Singing and Learning in Comfortable Obscurity
Hello there, dear readers,
It is kind of you to invite me into your inbox today. But, if for whatever reason this note comes as an uninvited guest, you can unsubscribe here.
So, I recently sang a song about Democracy’s Data. It’s set to one of my favorite old-timey tunes, “The Erie Canal Song,” which I learned only late in my life was not actually so old-timey, but was instead made to sound old-timey in the early twentieth century, at a moment when new transportation technologies were displacing the mules and drivers the song celebrated. Alas.
I am not sharing this clip because I am particularly proud of the lyrics—indeed, some of the rhymes are audaciously, and hopefully comically, slip-shod. Nor am I sharing this clip so you can see the generosity with which my co-panelists humored me—although, here and throughout the entire event, Ronteau Coppin and Alex Hanna gave me the great gift of playing along and thinking along, and even dancing along.
On that note: Here’s an example of Ronteau thinking along, asking just the right question about how and why people tell the stories they do about themselves to the census. And here’s Alex thinking along, talking about what gets all lumped together as “bias” in discussions of artificial intelligence and machine learning, to the detriment of our understanding of how all datasets are shaped by the values of their creators. She points to this paper with Morgan Klaus Scheuerman and Emily Denton, “Do Datasets Have Politics,” which is well worth a read!
No, I am sharing this clip, because I really like singing for people and you, dear readers, are my semi-captive audience.
I have always liked singing, but I was for a long time not very good at it. I recall trying to take a few semi-formal lessons in college from a good friend. I wanted my singing in church to be less painful to others. It helped, a little.
But mostly, my capacity for singing (and confidence in that capacity) grew from years—decades!—of singing alongside my partner, Lucas Bouk, an opera singer. The extraordinary thing about singing next to an opera singer is that no one else can hear you. You are drowned out entirely, and so free to sing freely, to experiment, mimic, and adapt. In other words, singing next to Lucas, I could hide in his billowing sonic cloud, and slowly, slowly get better—with no fear of embarrassment. It was a perfect learning environment.
To learn, we usually need teachers and guidance. We need people to observe us, adjust our technique, correct our errors, and expose us to new or better approaches. Then, we usually need space to try things out and make mistakes. (When I see kids in NYC, like my own child, learning to play ball in busy parks, I mark their bravery. There are so many people watching!)
Here’s another way to illustrate this point: I speak mediocre-to-poor German, but I attained that level of fluency, in part, by leaving Germany.
My child had been in kita there (an amazing daycare where everyday the kids pushed their parents out the door at dropoff). By the time left, German was as much his language as English. So when we returned to the U.S., I took to speaking with him in my bad German, mostly because I did not want to share family business or parent in public—and German (especially my ungrammatical version of it) served as a cipher. I spoke so much German, confident that no one around me would know how bad I was—it was the linguistic equivalent to singing next to Lucas. And, sure enough, when we returned to Berlin a few years later, my German had actually improved, a lot.
I was pleased to see this week that the political philosopher Danielle Allen began a series of essays for the Washington Post laying out a plan for rebuilding American democracy.
Allen recently ran in the Democratic primary for governor of Massachusetts, so she can speak not only as a theorist, but also as a practitioner of modern politics. She also chaired a remarkable and important commission that published Our Common Purpose: Reinventing American Democracy for the 21st Century. The commission worked assiduously to cross partisan lines and piece together a series of recommendations that could make a real difference. (I tip my hat to my friend, danah boyd, who served on Allen’s commission and introduced me to it.)
I will admit that I am a bit skeptical concerning Allen’s framing in this first WaPo essay. I find it hard to believe that Facebook or the platforms “broke our democracy.” But the solutions that Allen and her commission have put forward show promise nonetheless. They might work! And as readers of this newsletter or Democracy’s Data will know, I have over the last couple years been converted whole heartedly to one of the commission’s first recommendations: that the U.S. House should be enlarged.
Speaking of the Washington Post…
Democracy’s Data got reviewed!
(If you’re a reader who gets a physical copy of the Post, I’d love to know if/when this appeared in print. I suspect it would have been Saturday or today, Sunday.)
