers, new signups, deals closed. We were all privy to high-level details and minutiae, from the names and progress of job candidates to projected revenue. This panoramic view of the business meant individual contributions were noticeable; it felt good to identify and measure our impact.

Was this what it felt like to hurtle through the world in a state of pure confidence, I wondered, pressing my fingers to my temples—was this what it was like to be a man?

I was interested in talking about empathy, a buzzword used to the point of pure abstraction,

The hierarchy was pervasive at the analytics startup, ingrained in the CEO’s dismissal of marketing and insistence that a good product would sell itself.

He just taught himself to code over the summer, I heard myself say of a job candidate one afternoon. It floated out of my mouth with the awe of someone relaying a miracle.

As early employees, we were dangerous. We had experienced an early, more autonomous, unsustainable iteration of the company. We had known it before there were rules. We knew too much about how things worked, and harbored nostalgia and affection for the way things were.

The obsession with meritocracy had always been suspect at a prominent international company that was overwhelmingly white, male, and American, and had fewer than fifteen women in Engineering.

For years, my coworkers explained, the absence of an official org chart had given rise to a secondary, shadow org chart, determined by social relationships and proximity to the founders. Employees who were technically rank-and-file had executive-level power and leverage. Those with the ear of the CEO could influence hiring decisions, internal policies, and the reputational standing of their colleagues. “Flat structure, except for pay and responsibilities,” said an internal tools developer, rolling her eyes. “It’s probably easier to be a furry at this company than a woman.”

“It’s like no one even read ‘The Tyranny of Structurelessness,’” said an engineer who had recently read “The Tyranny of Structurelessness.”

Can’t get sexually harassed when you work remotely, we joked, though of course we were wrong.

I was in a million places at once. My mind pooled with strangers’ ideas, each joke or observation or damning polemic as distracting and ephemeral as the next. It wasn’t just me. Everyone I knew was stuck in a feedback loop with themselves. Technology companies stood by, ready to become everyone’s library, memory, personality. I read whatever the other nodes in my social networks were reading. I listened to whatever music the algorithm told me to. Wherever I traveled on the internet, I saw my own data reflected back at me: if a jade face-roller stalked me from news site to news site, I was reminded of my red skin and passive vanity. If the personalized playlists were full of sad singer-songwriters, I could only blame myself for getting the algorithm depressed.

As we left the theater in pursuit of a hamburger, I felt rising frustration and resentment. I was frustrated because I felt stuck, and I was resentful because I was stuck in an industry that was chipping away at so many things I cared about. I did not want to be an ingrate, but I had trouble seeing why writing support emails for a venture-funded startup should offer more economic stability and reward than creative work or civic contributions. None of this was new information—and it was not as if tech had disrupted a golden age of well-compensated artists—but I felt it fresh.

I had never really considered myself someone with a lifestyle, but of course I was, and insofar as I was aware of one now, I liked it. The tech industry was making me a perfect consumer of the world it was creating. It wasn’t just about leisure, the easy access to nice food and private transportation and abundant personal entertainment. It was the work culture, too: what Silicon Valley got right, how it felt to be there. The energy of being surrounded by people who so easily articulated, and satisfied, their desires. The feeling that everything was just within reach.

We wanted to be on the side of human rights, free speech and free expression, creativity and equality. At the same time, it was an international platform, and who among us could have articulated a coherent stance on international human rights? We sat in our apartments tapping on laptops purchased from a consumer-hardware company that touted workplace tenets of diversity and liberalism but manufactured its products in exploitative Chinese factories using copper and cobalt mined in Congo by children. We were all from North America. We were all white, and in our twenties and thirties. These were not individual moral failings, but they didn’t help. We were aware we had blind spots. They were still blind spots. We struggled to draw the lines. We tried to distinguish between a political act and a political view; between praise of violent people and praise of violence; between commentary and intention. We tried to decipher trolls’ tactical irony. We made mistakes.

I did not want two Silicon Valleys. I was starting to think the one we already had was doing enough damage. Or, maybe I did want two, but only if the second one was completely different, an evil twin: Matriarchal Silicon Valley. Separatist-feminist Silicon Valley. Small-scale, well-researched, slow-motion, regulated Silicon Valley—men could hold leadership roles in that one, but only if they never used the word “blitzscale” or referred to business as war.

