Category: Politics

The revolution will be at Starbucks

One of the biggest shocks about life in The Zone (11/9/2016-present) is how often Starbucks makes the news. Just a couple days after the election, a group of patriots, organizing around the hashtag #TrumpCup, decided to show solidarity with their big wet boy, subverting the sacred ordering ritual to trick baristas to shout “Iced Frappucino for Trump”. Then, there was the everyday-in-America story of a few young men thrown out—by the police—of a Philadelphia Starbucks for the mere act of being black in public. And now gloriously quixotic former CEO Howard Schultz is considering a third-party run for president. How has Trumpism turned America’s top coffee chain into a battleground?

I think I know. Starbucks is a looking glass, and when we gaze into it, we see what we want to. Allow me to explain.

We yet again live in a time where the public commons is contracting. It is not so much being “enclosed” (as it was in Georgian England) as neglected by the inexorable logic of austerity (as it happens, the key plank of Schultz’s platform). Even public libraries—a radical, and incredibly impactful, experiment in architecture and government—are at risk; President Trump has sought to eliminate federal spending on libraries, and they are under threat both in communities small and large. Faced with disappearing public commons, we turn increasingly to private simulcra of the park, the library, the school or university, and for some, a busy Starbucks will have to do.

Starbucks has another thing going for it. The product is really not bad, and of surprisingly uniform quality. While coffee snobs turn their noses up at the burnt-tasting drip coffee, the espresso drinks are quite good if not always great. The production of a large menu of high-quality, complex, labor-intensive goods, daily, at 14,000 locations across the US, is an incredible feat of logistics. US social welfare programs, increasingly administered by a patchwork of hostile state governments, do not come off well in comparison to the fungible, always-available Starbucks latte. It is easy to see why. Starbucks is embedded in an all-encompassing matrix of market capitalism, but internally, it is a command economy, one in which no store can be left behind. It is hard to even imagine living in an America where say, welfare or health care services are provided to citizens with the same efficiency of Starbucks manager requisitioning a case of oat milk.

At least that’s what I see when I look at Starbucks. But, as #TrumpCup shows, others see something different: the masses of Americans not moved—if not outright repelled—by the mixture of petty grievances and white identity politics that animates President’s Trump’s base. The libs (as we’ll call them) are a diverse group, better defined by exemplars—sometimes, right-wing media caricatures—than prototypes, and one key lib exemplar is the Starbucks barista. The barista is probably young, and possibly urban. Perhaps they have a college education and have taken the job for the health care benefits the state does not provide. Maybe they even share former CEO Schultz’s tepid opposition to President Trump.

If this wasn’t enough to forever code the barista as the Other, there is also a whole new language, not quite English, to learn. A small coffee is unexpectedly “tall”; a large is a “venti”; a “macchiato” is something else entirely. Mastering this language gives the customer the power to summon strange and fantastic beasts: the “blonde espresso”, or if the stars are properly aligned, the “spiced sweet cream nariño 70 cold brew”.

And, perhaps most importantly, the barista is a captive audience. The barista has a manager, and yes, you really can ask to speak to them. For the #TrumpCup Republican, this is a potent brew, a hierarchy in which they stand above the Other, the perfect victim for a bit of everyday cruelty and meaningless self-gratification.

It was probably inevitable that the of the most ubiquitous corporations in American life was going to ultimately come to index something, and where I see the state’s abdication of responsibilities inherent in the social contract, others just see a snot-nosed, underemployed 25-year-old who would rather not be working this job forever. In conclusion, Starbucks is a land of contrasts, and will remain so until we resolve the contradictions inherent in American society.

What to do about the academic brain drain

The academy-to-industry brain drain is very real. What can we do about it?

Before I begin, let me confess my biases. I work in the research division of a large tech company (and I do not represent their views). Before that, I worked on grant-funded research in the academy. I work on speech and language technologies, and I’ll largely confine my comments to that area.

[Content warnings: organized labor, name-calling.]

Salary

Fact of the matter is, industry salaries are determined by a relatively-efficient labor market. Academy salaries are compressed, with a relatively firm ceiling for all but a handful of “rock star” faculty. The vast majority of technical faculty are paid substantially less than they’d make if they just took the very next industry offer that came around. It’s even worse for research professors who depend on grant-based “salary support” in a time of unprecedented “austerity”—they can find themselves functionally unemployed any time a pack of incurious morons seem to end up in the White House (as seems to happen every eight years or so).

