The promise of AI in government is huge, but so are the stakes. We sit down with Dr. Cari Miller and Dr. Gisele Waters, co-founders of the AI Procurement Lab and leaders behind IEEE 3119, the first standard dedicated to procuring AI and automated decision systems. Together we break down how public buyers can make smarter, safer choices—turning values like transparency and human oversight into concrete policies, contract clauses, and day‑to‑day practices that actually hold up under pressure.
We start with practical first steps: form a truly cross‑functional procurement team, define a real problem, and assess data readiness. You’ll hear why “getting ready to get ready” is a smart move, using small, low‑risk pilots to clean data and build capability before rolling out bigger tools. We share cautionary case studies, including a clever pothole detection project on trash trucks that drifted into unintended surveillance, and we explain how scope, safeguards, and community accountability prevent harm while preserving benefits.
From there, we get specific on AI policy versus contracts: how to require model provenance, audit rights, incident reporting, redress processes, and exit strategies that avoid vendor lock‑in. We talk SPI and the hidden risk of metadata, why human‑in‑the‑loop matters for public trust, and how change management helps teams see AI as a useful tool rather than a threat. By the end, you’ll have a roadmap for responsible AI procurement that blends governance, ethics, and measurable outcomes.
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Season 6, Episode 7 Transcript
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