“Progress is so unusual and so rare, and we’re all out hunting, trying to find El Dorado,” Patrick said.

“Almost everyone’s going to return empty-handed. Sober, responsible adults aren’t going to quit their jobs and lives to build companies that, in the end, may not even be worth it. It requires, in a visceral way, a sort of self-sacrificing.”

Only later did I consider that he might have been trying to tell me something.

Abuses were considered edge cases, on the margin—flaws that could be corrected by spam filters, or content moderators, or self-regulation by unpaid community members. No one wanted to admit that abuses were structurally inevitable: indicators that the systems—optimized for stickiness and amplification, endless engagement—were not only healthy, but working exactly as designed.

The SF Bay Area is like Rome or Athens in antiquity, posted a VC. Send your best scholars, learn from the masters and meet the other most eminent people in your generation, and then return home with the knowledge and networks you need. Did they know people could see them?

I couldn’t imagine making millions of dollars every year, then choosing to spend my time stirring shit on social media. There was almost a pathos to their internet addiction. Log off, I thought. Just email each other.

All these people, spending their twenties and thirties in open-plan offices on the campuses of the decade’s most valuable public companies, pouring themselves bowls of free cereal from human bird feeders, crushing empty cans of fruit-tinged water, bored out of their minds but unable to walk away from the direct deposits—it was so unimaginative. There was so much potential in Silicon Valley, and so much of it just pooled around ad tech, the spillway of the internet economy.

Though I did not want what Patrick and his friends wanted, there was still something appealing to me about the lives they had chosen. I envied their focus, their commitment, their ability to know what they wanted, and to say it out loud—the same things I always envied.

I wanted to believe that as generations turned over, those coming into economic and political power would build a different, better, more expansive world, and not just for people like themselves. Later, I would mourn these conceits. Not only because this version of the future was constitutionally impossible—such arbitrary and unaccountable power was, after all, the problem—but also because I was repeating myself. I was looking for stories; I should have seen a system. The young men of Silicon Valley were doing fine. They loved their industry, loved their work, loved solving problems. They had no qualms. They were builders by nature, or so they believed. They saw markets in everything, and only opportunities. They had inexorable faith in their own ideas and their own potential. They were ecstatic about the future. They had power, wealth, and control. The person with the yearning was me.

could have stayed in my job forever, which was how I knew it was time to go. The money and the ease of the lifestyle weren’t enough to mitigate the emotional drag of the work: the burnout, the repetition, the intermittent toxicity. The days did not feel distinct. I felt a widening emptiness, rattling around my studio every morning, rotating in my desk chair. I had the luxury, if not the courage, to do something about it.

As I stood in the guest entrance, waiting for the stock plan administrator to collect the paperwork, I watched my former coworkers chatting happily with one another in the on-site coffee shop and felt, wrenchingly, that leaving had been a huge mistake. Certain unflattering truths: I had felt unassailable behind the walls of power. Society was shifting, and I felt safer inside the empire, inside the machine. It was preferable to be on the side that did the watching than on the side being watched.

#uncanny valley #books #best of

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loveastrologerankitus-blog · 7 years ago

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pandithsbrao1-blog · 7 years ago

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nofomoartworld · 8 years ago

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Data Everywhere, Statisticians Anywhere

I had the honor to deliver the commencement speech at the UCLA Statistics graduation this past weekend. I’m going to put this here for posterity before my memory tucks it away never to be uttered again. I truncated the speech last minute, so these notes are little more coherent than my delivery.

A big congratulations to all of you! It took a lot of work, a lot of distributions, sampling, and debugging in R to get here today, but you made it. Today’s your day.

For me, it’s weird standing up here seeing all you statisticians. When I was in undergrad, statistics was more of a required course than a field of study. I was an electrical engineering major, but around the end of my third year, I decided it wasn’t for me. I told my parents that I was going to grad school for statistics instead. It was quiet for a while. And my parents, who are all about finding what you love and going for it, asked, “Are you sure about this… statistics thing? Are you going to be able to find a job with that?” When I told my future father-in-law, he wasn’t so thrilled about it either.

