While the 2012 re-election of America’s first African-American President signaled resurgence in support for social liberalism, it also announced a sea change in our media culture: the triumph of polling statisticians over the “go with your gut” prognostications of traditional punditry. On Election Day, Nate Silver finally burst the bubble of such notable blowhards as Joe Scarborough, Peggy Noonan, and most dramatically Karl Rove, whose on-air denial of the election results and subsequent dismissal by Fox News’s election team quickly became YouTube spectacle. Meanwhile, Silver published quantitative analyses of how minorities’ limited access to voting booths would affect Obama’s chances of victory; the Obama campaign itself received plaudits for its use of statistical algorithms to identify likely voters and encourage turnout. It seemed the era of Big Data had finally come not just to political coverage, but to political activism.

On the eve of the 2014 midterm elections, it is natural to ask what their significance will be. Given the dangers the U.S. ship of state is currently navigating, from the global health crisis of Ebola, the foreign policy nightmares of Syria and Ukraine, racial tensions in Ferguson, MO, and an economic recovery which seems to be helping only the already wealthy, one would expect we, the voting public, would have decisions of consequence to make. However, we don’t seem to care. Even for a midterm election year, polls indicate that likely voter turnout will not only be low, but that Americans have a record-breaking lack of confidence in the governing ability of either of the two major political parties. If anything, 2014 looks to be memorable for its context-defying meaninglessness.

The sources for this apathy are manifold. Certainly Republican obstructionism has played a role: the GOP has made clear its commitment to governmental impairment since taking over the House in 2010. Systemic political dysfunction in the form of gerrymandering is also salient, undermining our democracy by letting our politicians pick their voters rather than the other way around. It also reflects a well-documented collapse in Americans’ confidence in many prominent social institutions. But seldom emphasized in these analyses is the abysmal and worsening position occupied by mass media —the very institution responsible for informing public opinion in the first place.

It wasn’t supposed to be this way. If 2012 was the tipping point for media-savvy statisticians, 2014 is the first cycle where their reign is undisputed. Silver launched the new fivethirtyeight.com under ESPN’s auspices with a self-described manifesto ending with the line “It’s time for us to start making the news a little nerdier.” Other bloggers such as Ezra Klein proudly crow their “wonky” credentials. Wasn’t our media shocked back into shape by Silver’s data-centric journalism?

Apparently not. Data journalism has failed to mitigate the feedback loop governing Americans’ distaste for mass media, and has become a manifestation of the very social phenomenon it was meant to dissect: the bifurcation in media culture between fear mongering and colorless prognostication. The real problem with our media wasn’t that it was bad at predicting elections (although it was)—it’s that it spends so much time on predicting elections at all, as opposed to moderating and shaping a national debate on what is at stake at the ballot box. Statisticians like Silver have helped eliminate bias when it comes to election prognostication, but there hasn’t been a similar commitment to eliminating the bias of spurious political narratives peddled by major media outlets. This leaves data journalism in the unfortunate position of helping to predict our electoral choices without evaluating their significance and pointing to alternatives.

The real problem with our media wasn’t that it was bad at predicting elections (although it was) — it’s that it spends so much time on predicting elections at all.

This isn’t to say there isn’t value in the technocratic skill and rigor behind data journalism. There is no question that a refined quantitative methodology for predicting election results is leagues beyond the horserace neuroticism of sites like Politico. But if, as Silver has said, he will not “do advocacy” and “won’t do a ton of public policy coverage,” then sites like FiveThirtyEight are really just a more skillful extension of the media circus Silver made a career out of criticizing. This is because eliminating bias when predicting events, in the absence of preventing bias when interpreting them, leaves intact the dysfunctional trajectory mass media has taken: its propensity for navel-gazing and sensationalism over actual journalism. As a result, data journalism runs the risk of statistically aggregating the U.S. political electorate before it can even express itself—and thereby downplaying its potential for transforming the political realities we face.

This extensive use of Big Data for election forecasting passively promotes our current sense of political fatalism. Elections are supposed to be about choices. It’s hard enough to get out the vote when every voter realizes their personal choice is practically meaningless amongst the millions of votes cast. But when people start to think, on top of this, that the result is a foregone conclusion, elections will lose their existential significance. Such an analysis is not speculative. It is the reality we face if Big Data becomes the only solution we have for the media’s inability to provide political narratives that are simultaneously interesting yet trustworthy, regulative yet empowering. If this trend continues, people will stop trying to negotiate the meanings the world can have for them through our democratic electoral system, instead relying on new social movements in the vein of Occupy. This is not a recipe for perfect statistical prediction; it is a recipe for political instability and further intransigence.

If watching Fox News, as a recent study concluded, literally makes you less informed about what is happening in the world, then data journalism has equivalently failed to make us care more about it. This is because Big Data, by definition, employs a statistical calculus that relies on the world acting in the future like it has in the past. Such a method may have great predictive power; it is also, unto itself, ideologically conservative. And that matters when what we are trying to measure is political participation itself. Make no mistake—Nate Silver should not be lumped together with Bill O’Reilly or Glenn Beck as an enemy of civic engagement; he lives and operates in a social reality very close to our own. But he does have one thing in common with them: persuading people into perceiving politics through the aesthetic coherence of his models at the expense of their own political imaginations. This is the danger inherent in Big Data qua ideology, rather than a tool in the service of inquiry.

