“Information” is a pretentious word. So are its kin, “data” and “data points” (???) If bad writing is about things that are not concrete, then info-data is its muse.
It’s a fancy word for “stuff,” in the end. Imagine the following slogans recast to show how trite info-data is:
-“the stuff age”
Some uses – “mobile data” – are more concrete. But look: it’s scary that a basic synonym probes the shallowness of info-data. It’s about air, about ideas that are festooned with flowery words like “solutions” and “digital” that themselves are blank, yet somehow add more character (“solution ” is at least evaluative; info-data is nothingness, less material even than “stuff” and its vivid homophones).
Why resort to info-data? Because computers and the industries around them lack a clear reason for existing.
The Internet is an outgrowth of the telegraph that has done as much bad (spying, fake social media personae, argument for no reason, stress over minor things like email) as good (new tools for writing, reading, and chatting).
Computers themselves are often justified as “productivity” tools, but “productivity” is a ritual, not a result. New jobs and issues are created to feed the hunger for “productivity,” but it can’t be sated.
Like the Internet, financial services, and 100-hour workweeks, computers keep recreating the need for productivity, rather than satisfying its requirements. We’re solving a problem that isn’t there – maybe that’s why “solutions” is meaningless and a crutch.
Info-data is even more generic and, well, insincere. Something like info-data has always existed for humans, but it has enjoyed a moment now that it is associated with smartphones and PCs. Are “analog” media like books repositories of info-data? Why didn’t the invention of the codex form kick off The Information Age?
Whereas books have clear boundaries and purposes – a novel for leisure reading; a textbook for education – info-data media do not. The Web has no purpose, and computers, while no generating info-data, are little more than extensions of analog tools for gaming and writing.
The info-data lingo makes computers and the Internet seem profound, like clear breaks with what came before. But this language is vague, and it reveals summering so ordinary that terms for the most ancient, mundane things – information, data – have to be put into service because there’s nothing else there.
Data data data. Big data. Granular data. You won’t need gasoline, or a Tesla – you are data-driven.
It’s hard to get away from “data” (or its cousin, “information”). What does the data say? Does the information tell us anything?
I don’t know; I didn’t realize that these things were sentient beings that can “say” phrases and “tell” us about ideas. And their vagueness – what IS data? Does it have important physical characteristics or is it part of the world’s growing layers of abstraction, under which manual work and tangible items are obscured and devalued?
The issue with the world’s data obsession is not that it necessarily produces bad commentary, bad writing, or bad sociological analysis. Still, it does do that. The data told us that, without any Entente/American troops on German soil in 1918, Germany maybe shouldn’t have surrendered. Who knows what their odds of victory were?
It’s not all bad news. Being data-driven leads to big, nice-looking, slow-loading webpages such as Vox, The Verge, and FiveThirtyEight, and their newsrooms full of tone-deaf white guys.
But trusting data over all else is to shirk social responsibility. It’s to wring one’s hand in faux-seriousness to some intangible ideal – data, numeracy, whatever you want to label it – that really plays a role analogous to god (but that would be frowned upon by data-driven crowds, natch). It becomes the agent, something unstoppable and immutable, while the writer becomes less accountable – after all, she’s just letting the data talk, as if channeling the Burning bush.
What a naive viewpoint. Using data is a matter of interpretation, and many writers don’t have the chops for it. It’s no coincidence that two good pieces (one from The New Republic, another from Quartz) bemoaning the rise of data journalism were published on the same day (today). They point out this gap, plus they get at a bigger issue – that even data-driven writing is opinion, with research structured to favor a particular point. Problematic literature is sidebarred or ignored altogether – it basically has to be, whether the writer intends to do so or not, given the sheer volume of material out there.
It’s easy to see why data-driven writing has cachet on the Internet, with its somewhat technologist demographics. And maybe if FiveThirtyEight gets this year’s NCAA brackets right, it’ll have done a good deed – I’m not saying data journalists aren’t making valuable contributions. But their relentless drive toward “the future” of journalism or “journalism for the digital era” (how long have these trope been around? They’re fucking exhausting), like all progressivism, is often overzealous and blinkered.
I mean, look at education. What has decades of data-driven teaching, testing, and planning done? Billions in profits for private corporations, miserable students with their mouths taped shut, unions busted up, laughable Common Core standards…administrators have spent the past 30 years trying to close an “achievement gap” that doesn’t exist, ignoring poverty in their drive to throw data-driven strategies at things such as SAT testing that have little redeeming social value.
What does that show? Well, data itself isn’t important. It’s what people do with it, how they interpret it. How could one not see the broader U.S. trend toward privatization and inequality in the data-driven education craze, except with actions sanctioned by the authority of “the data says ___”? I worry that writing is going to become like this too, with terrible data-driven drivel designed for machines and condoned by the godlike vehicle of “technology.”