So there was a ton of confidence back then in the future of statistics, especially in my family. So was I sure about statistics? Sort of? I didn’t know what I was going to do after school. I knew I liked to poke at data though, deciphering what all those numbers meant. It kind of felt like a magic power. When everyone else ran from distributions, I was having fun.

It’s a different story these days. Statistician is the sexy job of the decade, landing itself in lists of top jobs year after year.

I started to feel the shift during my second year here.

Like I said, I came to UCLA with a vague idea of what I wanted to do with statistics. The most exciting thing to me was the applied nature of it. I could use stat with a bunch of topics. I had statistics education in mind in the beginning. Looking at how we could teach younger kids complex concepts in an engaging way. Rob Gould showed me the possibilities. Then I shifted to data visualization, looking at how we can use interactive charts and graphs to understand data better. How it played a role in the everyday. Mark Hansen showed me the possibilities. Then I found myself at The New York Times making data graphics for the news. Then collaborating with graphic designers and artists for museum exhibits. And this was all as a UCLA stat student. A few years out from the PhD, I’m so thankful that my advisers and professors set me up with strong foundations and then gave me the flexibility to find what I really wanted to do. I’m sure all of you can relate.

Now look at me. I blog for a living. The other day, my wife’s co-worker said if she saw “blogger” on someone’s Tinder profile, she would swipe left in a heartbeat, which means instant rejection for those unfamiliar. So yeah, I have that going for me.

Of course, if we’re gonna be real, we all know you lead with “statistician” in your profile. Everyone’s gonna swipe right when they see “statistics.” It gets people’s attention these days, whether it be for online dating or for a job search.

But back to blogging, the greatest career move ever. I’ve learned a lot by blogging about statistics over the years. It turns out there’s a lot to gain by dealing with trolls and know-it-alls on the internet, which is why I’ll use the rest of my time to bestow upon you the three most important things I’ve learned as a blogger. Hopefully you can use them in your future stat careers, and maybe one day, you too can be a blogger like me.

So let’s get to it.

Lesson 1.

As evidenced by my own career path, statisticians can now work anywhere there is data, and data is everywhere. It’s not just in cubicles, in big tech companies, or academics. With the growing parts of our lives that take place online we produce data like never before, and there are a lot of people, groups, and companies that want to understand these new streams.

Running a site online, I tend to get a lot of recruitment email and business inquiries from these interested people, which gives you a good idea of who’s looking for help with their data. Interest is all across the board, ranging from tech and business analytics, to journalism, publishing, to non-profits and humanitarian efforts, to retail, sports, gaming, government, academic, and all the way to art galleries and children’s museums.

The spectrum for where you can go is really wide. On one end there’s the analytical side of data where you draw quantitative insights for data-driven decisions, and then on the other end, there is the beauty and stories in data that are more qualitative. Looking at what data represents and the social implications of it all. It’s not as easily measured, but equally important. UCLA statistics has given you the skills to make yourself indispensable across the spectrum.

A weird thing though is that the job titles are rarely “statistician.” It’s always data analyst, data engineer, data scientist, data journalist, data something or other. And as new grads, you might feel a little bit of imposter syndrome start to creep in. A feeling that maybe you don’t have what it takes. But you do have it takes. If you look at the job requirements, you almost always see “statistics degree or equivalent.” I think that’s telling of where statistics is headed and what it’s grown into over the years.

Bottom line: You, with the stat degree, can be a data scientist. You can be a data engineer. And yes, you can even be a blogger. The job title doesn’t matter. You’re ready for it and have what it takes to learn anything you don’t know yet, because at the core, you’re a statistician.

Lesson 2.

People care about data. They care about statistics. And it’s not just the nerdy people anymore. It’s not just the people who have data or the ones who analyze it. Millions of people around the world are interested in probabilities, simulations, distributions, space, time, relationships and uncertainty.

