AI in Legislation and How NYC Uses Data Science to Drive Policy

Mar 5, 2025

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Alaa Moussawi, Chief Data Scientist for the New York City Council, shares how AI is reshaping legislative processes through smarter, data-driven laws. He discusses the council’s use of Retrieval-Augmented Generation (RAG) models, and open-source AI solutions to streamline workflows and ensure legislative originality. He also shares his perspective on the future of AI in government, the importance of transparency in policy-making, and why generative AI should assist with—but never make—decisions.

Key Takeaways:

How the New York City Council team leverages AI and data science to drive evidence-based policymaking
The importance of transparent, statistically-driven legislation
The debate between cloud-based vs. on-premise AI solutions in government
Common misconceptions about generative AI and decision-making
The future of AI in government and its role in shaping policy

Guest Bio: Alaa Moussawi serves as Chief Data Scientist for the New York City Council, leading teams of data scientists and software engineers. His data team analyzes issues like pay equity, rats, and school bus delays to support data-driven legislation, emphasizing transparency and reproducibility. The software team works to streamline council workflows, automate tasks, and improve efficiency, developing open-source tools like CRMs, dashboards, and paperless hearing systems. They’ve deployed machine learning models, including a RAG model for simplifying legal research. Dr. Moussawi is also producing a LinkedIn Learning course on developing RAG models in secure environments. ----------------------------------------------------------------------------------------

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Produced by: Sam Laliberte