In her review, Karen Sandstrom captures my tone very well: Bouk, she explains, “writes with genuine, even geeky affection for his subject.” Genuine AND geeky! Check AND check!
The essay includes the necessary caveat that this topic and this book is not so boring as it seems like it should be. (This is my brand!) Sandstrom writes:
“Solid storytelling chops and a friendly tone help Bouk convince readers who might question just how interesting a book about the census can be. Surprise — it can be! In the hands of someone who understands it, the census is a mirror of the country’s ideals, values, flaws and attributes.”
And it ends on an affirming note:
“Bouk uncovers the great paradox about the decennial count: that it is an impossibly large and messy task, but also an awe-inspiring achievement. As he puts it, ‘Every census is a remarkable accomplishment, a glorious dream, and a serious slog.’ He wants us to believe that achieving a better census is possible, and to care whether it improves. Democracy’s Data makes the case.”
Also, so long as I am bragging. I was “Tiger of the Week,” thanks to David Marcus, who has read both of my books with insight, enthusiasm, and care. I love what the Princeton Alumni Weekly chose to use as its tagline: “I look at numbers and databases the way people look at poems and paintings.” I do, indeed!
I’ve been working up a blog post about two really, really important books that I read recently. Beth Popp Berman’s Thinking Like an Economist is really mind-bending and world-shaking: it is the sort of book that made the society I have grown up in suddenly make sense. It is not a how-to book, but rather an explanation of how a particular economic style of thinking has thoroughly shaped the American policy conversation, sacrificing other values (like solidarity) to the cult of efficiency.
The other book is by Jessie Singer and it’s called There Are No Accidents. It too made things clear to me that should have been clear before, and it makes the case that if we wanted to, we could in fact build a society that allocated harm more equally, and more than that, reduced harm generally. I have many more thoughts, which is why I am promising a blog post over at shroudedincloaksofboringness.com soon. But in the meantime, read this revealing interview with Jessie at Mother Jones.
Singer, in the book and the interview, thinks seriously about storytelling. A central question is: how do we explain the way the world repeatedly deals out “bad luck” to some folks and not to others? In this interview, they explain:
“Policy decisions, unregulated corporate power, and the differential distribution of resources lead to risk unequally distributed across the US. These are not accidents. These are predictable, preventable events—the results of how we allocate safety across the country.”
And:
“The point of the accident narrative is to maintain and defend the system as it is, to define the incidents as an aberration, not a predictable result.”
Singer’s larger point resonates with my earlier claims about learning. Our goal should not be to prevent mistakes or mishaps. Rather, we should build systems and environments that allow people to make mistakes—to learn!—and also to recover. “To err is human” Singer says. “Mistakes are inevitable, but our failure to protect people is not.”
I encourage you to read the interview, and the book!
Since, this newsletter edition began with singing, I will end it as well on a musical note.
If you have not already, check out Penny Lane’s documentary (on HBOMax) Listening to Kenny G.
Penny is a friend, but this is not friendship speaking: Penny Lane is a documentary filmmaker who tackles big questions and opens up big ideas through small/strange/obscure stories. I think she’s a genius. I first became convinced of this when viewing Nuts, in which she tells the story of a huckster who sells a healing potion purportedly made from goat testicles, bringing to life a historical oddity through a series of commissioned animations and archival photography. Penny made footnotes for the show which highlight the deep uncertainty in how documentary film does and doesn’t present the truth.
I was prepared to like the Kenny G doc less (much less) than I did. But Penny does that thing that she always does: she approaches her subjects with respect and curiosity, and they reveal themselves in startling ways. More than that, I love how the film acknowledges the critical derision that came with Kenny G’s success, while still honoring the fact that loads of people love his music: it means something to them. I won’t give anything away, but I will say the doc starts out with Kenny G saying something really shocking about his relationship to music, and that about half-way through it takes a very unexpected jaunt to China that just blew me away.
Well, that’s all for now! Thanks for joining me for these musings on music and learning.
Keep an eye out for Democracy’s Data this week. The book launches on Tuesday! Send me photos of the book out in the wild!
take care all,
Dan