How (Not?) To Win the Information War Over Ukraine

In an opinion piece for The Telegraph last Friday (here), writer Anne Applebaum bemoans that Russia is winning the “information war” over the crisis in Ukraine with demonstrable falsehoods.

The crude and shrill nature of the propaganda now being aired on Russian media and especially on Russia Today (RT), the international news channel owned by the Russian state, has surprised me. Until now, the tone has generally been snide and cynical rather than aggressive. With slick, plausible American anchors and some self-styled hip outsiders—Julian Assange had a regular show—it seemed designed to undermine Western arguments, not denounce them. But now it is openly joining an information war being conducted on an unprecedented scale. The bald-faced lie has now become commonplace.

To counter this torrent of lies, Applebaum argues, the U.S. and Europe need to speak more truth louder.

The only response to an all-out information war is an all-out information defence. The West used to be quite good at this: simply by being credible truth-tellers, Radio Free Europe and the BBC language services provided our most effective tools in the struggle against communism. Maybe it’s time to look again at their funding, and to find ways to spread their reach once more.

I’d say that Putin & co. are clearly winning the propaganda war over Ukraine on the domestic front and playing to a draw on the international side. Press freedom is nearly non-existent in Russia (here), and Moscow’s domestic audience skews nationalist anyway (here), so that’s an easy victory. International audiences are more heterogeneous and surely less sympathetic than native ones, but as Applebaum notes, the Russian government doesn’t need to convince everyone that its version of the narrative is true to shape the politics of the response.

Unlike Applebaum, though, I am not confident that her proposed remedy—loud truth-telling—will produce the desired result. In fact, experiments conducted in the past few years by political scientist Brendan Nyhan and several co-authors suggest that, in information wars, frontal assaults sometimes have the opposite of the intended effect. In a 2013 paper entitled “The Hazards of Correcting Myths About Healthcare Reform” (here), the authors describe the results of an experiment “to determine if more aggressive media fact-checking could correct the false belief that the Affordable Care Act would create ‘death panels.'”

Participants from an opt-in Internet panel were randomly assigned to either a control group in which they read an article on Sarah Palin’s claims about “death panels” or an intervention group in which the article also contained corrective information refuting Palin.

Findings: The correction reduced belief in death panels and strong opposition to the reform bill among those who view Palin unfavorably and those who view her favorably but have low political knowledge. However, it backfired among politically knowledgeable Palin supporters, who were more likely to believe in death panels and to strongly oppose reform if they received the correction.

Conclusions: These results underscore the difficulty of reducing misperceptions about health care reform among individuals with the motivation and sophistication to reject corrective information.

Nyhan and his co-authors got similar results in a follow-on study designed “to test the effectiveness of messages designed to reduce vaccine misperceptions and increase vaccination rates” (here). This time,

A Web-based nationally representative 2-wave survey experiment was conducted with 1759 parents age 18 years and older residing in the United States who have children in their household age 17 years or younger (conducted June–July 2011). Parents were randomly assigned to receive 1 of 4 interventions: (1) information explaining the lack of evidence that MMR causes autism from the Centers for Disease Control and Prevention; (2) textual information about the dangers of the diseases prevented by MMR from the Vaccine Information Statement; (3) images of children who have diseases prevented by the MMR vaccine; (4) a dramatic narrative about an infant who almost died of measles from a Centers for Disease Control and Prevention fact sheet; or to a control group.

RESULTS: None of the interventions increased parental intent to vaccinate a future child. Refuting claims of an MMR/autism link successfully reduced misperceptions that vaccines cause autism but nonetheless decreased intent to vaccinate among parents who had the least favorable vaccine attitudes. In addition, images of sick children increased expressed belief in a vaccine/autism link and a dramatic narrative about an infant in danger increased self-reported belief in serious vaccine side effects.

CONCLUSIONS: Current public health communications about vaccines may not be effective. For some parents, they may actually increase misperceptions or reduce vaccination intention. Attempts to increase concerns about communicable diseases or correct false claims about vaccines may be especially likely to be counterproductive.

I see the results of those studies and imagine Russian and other audiences already ambivalent or hostile toward the U.S. as the functional equivalent of those Palin supporters and vaccine skeptics. It’s counter-intuitive and frustrating to admit, but facts don’t automatically defeat falsehoods, and attempts to beat the latter with the former can even encourage some antagonists to dig their heels in deeper. Before the U.S. and Europe crank up the volume on their own propaganda, they should think carefully about the results of these studies.

