The simulation manifesto: The limits of brute‐force empiricism in geopolitical forecasting

Intelligence analysis has traditionally relied on inside‐view, case‐specific modes of thinking: why did this actor—say, the USSR—do that and what might it do next? After 9/11, however, analysts faced a vastly wider range of threats that necessitated outside‐view, statistical modes of reasoning: how likely are threats to emerge from actors of diverse types operating in situations of diverse types? Area‐study specialists (who staffed most geopolitical desks) were ill‐equipped for answering these questions. Thanks to advances in long‐range sensing, digitization, and computing, the intelligence community was flooded with data, but lacked clear ideas about how to render it relevant. Empiricism, whether grounded in deep inside‐view knowledge of particular places or broad outside‐view knowledge of statistical patterns across the globe, could not and cannot solve the problem of anticipating high‐impact, rare events, like sneak attacks and pandemics. Contingency planning for these threats requires well‐calibrated conditional forecasts of the impact of policy interventions that in turn require synthesizing inside‐ and outside‐view analytics. Such syntheses will be best achieved by refining computer simulations that permit replays of history based on the interplay among initial conditions, chance, and social‐science models of causation. We offer suggestions for accelerating the development and application of theory‐guided simulation techniques.