Über die Autorin bzw. den Autor

Thomas Fingar is the Oksenberg/Rohlen Distinguished Fellow in the Freeman Spogli Institute for International Studies at Stanford University. From May 2005 through December 2008 he served as the first Deputy Director of National Intelligence for Analysis and, concurrently, as Chairman of the National Intelligence Council. He served previously as Assistant Secretary of the State Department's Bureau of Intelligence and Research, Principal Deputy Assistant Secretary (2001-2003), Deputy Assistant Secretary for Analysis (1994-2000), Director of the Office of Analysis for East Asia and the Pacific (1989-1994), and Chief of the China Division (1986-1989).

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Reducing Uncertainty

Stanford University Press

Contents

Acknowledgments...........................................................................ix1 Reducing Uncertainty....................................................................12 Myths, Fears, and Expectations..........................................................193 Spies Collect Data, Analysts Provide Insight............................................334 Using Intelligence to Anticipate Opportunities and Shape the Future.....................505 Estimative Analysis: What It Is, What It Isn't, and How to Read It......................676 A Tale of Two Estimates.................................................................897 Epilogue: Lessons and Challenges........................................................126Notes.....................................................................................141Index.....................................................................................171

Chapter One

the U.S. government spends billions of dollars every year to reduce uncertainty. The National Weather Service spends more than $1 billion a year to forecast precipitation amounts, track storms, and predict the weather. The Centers for Disease Control spend more than $6 billion to detect and investigate health problems in the United States and abroad. The Departments of Agriculture and Energy track and predict production of crops and various types of energy. Virtually every agency of the federal government monitors and forecasts a wide range of developments because farmers, manufacturers, state governments, travelers, and citizens in every walk of life want information that will enable them to make better-informed decisions about what to grow, whether to invest, and where to travel. In other words, we spend a lot of money to anticipate problems, identify opportunities, and avoid mistakes.

A substantial portion of what we spend to reduce uncertainty—almost $50 billion a year—goes to the U.S. Intelligence Community (IC). The need for this amount of money is justified through a process that emphasizes threats to our nation, our interests, and our people. For example, the classified and unclassified versions of the Annual Threat Assessment submitted to Congress by the director of national intelligence devote far more attention to problems and perils than to opportunities to shape events. This emphasis is understandable, but it is also unfortunate because it obscures one of the most important functions of the Intelligence Community and causes both analysts and agencies to devote too little attention to potential opportunities to move developments in a more favorable direction.

Intelligence Community work to reduce uncertainty differs from that of other U.S. government (USG) agencies in a number of important ways. The most obvious, of course, is that it has access to clandestinely acquired and other classified information. Indeed, the IC exists, in part, to ferret out secrets and to collect information that cannot be obtained by scholars, journalists, bankers, diplomats, or other "collectors." The use of classified information does not automatically make analyses produced by the Intelligence Community better than those produced using only unclassified information, but reducing uncertainty about a large number of traditional national security issues can be more precise and often more reliable if IC collectors have managed to intercept, inveigle, purchase, or steal information that others wish to keep hidden.

Another way in which IC efforts to reduce uncertainty differ from those of other USG agencies is that most IC products remain classified for a long time. The reasons they do include the need to protect sources and methods (that is, how we obtained the information), the value attached to objectivity and clarity (it can be difficult to obtain a hard-nosed assessment of a foreign political leader or military capability if the analysis is intended for public dissemination), and the fact that many IC assessments are used to determine policies and negotiating positions of the U.S. government (telling others what U.S. officials are considering before they have made a decision on the issue is generally thought to be unhelpful). Despite recurring assertions to the contrary, IC analytic products are not classified for long periods of time to prevent taxpayers from knowing what they get for $50 billion a year. Classification decisions are made when assessments are produced, almost always on the basis of the classification level of information used in the report. I cannot imagine a situation in which an analyst or manager would say, in effect, "This analysis is really bad. Let's disseminate it to decision makers but give it a very restrictive security classification so the public will not see how bad it is." In my experience, most intelligence assessments are not very sexy or exciting, and few present theoretical breakthroughs of any kind. But that does not mean that they are poorly crafted or of little value. As noted in Chapter 5, hundreds of National Intelligence Estimates have been declassified and released. Most of them stand up pretty well, especially if judged against the criteria of "Were they useful to decision makers at the time they were produced?" and "Did they help to reduce uncertainty—even if only by reaffirming what officials thought they understood to be the case—about issues being deliberated in the USG?"

Reducing uncertainty sometimes involves acquiring information, overtly and covertly, that is thought to be useful to understanding developments or intentions. Sometimes it involves research and analysis to produce what Carl Ford refers to as "new knowledge," that is, better understanding and new insights derived from thinking hard about information we possess but have not considered or combined in the way that led to the new assessment. At still other times it involves efforts to substantiate or disconfirm a hunch articulated by a customer or fellow analyst or to refute statements made in a meeting or the media. Reducing uncertainty, in other words, can take many forms and involve many types of analysis, but it almost always strives to enhance understanding of what is known, what remains unknown, what is happening, where events seem to be headed, what is driving them, and what might alter the trajectory of developments.

Contrary to fictional depictions and popular misconceptions fueled by political grandstanding and media caricatures, the intelligence enterprise exists to do more than steal secrets and "connect the dots." Ferreting out information that adversaries wish to hide and discovering (and disrupting) terrorist plots and other threats to our nation and our interests are important missions and, disparaging characterizations notwithstanding, we perform them very well—most of the time. We never have batted 1.000 and never will, but getting it mostly right, most of the time, in time to shape, prevent, or prepare for developments with the potential to affect our nation, our citizens, and our interests is and will remain our most important goal and criterion of success. Unlike highly paid ballplayers, we will never be satisfied with a .300 batting average. The security of our nation requires that we come as close to 1.000 as is humanly possible, and every IC analyst worthy of the...