The era of theoretical AI ethics is over. For state governments, the age of AI regulation has begun.

From Sacramento to Albany, statehouses are becoming the new front lines for AI policy. As agencies rush to deploy AI for everything from DMV services to public health inquiries, they face a daunting challenge: how do you write the rules for a technology that evolves faster than the legislative process? The risks are immense—algorithmic bias in social services, data privacy breaches, and the public's eroding trust.

In this critical episode, we go beyond the headlines to examine the intricate process of building AI policy and regulation from the ground up at the state level. We explore how states like Indiana, California, and Virginia are creating their own AI risk frameworks, often based on principles from MIT and NIST, to govern how they and their vendors operate.

Join us as we talk with the architects of these new digital directives—the policy managers, state CIOs, and legal experts who are writing the playbook in real-time. We'll dissect the tough questions every state is facing:

• The Liability Labyrinth: When a state-sanctioned AI agent gives flawed financial advice or mishandles a crisis disclosure, who is legally responsible? The software vendor? The agency that deployed it? We unpack the battle over accountability.
• Procurement with Guardrails: How can states purchase innovative AI solutions without inheriting unacceptable risks? We look at the new compliance clauses and ethical certifications vendors must now meet to win public sector contracts.
• From Policy to Practice: What does it actually take to enforce these rules? We discuss the rise of state-level AI Ethics Boards, the role of a Chief AI Officer, and the technical tools required to audit an algorithm for fairness and compliance.

This episode is essential listening for:

• Public Sector Officials and Policymakers
• Technology Vendors and Service Partners in the GovTech space
• Chief Risk, Compliance, and Information Officers
• Anyone interested in the practical application of AI ethics and law.