There’s been a recent surge in attention given to a relatively obscure British journalist’s thoughts on headline writing. “Betteridge’s Law” is the informal term for the argument that any (usually technology-related) headline that ends in a question mark can be answered “no.” Betteridge made his original argument in response to a TechCrunch article entitled “Did Last.fm Just Hand Over User Listening Data to the RIAA?”
The reason that so many of this rhetorical questions can be answered “no” comes from their shared reliance on flimsy evidence and/or rumor. The TechCrunch piece in question ignited controversy and resulted in a slew of vehement denials from Last.fm, none of which TechCrunch was able to rebut with actual evidence. John Gruber also recently snagged a prime example in The Verge’s review of Fanhattan’s new set-top TV box, entitled “Fan TV revealed: is this the set-top box we’ve been waiting for?”
So we know what Betteridge’s Law cases look like in terms of their headlines, which feature overzealous rhetorical questions. But what sorts of stylistic traits unite the body of these articles? Moreover, why do journalists use this cheap trick (other than to garner page-views and lengthen their comments sections), and what types of arguments and rhetoric do they employ in following-up their question? I am guilty of writing a Betteridge headline in my own “Mailbox for Android: Will Anyone Care?,” which isn’t my strongest piece, so I’ll try to synthesize my own motivations in writing that article with trends I’ve noticed in another recent article that used a Betteridge headline, entitled “With Big Bucks Chasing Big Data, Will Consumers Get a Cut?”
Most visibly, Betteridge’s Law cases employ numerous hedges, qualifiers, and ill-defined terms, some of which are often denoted by italics or scare-marks. By their nature, they’re almost invariably concerned with the future, which explains the feigned confusion inherent in the question they pose. That is, they act unsure, but they have an argument (and maybe even a prediction to make). Nevertheless, they have to hedge on account of the future not having happened yet (the “predictions are hard, especially about the future” syndrome), or, similarly, use conditional statements.
I did this near the end of my Mailbox article, saying “This isn’t a critical problem yet, or at least for as long as Google makes quality apps and services that it doesn’t kill-off abruptly, but it will make life hard for the likes of Mailbox and Dropbox.” My “yet” is a hedge, and my “it will” is the prediction I’m trying to use to establish more credibility. In The Verge article linked to by Gruber, the authors say “IPTV — live television delivered over the internet — is in its infancy,” strengthen that with “Meanwhile, competition for the living room is as fierce as it has ever been,” and then feebly try to make sense of it all by saying “At the same time, if it matches the experience shown in today’s demos, Fan TV could win plenty of converts.”
Delving into the aformentioned article about “big data,” we find similarly representative text:
- “You probably won’t get rich, but it’s possible”
- “But there’s a long road ahead before that’s settled”
- “Others aren’t so sure a new market for personal data will catch on everywhere”
- “not as much is known about these consumers”
- “That’s a big change from the way things have worked so far in the Internet economy, particularly in the First World.”
- “big data”
This headline is really a grand slam for Betteridge’s Law. Simply answering “no” means that you believe that corporations specializing in data-collection won’t be all that generous in compensating their subjects for data that they’ve possibly given up without even realizing that they’ve done so. After all, lucid arguments have been made about how Google in particular could be subtly abetting authoritarianism via its data collection, which if true would constitute a reality directly opposed to the fairer, more democratic world proposed by advocates of data-related payments. To the latter point, Jaron Lanier has argued for “micropayments” to preserve both middle-class society and democracy in the West.
The article examines mostly nascent data-collection and technology companies and ideas whose success or failure is so far hard to quantify and whose prospects remain unclear. Accordingly, the author must use filler about the weak possibility of becoming rich, the cliché of a “long road ahead,” and the admission that many consumer habits are a black box and that maybe not all consumers are the same. Even the broad “consumers” term is flimsy, to say nothing of the nebulous term – “big data” – that the article must presuppose as well-defined (I have argued that it is not so well-defined) to even have a workable article premise.
For additional seasoning, the article resorts to the outmoded term “First World” (a leftover from the Cold War) and the ill-defined “Internet economy.” I think I know what he means with the latter: the targeted-ad model of Google, Amazon, and Facbook. But the vacuity of the term “internet” leaves the door open: would Apple’s sale of devices that require the internet for most functions count as part of the “internet economy,” too, despite having a different structure in which users pay with money rather than data?
Like many Betteridge-compliant headlines, the accompanying article isn’t a contribution to any sophisticated discussion of the issues that it pretends to care about. Hence the teaselike question-headline; Betteridge’s Law cases pretend that they’re engaging in high discourse, perhaps in the same way that the valley girl accent – riddled with unusual intonations cadences that throw off the rhythm of its speaker’s sentences and draws attention away from content – pretends it is partaking in real conversation. Perhaps we really should bring back the punctus percontativus so we can see these rhetorical questions for what they really are.
