Silverman’s group focuses on individual agents, but other modelers take a more organizational approach, simulating large-scale social networks on supercomputers and churning out trillions of bytes of data. Models built by Edward MacKerrow at Los Alamos National Laboratory, Charles Macal at Argonne National Laboratory, Alok R. Chaturvedi at Purdue University, Desmond Saunders-Newton at BAE Systems, and Kathleen Carley at Carnegie Mellon University use thousands or millions of relatively simple agents to examine how networks form and mutate, how individuals communicate, and who leads and who follows. Carley’s programs, which process real data, stand out for their ability to help analysts imagine how a terrorist network might adapt—or not—after its leader is killed or captured.

Such work, concentrated in the United States and sustained by tens if not hundreds of millions of dollars in funding by various intelligence organizations, including the CIA and the Defense Intelligence Agency, points to a new era in training and intelligence analysis. The experts developing these systems are reticent about exactly how their programs are being used. But outside observers say it is a good bet that software designed to identify the critical people in a terrorist organization will be used—if it hasn’t been already—to draw up lists that prioritize which people should be killed or captured so as to do maximum damage to the organization.

That worries some experts, who caution that even when the models are fed by the best available intelligence, they should never be trusted to determine, by themselves, whether someone should live or die. “A simulation is by its nature speculative, and you don’t go out and kill people based on speculation,” says Steven Aftergood, director of the Project on Government Secrecy for the Federation of American Scientists, in Washington, D.C.

Many modelers emphasize that such simulations are not intended to replace analysts but to augment their abilities to ferret out key individuals, break up covert cells, and prevent the kinds of surprises that lead to devastating terrorist successes. That still leaves one huge question unanswered, skeptical ­insiders say: Will analysts, many of whom struggle just to stay abreast of the information they are inundated with every day, bother to use these modeling tools if they ever become widely available?

Intelligence is by its very nature hazy and fragmentary. Its practitioners’ successes must remain secret, while their worst failures erupt in near–real time for all the world to see. For U.S. Intelligence, the attack on Pearl Harbor, the collapse of the Soviet Union, and 9/11 will resound indefinitely. Yet, in all three of those misses, scraps of information collected before the events hinted at what was to come, only to languish undigested or even unnoticed by analysts.

Part of the problem is the way analysts work, which predisposes them to what the 9/11 Commission termed “failure of imagination.” Analysts are experts, with advanced degrees in areas like economics or German literature or social psychology, who know one country or group or industry extremely well. For many, the only things that diverted them from careers in academia were patriotic inclinations or the quiet thrill of poring over deciphered intercepts, satellite photos, and data gathered by spies.

This academic culture flourished during the Cold War. Back then, analysts spent much of their time weighing pieces of classified information and thinking about strategies to achieve long-term policy goals. For the vast majority of analysts, anticipating attacks on the homeland wasn’t in the job description. But after 9/11, two developments combined to make life for many analysts much more hectic. One was the urgent need to more closely track elusive enemies who were obviously committed to killing people and destroying property. The other was the establishment of the Internet as the primary source of publicly available information—and the preferred means of terrorist communication. The Internet hugely increased the amount of data that analysts must sort through, and it consequently changed the nature of their jobs.

“Today your first responsibility as an analyst is to keep track of what’s happening right now,” former CIA analyst Larry Johnson said during a brief phone conversation as he prepared to depart for Iraq on a consulting assignment this past May. “That means dealing with 1500 to 2000 messages, classified at various levels, that move across your desk every day, messages which can be one to three pages long.”

Though the volume of the data is greater than it ever has been, the methods for analyzing it haven’t changed. Gregory F. Treverton, senior policy analyst at the Rand Corp., Santa Monica, Calif., noted during a recent tour of intelligence agencies that analysts don’t use formal analytical methods, let alone computational ones. “Insofar as there was a method in play, it was limited to brainstorming and then looking for evidence and argument that would either confirm or disprove hypotheses,” he says. “Maybe that wasn’t such a bad way to do the work during the Cold War, but it seems to many of us that it’s not the right way to do analytic work now.”

An intelligence analyst’s routine these days is more like that of a reporter than that of an academic, according to a 2005 ethno­graphic study for the CIA’s Center for the Study of Intelligence. “Basically, on a day-to-day basis, it’s like working at CNN, only we’re CNN with secrets,” one analyst told the study’s author, anthropologist Rob Johnston.

The result has been a major shift in the analyst ranks: 50 percent of U.S. analysts have less than five years’ experience, according to some estimates. And yet despite all the turnover, Johnston noted a lingering tendency among analysts to look for information to confirm the prevailing hypothesis in their groups or sections rather than challenge it and risk alienating colleagues and superiors. Indeed, it is considered taboo to change “the corporate product line”: if the president or his national security team receives an official opinion from an intelligence agency and that agency later radically revises it, trust, status, and ultimately funding are jeopardized.

Besides looking for patterns in evidence that confirm existing theories, Johnston asserts that analysts often use the wrong rules to make predictions or are too focused on one little piece of the puzzle—say, the influence of foreign fighters in Iraq’s Anbar Province. That makes it hard for them to integrate all of the different kinds of information necessary to explore how people might behave in a given situation.

“Becoming an expert requires a significant number of years of viewing the world through the lens of one specific domain,” writes Johnston (who did not respond to repeated requests for an interview). “This concentration gives the expert the power to recognize patterns, perform tasks, and solve problems, but it also focuses the expert’s attention on one domain to the exclusion of others. It should come as little surprise, then, that an expert would have difficulty identifying and weighing variables in an ­interdisciplinary task, such as forecasting an adversary’s intentions.”