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The Green Lantern Theory of State-Building

In a recent post on Human Rights Watch’s World Policy Blog, Hanan Salah nicely summarizes the poor state of state-building in post-Qaddafi Libya:

The main problem affecting both justice and security is that armed militias still maintain the upper hand. They have various agendas—financial, territorial, political, religious—and operate with impunity two years after the Qaddafi regime ended. Successive interim governments have failed to assert control over these militias, preferring to contract them as parallel forces to the army and police. Consequently, they retain a stranglehold over key security objectives, such as protecting Libya’s oil fields, making it ever harder for the government to break their financial dependency and hold on these lucrative opportunities. The structure of the militias and related armed groups, their shared interests, political aspirations, and the tribal nature of Libyan society are further complicating factors.

This passage gets at the chicken-and-egg problem that makes state-building so hard, not just in Libya but everywhere. “Justice and security” are the chief public goods a state exists to provide, but the provision of those goods depends on widespread obedience of state authority, and that authority is hard to construct.

What bugged me about Salah’s otherwise excellent post was the use of the verb “prefer” to indicate why this authority isn’t cohering faster in Libya. “Prefer” connotes choice, and I’m not convinced that the officials comprising Libya’s internationally recognized government have very much of that. They face an array of entrenched militias that are probably profiting handsomely from control of their various fiefdoms. Those officials supposedly command an army and police force of their own, but those organizations are still small and under-resourced. Worse, the revenue streams that could make the national army and state police stronger—including oil—are often controlled by the very militias those forces are supposed to be beefing up to defeat. Under these circumstances, how exactly are Libyan officials supposed to persuade these militias to cooperate? Give them a stern talking-to?

To be fair, Salah’s post is hardly the first place I’ve seen this line. Actually, I think it’s fair to say that this is comparative politics’ version of the Green Lantern Theory that Matt Yglesias coined to describe neoconservative U.S. foreign policy and Brendan Nyhan has since extended to the American presidency. In the Green Lantern Theory, political outcomes are mostly a matter of will. If the state doesn’t cohere, it’s because the people tasked with doing it lack the spine to fulfill their charge as duly chosen leaders.

If we reject the Green Lantern Theory of state-building and recognize that power is at least as important as will, it’s tempting to think that outsiders can goose the process with an infusion of armed forces, or at least the money and training an internationally recognized government needs to build up its own. The growth of the state is stunted, so a few costly doses of hormone therapy should do the trick. In fact, as Reuters reported, Libya’s prime minister recently made just this plea at an investment conference in London:

If the international community does not help in the collection of arms and ammunition, if we don’t get help in forming the army and the police, things are going to take very long… The situation is not going to improve unless we get real and practical assistance.

In fact, politics isn’t nearly as mechanical and modular as this idea implies. Before embarking on a new state-boosting mission in Libya, foreign governments would do well to take another look at Somalia, which has been the target of similar treatments for the past two decades. As Alex de Waal describes in a recent post on the LRB Blog,

[President] Hassan’s Western backers have not yet squared the circle of pouring money and guns into a client government to fight a counterinsurgency, and preventing that government from becoming rentierist, militaristic and corrupt. Rent-seeking pervades the whole system: the president or defence minister must bargain separately with each military unit to secure its loyalty for each operation. And even then, he cannot order a Somali unit to enter a ‘liberated’ town where the locals won’t welcome it. It’s no surprise that Somalis hedge their bets against the time when the [Somali Federal Government’s] international sponsors tire of a Sisyphean counterinsurgency and sell out their erstwhile proxies. Even if al-Shabab were defeated, it wouldn’t solve Somalia’s problems. The corrupt rentierist system of government, which gave rise to al-Shabab in the first place, would be more entrenched than before.

Much the same could be said of Afghanistan, too.

And this is the Great Frustration of applied social science: prescription doesn’t always follow from explanation. Even if we can understand pretty well why state-building is so hard, we still can’t figure out how to control it. Whether that’s a curse or a blessing will depend on whom you ask, and therein lies the essence of politics.

When Forecasting Rare Events, the Value Comes from the Surprises

Forecasters of U.S. presidential elections are carrying on a healthy debate about the power and value of the models they construct. Nate Silver fired the opening salvo with a post arguing that the forecasts aren’t nearly as good as political scientists (and their publishers) claim. John Sides and Lynn Vavreck responded with reasoned defenses, and Brendan Nyhan‘s earlier post on the topic deserves another look in response to Silver’s skepticism as well.

