AI Policy: Principles, Practice, and the Path Forward

The first part lays the groundwork, tracing historical technology policies, defining AI within regulatory contexts, and analyzing ethical frameworks and geopolitical approaches. Part II explores core policy themes such as data governance, algorithmic transparency, human rights, bias, accountability, economic disruption, surveillance, national security, and environmental impact. These chapters unpack the tensions between innovation and regulation, and between individual rights and collective risks.

Part III shifts to the tools of governance, distinguishing between soft law (standards, guidelines) and hard law (binding regulations), and addressing mechanisms like policy sandboxes, public procurement levers, and risk differentiation between safety and security. The final part uniquely delves into underexplored topics, including AI in informal economies, the Global South, participatory governance, open-source regulation, and liability insurance.

The concluding chapters anticipate future challenges—global treaty feasibility, long-term foresight, institutional capacity-building, and evaluating policy effectiveness. A strong emphasis is placed on democratizing AI policy, arguing that equitable, inclusive, transparent, and accountable governance must be central to any sustainable AI future.

By offering a holistic yet detailed view, the book equips policymakers, researchers, and civil society actors with the tools to navigate and shape AI governance in a way that serves the public good, respects diversity, and guards against harm across all societies.