Sports commentators talk about analytics during general broadcasts now. ESPN acquired the the rights to political data blog FiveThirtyEight. The New York Times has a prominent data-centric section called The Upshot. Even me, a one-man shop – a statistician working from a home office – is able to prosper. There’s so much data on so many different topics that people are eager to learn about what’s going on in the world or with themselves, from a statistical point of view.

When I started FlowingData, I just wrote to connect with other data people. I had just finished my master’s and I had to move to Buffalo because my wife was starting her medical residency there. It was my outlet and a way to catalog different types of visualization as I tried to finish my PhD remotely. So it was a few hundred people who read at best. Probably fewer. Maybe five. Now it’s on the scale of millions. Just to look at charts and graphs and read about statistics. That’s still crazy to me, even though I’ve been doing it for a while.

A few months back, I used openly available data on mortality from the Centers for Disease Control and Prevention. The data has been free to download for years, as evidenced by the challenging interface to access the data. But millions of people around the world visited FlowingData to interact with charts and graphs. Crazy. It was a similar case for a simulation I made to show the average day for Americans. I used a Monte Carlo method, and the R code was similar to what I used for my dissertation. It got the attention of millions. I won design awards. Me, a statistician.

I mention these not to brag. What I hope that you can see is the scale at which you can reach others who maybe don’t even know they like data. The audience isn’t just other statisticians or other data people anymore. It’s the general public. With so many interested in statistics, that can only mean great things for you.

For me, most importantly, my parents aren’t hesitant about my career path anymore, and my now father-in-law gave me his blessing to marry his daughter.

Lesson 3.

You can use this heightened interest to your advantage. All these new capsules of attention that used to wander elsewhere, you can use it as a way to teach statistics and improve data literacy for people at all levels of stat knowledge.

There’s really no better student than one who is eager to learn. That makes the job easy, because you can give someone the material and they soak it up like a sponge. Just ask my three-year-old who’s nerding out to superheroes every waking minute.

However, the increased interest also means a lot more people who think they know it all because they read an introductory book or article on statistics, or in my case, visualization. They troll you. They talk down to you when maybe they should be asking you for advice.

A younger, ruder version of me would just mutter profanities under my breath. Or, I’d just shake my head and tell myself those sort of people should go learn some real statistics.

That’s the easy way out though, and nobody gets anything out of that interaction. Besides, it’s not what statisticians do. We’re all about rigor and due diligence and paying close attention to the tiny details. Question every single digit.

Where others barely graze the surface, you know how to examine data in depth.

You know that correlation doesn’t equal causation, but you also know how to find out when it does. You know how to find trends and patterns, but you also know when you’re just looking at statistical noise. You know how to lie with statistics, but most importantly, you know how to tell the truth with statistics.

So use these moments of angst that you’ll inevitably come across as a chance to educate others. Especially these days, finding the truth with data is more important than ever. Embrace the responsibility, and we’ll all come out better in the end.

At the same time, it goes the other way. Never stop learning. Accept that you don’t know everything and seize opportunities to collaborate with others across the data spectrum. Sometimes statisticians get stuck in a stat bubble, where analysis and theory rules over everything else data-related. Obviously, that’s our strong suit, so that makes sense, but others have their own strengths, whether it be technical know-how, research in visual perception, experience with data presentation, or telling stories with data. The best work hands-down comes from those with a multi-disciplinary mindset. So keep learning. Data is a lot more fun that way.

Besides, you don’t want to get stuck in that ivory tower. It gets lonely up there. Super cold, dank. Sometimes the toilet breaks unexpectedly and you have to walk all the way down the stairs because there’s no elevator. It’s just not a good place to be.

So there you have it. Three lessons.

Lesson 1. Data is everywhere, and therefore, you can go anywhere and make a difference.

Lesson 2. People care about data, and it’s on a much bigger scale now, which makes statistics that much more exciting.

Lesson 3. With so much attention, it’s your responsibility to teach others about data, which also means we must never stop learning.

And now, all of you can be bloggers too in addition to your future stat careers. Woo.

Whatever you do at the end of the day, when presented with so many possibilities, it’s my hope that you choose to do good with your magic powers. I have little doubt though because you graduated from UCLA statistics.

Tags: commencement

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