TITaha Iqbal
Research Papers
GovernanceForecastingInstitutional Risk

Perspectives and Opportunities in Intelligence for U.S. Leaders

Weinbaum, Parachini, Girven, Decker, Baffa·RAND Corporation·January 1, 2018·Intermediate·Source

Abstract

Examines structured analytic techniques for reducing cognitive bias in IC assessments

Interpretation

Justifies anchoring AI threat models on capability signals when intent is unmappable

Governance Implications

IC methodology as template for AI oversight frameworks

Forecasting Implications

SATs as forcing function against embedded mind-sets on AI plateau assumptions

Criticisms

Designed for human adversaries; fluid agency breaks its intent-mapping assumptions

Hypotheses

"Structured analytic techniques reduce warning failure probability when applied to AI capability assessment"

72%

SATs were designed for human adversaries but the core logic — forcing analysts past embedded mind-sets — applies directly to AI plateau assumptions

Updated May 28, 2026