One reason it’s so hard to forecast U.S. presidential elections is that there aren’t that many examples from which to learn. American presidential elections only happen 25 times each century, and the country’s only been around for a couple of those. As if that weren’t enough trouble, it’s hard to imagine that the forces shaping the outcomes of those contests aren’t changing over time. Just 25 election cycles ago, TVs and PCs didn’t exist, and most American homes didn’t even have phones.

Those of us who try to forecast rare forms of political conflict and crisis confront a similar challenge. Right now, I’m working on a model that’s meant to help anticipate onsets of state-sponsored mass killing in countries around the world. Since World War II, there have been only 110 of these “events” worldwide, and they have become even rarer in the two decades since the collapse of the Soviet Union.

The rarity of these atrocious episodes is good news for humanity, of course, but it does make statistical forecasting more difficult. With so few events, statistical models don’t have many cases on which to train, and modelers have to think more carefully about the trade-offs involved in partitioning the data for the kind of out-of-sample cross-validations that offer the most information about the accuracy of their constructs. The same logic applies to wars within and between states, coups, democratic transitions, popular uprisings, and just about everything else I’ve ever been asked to try to forecast.

When modeling events as rare as these in a data set that covers all relevant cases, the utility of the forecasts isn’t in the point estimate of the likelihood that the event will occur. With small samples and noisy data sets, those point estimates are way too uncertain to take literally, and even the most powerful models will never generate predictions that are nearly as precise as we’d like.

Instead, a good starting point for forecasting from rare-events models is a list of all at-risk cases shown in descending order by estimated probability of event occurrence. Most of the countries at the tops and bottoms of these lists will strike their consumers as “no-brainers.” For example, most of us probably don’t need a statistical model to tell us that China is especially susceptible to the onset of civil-resistance campaigns because it’s an authoritarian regime with more than 1 billion citizens. Likewise for a list that tells us Norway is unlikely to break out in civil war this year. Both of those forecasts can be accurate without being especially useful.

The real value of rare-events forecasts comes from the surprises–the cases for which a ranked list generated from a reasonably reliable model contradicts our prior expectations. These deviations provide us with a useful signal to revisit those expectations and, when relevant, to prepare against or even move to prevent that crisis’ occurrence.

Take the recent coup in Mali. While the conventional narrative described this country as a consolidated democracy, a watch list generated from statistical models identified it as one of the countries in the world most likely to suffer a coup attempt in 2012. Had people concerned about Mali’s political stability seen that forecast ahead of time, it might have spurred them to rethink their assumptions and perhaps prepare better for this unfortunate turn of events.

These surprises can cut the other way, too. In January, when I used a model of democratic transitions to generate forecasts for 2012, I was chagrined to see that Egypt ranked pretty far down the list. Now, with the outcome of the transition increasingly in doubt, I’m thinking that forecast wasn’t so bad after all. For concerned observers, a forecast like that could have served as a useful reminder that Egypt still isn’t on a steady glide path to democracy.

Even with well-calibrated models, these “deviations” won’t always prove prescient. A watch list that accurately identified Egypt, Morocco, and Syria as three of the countries most likely to see civil-resistance campaigns emerge in 2011 also ranked North Korea in the top 10 for that year, and nothing in that list or the underlying model could have told us in advance which would be which.

In spite of that imprecision, I think the forecasts worked pretty well. Most of the countries toward the top of the list may not have seen popular uprisings, but nearly all of the uprisings that did occur happened in top 30 countries. Analysts who were surprised to see a civil-resistance campaign erupt in Syria might not have been so surprised if they had seen those forecasts and reconsidered their mental models accordingly.

The broader point is that, when trying to forecast rare events, we shouldn’t get too hung up on the exact values of the predicted probabilities. The model we’re striving for here isn’t an actuarial table that allows us to allocate our dollars and attention as efficiently as possible. Even if policy and advocacy worked that way–and they don’t–the statistics won’t allow it.

A more useful model, I think, is the light on your car’s dashboard that tells you you’re running low on fuel. When that light comes on, you don’t know how far you can drive before you’ll run out of gas, but you do know that you’d better start worrying about refilling soon. The light directs your attention to a potential problem you probably weren’t thinking about a few moments earlier. A reasonably well-calibrated statistical model of rare political events should do the same thing for analysts and other concerned observers, whose attention usually doesn’t get redirected until the engine is already sputtering.

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