What is “big data?” Good question. Its name suggests that it describes a large pile of something, collected and organized by a company: numbers, autocorrect mistakes, search queries, anything
More practically, Big Data is often the tagline for aggregative software services that do things like predict fluctuations in airline ticket prices, or track video-viewing habits on Netflix. It collects and stores all of this data for retrieval later, and then uses it to try and predict outcomes. Accordingly, phenomena like House of Cards (based on painstaking research of Netflix habits), the 2008 Wall Street meltdown, and the installation of (mostly unmonitored) video cameras in seemingly last corner of Chicago are good examples of Big Data at work. What’s so great about any of that? To be fair, Google and especially Facebook can be regarded as leading Big Data collectors, too, but in both cases, the benefits they’ve provided are often matched by the privacy infringements, security concerns, and general Internet fatigue that both of those “free” services can cause.
The next time that some TED speaker, Amazon-bestselling author, or columnist tells that we are living in a uniquely disruptive and transformative era and that (this time, anyway) Big Data is the reason why, your should be skeptical. Big Data, as understood in the tech media, is basically a way to collect data, infringe privacy, and, in return, provide services (often “free” – be wary of anything that’s “free,” because it usually has a hidden price in the data it collects). Its Bigness is a byproduct of higher network speeds and cheaper, easier cloud storage. Other than size, its data collection targets (what we do, watch, buy, sell, etc) are old-hat, nothing that would shock even the the Attic Greeks, who kept their own meticulous manual measurements (Small Data?) of diet and exercise regimens. There’s nothing new out there.
But Big Data is a Big Deal because it has no drawbacks for the parties that promote it. As Anthony Nyström pointed out recently, the idea of Big Data is so nebulous that even if it fails to deliver, then the speakers and evangelists who have sold tons of books and speeches on its account can simply say that the “data is bad” or that it’s your problem. This is what happens when people are allowed to get away with generalities and not pressed to be more concrete in their assertions. But it also highlights how flimsy the notion of “data” is, anyway. “Data-driven” and “the data” are terms that have become almost sacrosanct in the United States in particular. Elon Musk’s recent spat with the NYT over its “fake” review of the Tesla S is a good case in point. The reviewer-driver, Musk asserted, was simply lying when he said that the car had an unreliable battery that couldn’t hold charge in cold weather, and “the data” that Musk’s company had collected from the car would shatter the reviewer’s soft nonsense. No such thing happened. If anything, Musk’s torrent of data only inflamed the he-said/he-said debate.
Look: data is not some god or force of nature. It’s manmade, and handled by humans who have to then make sense of it. If you have a bad analyst, or too much data, then the entire operation can be compromised. Would Apple have been better off collecting more data about tablets before it made the iPad, rather than simply following Steve Jobs’ gut assertion that users needed to be guided in what they wanted? It’s debatable whether more data even leads to better decisions. And even in cases where the amount of data isn’t an issue, its quality can become one, too, even if it seems like good data on the surface. Data about lower crime rates in certain neighborhoods could lead one to think that crime wasn’t an issue there, despite having the obvious blindspot that many crimes go unreported and as such are not part of “the data.”
But that can be fixed, you might say – we just need better surveillance and better tools to give us better data. More technological progress (I disagree with the entire notion of “progress,” but I’ll let that slide for another time) you might say. OK: but at what cost? The same sort of nonsensical, overexcited language that drives a lot of the press about Big Data also drives the posts of many tech bloggers who advocate for rollbacks on privacy or any notion of any unconnected world. Jeff Jarvis thinks you shouldn’t be worried about losing your privacy, since publicness makes our lives better. Nick Bilton just can’t stand it that electronic devices can’t be used during airplane takeoff, as if those few moments of not being able to refresh Gmail or Facebook were critical to the betterment of humanity.
In these cases, as with the debate about Big Data and all of its privacy entanglements, it’s not so much the content of the assertion as it is the attitude with which it is made. It rings of “I know best” and has little regard for niceties like privacy and offline existence in particular. Don’t want to be part of “the data” made by Big Data and its tools? Too bad, that aforementioned attitude would say. What’s worse, the price of this “progress” toward more data and bigger data is often hidden because so many of Big Data’s tools are “free.” To be fair, paid services like Netflix are also part of the overall Big Data dredge. But general consumer awareness of how and why their data is being collected, whether by a free or paid service, appears to be low, and that’s too bad.
Slate has already worried that Big Data could be the end of creativity. I disagree, but I’m glad to see at least some pushback on the Big Data train – it isn’t clear that Big Data, despite all of its pretenses, is giving, or can give, us what we really want or need. Big Data, I think, assumes a certain linearity in how humans operate – that we show a machine, by way of what we click or like or +1, what we truly want, and that that input can be transformed into a high-quality output, like a certain type of content. I admit to making some data-based posts myself, but if I were to make this entire blog a slave to the data it collects, it would probably look like a super-geeky version of BuzzFeed, which, while fun for a while, would preclude some of the longer or more detailed posts that provide variety and often are surprise hits (at least from my modest perspective). So I’m sticking with just a modest, consciously restrained dose of data for now, something I think that those aforementioned Greeks would approve of.