This situation is all the more frustrating in light of the media’s refusal to obey its own platitude of informing public opinion. Data journalism is preoccupied with informing the people more about their own voting behavior than the people actually on the ballot. This doesn’t help the public judge their representatives; it helps elites predict public behavior. Such a project turns the idea of an election on its head: elites who have been informed on the electorate in advance can make political and economic choices that preemptively shape public opinion, while the public is left uninformed on the politicians and unable to make effective decisions. This atmosphere of statistical certitude induces politicians to become ideologically calcified and electorally complacent; amongst the public, it induces disinterest and anxiety in equal measure. If our politicians are now fully adept at gerrymandering congressional districts to ensure their own reelection, then Big Data has the potential to empower rather than critique the political machines that help elites control elections. It would offer, so to speak, an opportunity to gerrymander our minds—to ensure our collective political imagination is kept static.

Data journalism should be telling us what’s at stake, emphasizing our agency, and empowering our sense of political possibility. It should work to make the world more comprehensible, not more predictable. In truth, this is a problem bigger than our media or our politics. At its best, the age of Big Data could lead to the triumph of reason over prejudice, possibility over tradition, pragmatism over ideological dogmatism. But at its worst, it could comprise an age of meaninglessness in the face of apparent determinism, the valuation of skill over purpose, and knowledge without wisdom. We want data journalism to help us reach the potential of the former rather than suffer the pitfalls of the latter.

The atmosphere of statistical certitude induces politicians to become ideologically calcified and electorally complacent; amongst the public, it induces disinterest and anxiety.

If nothing else, this election is important for making the difficulty of this dichotomy clear. The current media environment isn’t just unhelpful; it’s suffocating, even for those in positions of power who might otherwise be a voice for political possibility. Throughout his public life, President Obama has acquired a reputation as one of the nation’s most inspiring political figures. Yet in this election he has been viewed as a liability for his party, increasingly detached and disinterested in campaigning. No less than his former top political advisor David Axelrod has said that Obama is “negligent in the symbolism of the Presidency” and that “there’s a theatrical nature to the presidency that he resists.” But what does it say about the symbolic efficacy of our political institutions when we feel a need to give the man responsible for articulating “A More Perfect Union”—perhaps the most mature discussion of race ever articulated by a national American politician—a lesson in how to be inspiring?

It is more likely Obama has given in to the “reality” perpetuated, if not wholly created, by our media—that his presidency effectively “ended” with the 2012 election. This is a presidency whose most noteworthy second-term accomplishment, the implementation of health-care reform, was given one of its largest bursts of youth support by Obama’s not-quite-serious-but-not-quite-not-serious appearance on “Between Two Ferns.” His most humanizing moment from the 2013 White House Correspondents’ Dinner came when Obama presented the trailer for Spielberg’s “upcoming” biopic of his own presidency, featuring a performance by Obama-as-Daniel-Day-Lewis-as-Obama, in which he openly wondered what Obama’s (i.e. his own) true “motivations” are; it’s less an amusing attempt at self-mockery than a perfect encapsulation of everything wrong with modern media culture.

If our politicians can’t risk making public appearances or trying to appear human without navigating at least three levels of performative irony, then our political culture has entered a state of structural crisis. Every “straight” speech is viewed through the lens of the horserace first, interest groups second, substance last. It is not even clear how we might evaluate the result of the midterms as a referendum on Obama’s tenure—every possible lens for doing so has already been monopolized by hyper-politicized media outlets. The result is that the only seemingly objective narrative we can hold on to for understanding our shared political reality is that provided by the predictive certainty of data journalism. And because of this, Generation Y may be the first for whom discussing the likelihood of a candidate’s election based on the integration of the latest polling data to a reliable statistical model feels more politically engaging than actually voting.

Data journalism could help resolve this media crisis by pointing to new pathways for political action. Consider again the example of voter suppression, which Republicans have continued to pursue with little effective opposition. Silver has not elaborated on or refined his speculative contribution to this issue from the 2012 campaign, despite being in a prime position to do so; FiveThirtyEight’s coverage of the recent Ebola outbreak did not go far beyond evaluating null hypotheses in response to Politico’s speculations and evaluating epidemic scenarios which, by the authors’ own admissions, will likely never occur. Where is the historically conscious, data-driven, headline-grabbing content that would help me intelligently decide if Ebola is cause for concern, or if sending troops to Liberia is the most effective course of action amongst unquestioned alternatives?

Big Data is a tool to help us perceive what is at stake, to evaluate possibilities normatively rather than positively.

The emptiness of our national political discourse as led by the media isn’t made more empty by the incorporation of rigorous mathematical techniques. Big Data is a tool to help us perceive what is at stake, to evaluate possibilities normatively rather than positively. It can inform our choices and clarify our own values in light of complex and seemingly chaotic realities. But it cannot act as a substitute for astute political analysis, let alone civic engagement. Silver is right to insist that the news media should become more data-driven, but the best coverage is inevitably both grounded in the empirical world while providing a vision for where the world might go from here. We should care more about changing the world at the same pace that we learn more about what is happening within it.

In brief, we have an amazingly good idea of exactly what will happen on November 4—indeed, maybe a better idea than for any previous midterm election in the nation’s history. It is also hard to think of a national election about which we have had less of a reason to care. These facts are not unrelated. Data journalism should be helping us understand the implications of this confluence for the lasting integrity of our political system, not by providing the latest metrics on what we think other people are likely to do, but by helping us look to each other.