Transformational Public Policy examines how governments can more effectively handle uncertainty and risk in an uncertain and changing world. 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. It shows readers how the power of hypothesis testing in governance can be deployed. This approach can reduce the impact of negative unintended consequences -- a topic of great interest to policy makers and academics alike.

1. Introduction: governance and entropy
2. The limitations of uncertainty and risk-averse public policy
3. Government as uncertainty and risk manager of last resort
4. Concepts for facilitating the transition
5. Achieving the paradigm shift
6. Conclusions: low entropy governance

Mark Matthews is a public policy specialist who has worked closely with different governments from both private sector and academic bases. He has a background in science and innovation policy and is particularly interested in the consequences of shortcomings in the ways in which governments approach uncertainty and risk - and what could be done to address these problems.