Transformational Public Policy examines how governments can more
effectively handle uncertainty and risk in an uncertain and
changing world. Unpredictable and changing circumstances often
bring nasty surprises that can increase waste in governance and
public debt. This book illustrates how new methods derived from
signal processing techniques can improve the practice of public
policy by transforming it through rapid learning and adaptation.
Interventions are processes of discovery, not compliance.
Transformational Public Policy shows readers how the power of
hypothesis testing in governance can be deployed. The book argues
that public policy can be framed as tests of competing hypotheses
subject to diagnostic errors. The aim is to learn how to reduce
these diagnostic errors through cumulative experience. This
approach can reduce the impact of negative unintended consequences
-- a topic of great interest to policy makers and academics alike.
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