Better Governance
This book examines how governance structures shape incentives, behavior, and long-term investment, arguing that the quality of governance is the primary determinant of prosperity and liberty. It explains how political power operates, why inclusive democracies tend to outperform autocracies, and how institutional frameworks can leverage technology to automate enforcement.
Drawing on institutional economics, mechanism design, game theory, and systems engineering, the book reframes constitutional design as an engineering problem rather than an ideological debate. Instead of prescribing specific policy decisions, it proposes a framework for constructing rules and constitutional provisions that reliably produce better collective decisions.
Moving from theory to practice, the book offers a rigorous blueprint for scholars, policymakers, reformers, and technologists seeking to improve governance. It provides concrete tools for institutional reform, including an AI-based adjudication system and a “smart constitution” deployable on a blockchain to govern political transitions and establish legitimate interim governments. It also proposes a zero-trust constitutional framework that assumes adversarial behavior by public officials.
Daniel Armani is an applied econometrician and data scientist whose work examines how governance, AI, and blockchain technologies shape collective action and economic performance. His research focuses on automated governance and decentralized autonomous organizations (DAOs), which he designs and evaluates using online experimentation and agent-based simulation. He has conducted research on collective intelligence and governance mechanisms at Michigan State University, the University of Texas at Austin (as Principal Investigator), and the University of Delaware, and has taught at all three institutions. He holds a Master’s in Socio-economic Systems and a PhD in Management Information Systems.