The solution here is political. Fund the damn NIH and NSF. Double—no, triple—their funding. Pay for it by taxing corporations and the rich, or, better yet, divert some money from the Giant Death Machines fund. Make grant support contractual, so PIs with a five-year grant are guaranteed five years of salary support and a chance to realize their vision. Insist on transparency and consistency in “indirect costs” (i.e., overhead) for grants to drain the bureaucratic swamp (more on that below). Resist the casualization of labor at universities, and do so at every level. Unionize every employee at every American university. Aggressively lobby Democrat presidential candidates to agree to appoint the National Labor Relations Board who will continue to recognize graduate students’ right to unionize.

Administration & bureaucracy

Industry has bureaucratic hurdles, of course, but they’re in no way comparable to the profound dysfunction taken for granted in the academic bureaucracy. If you or anyone you love has ever written a scientific grant, you know what I mean; if not, find a colleague who has and politely ask them to tell you their story. At the same time American universities are cutting their labor costs through casualization, they are massively increasing their administrative costs. You will not be surprised to find that this does not produce better scientific outcomes, or make it easier to submit a grant. This is a case of what Noam Chomsky has described as the “neoliberal confidence trick”. It goes a little something like this:

  1. Appoint/anoint all-powerful administrators/bureaucrats, selecting for maximal incompetence.
  2. Permit them to fail.
  3. Either GOTO #1, or use this to justify cutting investment in whatever was being administered in the first place.

I do not see any way out of this situation except class consciousness and labor organizing. Academic researchers must start seeing the administration as potentially hostile to their interests, and refuse to identify with, or (or quelle horreur, to join) the managerial classes.

Computing power & data

The big companies have more computers than universities. But in my area, speech and language technology, nearly everything worth doing can still be done with a commodity cluster (like you’d find in the average American CS departments) or a powerful desktop with a big GPU. And of those, the majority can still be done on a cheap laptop. (Unless, of course, you’re one of those deep learning eliminationist true believers, in which case, reconsider.) Quite a bit of great speech & language research—in particular, work on machine translation—has come from collaborations between the Giant Death Machines funding agencies (like DARPA) and academics, with the former usually footing the bill for computing and data (usually bought from the Linguistic Data Consortium (LDC), itself essentially a collaboration between the military-industrial complex and the Ivy League). In speech recognition, there are hundreds of hours of transcribed speech in the public domain, and hundreds more can be obtained with a LDC contract paid for by your funders. In natural language processing, it is by now almost gauche for published research to make use of proprietary data, possibly excepting the venerable Penn Treebank.

I feel the data-and-computing issue is largely a myth. I do not know where it got started, though maybe it’s this bizarre press-release-masquerading-as-an-article (and note that’s actually about leaving one megacorp for another).

Talent & culture

Movements between academy & industry have historically been cyclic. World War II and the military-industrial-consumer boom that followed siphoned off a lot of academic talent. In speech & language technologies, the Bell breakup and the resulting fragmentation of Bell Labs pushed talent back to the academy in the 1980s and 1990s; the balance began to shift back to Silicon Valley about a decade ago.

There’s something to be said for “game knows game”—i.e., the talented want to work with the talented. And there’s a more general factor—large industrial organizations engage in careful “cultural design” to keep talent happy in ways that go beyond compensation and fringe benefits. (For instance, see Fergus Henderson’s description of engineering practices at Google.) But I think it’s important to understand this as a symptom of the problem, a lagging indicator, and as part of an unpredictable cycle, not as something to optimize for.

Closing thoughts

I’m a firm believer in “you do you”. But I do have one bit of specific advice for scientists in academia: don’t pay so much damn attention to Silicon Valley. Now, if you’re training students—and you’re doing it with the full knowledge that few of them will ever be able to work in the academy, as you should—you should educate yourself and your students to prepare for this reality. Set up a little industrial advisory board, coordinate interview training, talk with hiring managers, adopt industrial engineering practices. But, do not let Silicon Valley dictate your research program. Do not let Silicon Valley tell you how many GPUs you need, or that you need GPUs at all. Do not believe the hype. Remember always that what works for a few-dozen crypto-feudo-fascisto-libertario-utopio-futurist billionaires from California may not work for you. Please, let the academy once again be a refuge from neoliberalism, capitalism, imperialism, and war. America has never needed you more than we do right now.

If you enjoyed this, you might enjoy my paper, with Richard Sproat, on an important NLP task that neural nets are really bad at.