Why Big Data Falls Short of Its Political Promise

Via Mashable

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Politics Transformed: The High Tech Battle for Your Vote is an in-depth look at how digital media is affecting elections. Mashable explores the trends changing politics in 2012 and beyond in these special reports.

Big Data. The very syntax of it is so damn imposing. It promises such relentless accuracy. It inspires so much trust –- a cohering framework in a time of chaos.

Big Data is all the buzz in consumer marketing. And the pundits are jabbering about 2012 as the year of Big Data in politics, much as social media itself was the dizzying buzz in 2008. Four years ago, Obama stunned us with his use of the web to raise money, to organize, to get out the vote. Now it’s all about Big Data’s ability to laser in with drone-like precision on small niches and individual voters, picking them off one by one.

It in its simplest form, Big Data describes the confluence of two forces — one technological, one social. The new technological reality is the amount of processing power and analytics now available, either free or at no cost. Google has helped pioneer that; as Wired puts it, one of its tools, called Dremel, makes “big data small.”

This level of mega-crunchability is what’s required to process the amount of data now available online, especially via social networks like Facebook and Twitter. Every time we Like something, it’s recorded on some cosmic abacus in the sky.

Then there’s our browsing history, captured and made available to advertisers through behavioral targeting. Add to that available public records on millions of voters — political consultants and media strategists have the ability drill down as god-like dentists.

Website TechPresident describes the conventional wisdom of Big Data as it relates to elections:

… data is dominating both the study and practice of political campaigns. Most observers readily acknowledge that the 2012 presidential campaign will be decided by the outcome of a handful of battles in just a few key swing states — identified thanks to the reckoning of data scientists and pollsters.

There are two sides to the use of Big Data. One is predictive — Twitter has its own sentiment index, analyzing tweets as 140-character barometers. Other companies, like GlobalPoint, aggregate social data and draw algorithmic conclusions.

But Big Data has a role beyond digital clairvoyance. It’s the role of digital genotyping in the political realm. Simply find the undecided voters and then message accordingly, based on clever connections and peeled-back insights into voter belief systems and purchase behaviors. Find the linkages and exploit them. If a swing voter in Ohio watches 30 Rock and scrubs with Mrs. Meyers Geranium hand soap, you know what sites to find her on and what issues she cares about. Tell them that your candidate supports their views, or perhaps more likely, call out your opponent’s demon views on geranium subsidies.

Central to this belief is that the election won’t be determined by big themes but by small interventions. Big Data’s governing heuristic is that shards of insight about you and your social network will lead to a new era of micro-persuasion. But there are three fallacies that undermine this shiny promise.

Atomic Fallacy

The atomic fallacy is the assumption that just because you can find small, Seurat-like dots in my behavior which indicate preferences, you can motivate me by appealing to those interests.

Yes, I may have searched for a Prius out of curiosity. I may follow environmental groups or advocates on Twitter. I may even have Facebook friends who actively oppose off-shore drilling and fracking. Big Data can identify those patterns, but it still doesn’t mean that Romney’s support of the Keystone pipeline will determine my vote.

There are thousands of issues like this. We care about subjects and might research them online, and those subjects that might lead us to join certain groups, but they aren’t going to change our voting behavior. Candidates can go down a rabbit hole looking for them. Give a child a hammer and everything is a nail; give a data scientist a preference and everything is a trigger.

And then when a candidate gets it wrong — and that’s inevitable — all credibility is lost. This data delinquency was memorialized in a famous Wall Street Journal story a decade ago: “If TiVo Thinks You Are Gay, Here’s How to Set It Straight.”

Big Data still hasn’t solved its over-compensation problem when it comes to recommendations.

Interruption Fallacy

I define the interruption fallacy as the mistaken notion that a marketer or a candidate (the difference is only the level of sanctimony) can rudely insert his message and magically recalibrate deeply ingrained passions.

So even if Big Data succeeds in identifying subjects of paramount importance to me, the interruption fallacy makes it extremely unlikely that digital marketing can overcome what behavioral psychologists call the confirmation bias and move minds. Targeting voters can reinforce positions, but that’s not what pundits are concerned about. They’re opining that Big Data has the ability to shift undecideds a few points in the swing states.

Those who haven’t made up their minds after being assaulted by locally targeted advertising, with messaging that has been excruciatingly poll-tested, are victims of media scorch. They’re burned out. They are suffering from banner blindness. Big Data will simply become a Big Annoyance.

Mobile devices pose another set of challenges for advertisers and candidates, as Randall Stross recently pointed out in The New York Times. There’s a tricky and perhaps non-negotiable tradeoff between intrusiveness and awareness, as well as that pesky privacy issue. Stross writes:

Digital advertisers working with smartphones must somehow make their ads large enough to be noticed, but not so large as to be an interruption. And they must be chosen to match a user’s interests, but not so closely as to induce a shiver.

But that shiver is exactly what Big Data’s crunching is designed to produce– a jolt of hyper-awareness that can easily cross over into creepy.

And then there’s the ongoing decline in the overall effectiveness of online advertising. As Business Insider puts it, “The clickthrough rates of banner ads, email invites and many other marketing channels on the web have decayed every year since they were invented.”

No matter how much Big Data is being paid to slice and dice, we’re just not paying attention.

Narrative Fallacy

If Big Data got its way, elections would be decided based on a checklist that matched a candidate’s position with a voter’s belief systems. Tax the rich? Check. Get government off the back of small business? Check. Starve public radio? Check. It’s that simple.

Or is it? We know from neuromarketing and behavioral psychology that elections are more often than not determined by the way a candidate frames the issues, and the neural networks those narratives ignite. I’ve written previously for Mashable about The Political Brain, a book by Drew Westen that explains how we process stories and images and turn them into larger structures. Isolated, random messages — no matter how exquisitely relevant they are — don’t create a story. And without that psychological framework, a series of disconnected policy positions — no matter how hyper-relevant — are effectively individual ingredients lacking a recipe. They seem good on paper but lack combinatorial art.

This is not to say that Big Data has no role in politics. But it’s simply a part of a campaign’s strategy, not its seminal machinery. After all, segmentation has long enabled candidates to efficiently refine and target their messages, but the latest religion of reductionism takes the proposition too far.

And besides, there’s an amazing — if not embarrassing — number of Big Data revelations that are intuitively transparent and screechingly obvious. A Washington Post story explains what our browsing habits tell us about our political views. The article shared this shocking insight: “If you use Spotify to listen to music, Tumblr to consume content or Buzzfeed to keep up on the latest in social media, you are almost certainly a vote for President Obama.”

Similarly, a company called CivicScience, which offers “real-time intelligence” by gathering and organizing the world’s opinions, and that modestly describes itself as “a bunch of machines and algorithms built from brilliant engineers from Carnegie Mellon University,” recently published a list of “255 Ways to Tell an Obama Supporter from a Romney Supporter.” In case you didn’t know, Obama supporters favor George Clooney and Woody Allen, while mysteriously, Romney supporters prefer neither of those, but like Mel Gibson.

At the end of the day, Big Data can be enormously useful. But its flaw is that it is far more logical, predicable and rational than the people it measures.

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