Can artificial intelligence help governments make better policy without actually making policy?
Recorded live at AI4 2026 in Las Vegas, Sanjay Puri speaks with Alaa Moussawi, Chief Data Scientist at the New York City Council, about how data science, open-source AI, RAG, and AI agents are being used to make government more evidence-driven and efficient.
Alaa explains how his team uses Retrieval-Augmented Generation (RAG) to help attorneys and policy analysts search thousands of legal memos, retrieve relevant precedents, and conduct legislative research in seconds—while keeping humans responsible for the actual policy decisions.
The conversation explores the role of AI in government, AI-assisted policymaking, open-source AI, legislative research, AI governance, government technology, and the growing question of where the line should be drawn between AI assisting policymakers and AI influencing policy itself.
Alaa also shares how the New York City Council is building multiple AI agents into a single chatbot that can retrieve information from legislation, demographic data, HR systems, and external APIs, creating a unified AI interface for government employees.
In this episode:
* How AI is being used inside the New York City Council
* Can AI help governments write better legislation?
* Using RAG for legislative and legal research
* Why AI should assist policymakers—not make policy
* How open-source AI can improve government technology
* Building AI agents for government workflows
* Creating a unified AI chatbot for government employees
* AI governance and human oversight in public policy
* Why data-driven policymaking matters
* The future of AI in government
* AI, job displacement, and the role of government
* Why government needs to adapt to AI-driven automation
* Building AI capabilities inside public institutions
* Why Alaa chose public service over Silicon Valley
Alaa argues that the goal isn't simply to make government faster. It is to improve the quality of legislation by reducing repetitive work and decision fatigue, allowing attorneys, policy analysts, and elected officials to focus on higher-value work.
Whether you're a policymaker, government technology leader, Chief AI Officer, data scientist, researcher, or AI governance expert, this conversation offers a practical look at what responsible AI adoption in government can actually look like.
Recorded live at AI4 2026 in Las Vegas by Knowledge Networks.
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## Chapters
00:00 Can AI assist without writing policy?
00:50 Meet Alaa Moussawi, NYC Council Chief Data Scientist
02:00 Building data-driven policymaking at NYC Council
02:46 Building government technology with open source
04:50 Using RAG for legislative research
07:30 How RAG works inside government
10:00 Making legal research faster with AI
11:56 Where AI assistance ends and policymaking begins
14:44 Should AI make government more efficient?
16:13 Automating government workflows
17:00 Measuring AI's impact on government
19:00 The challenges of adopting AI in government
20:00 Why NYC Council uses open-source AI
21:30 AI, energy use, and the ethics of AI
22:20 AI and the future of jobs
25:40 Why NYC Council chose open-source AI
26:43 How many jobs could AI replace?
27:28 Does AI need federal governance?
28:14 Can NYC's AI model be replicated elsewhere?
30:06 Why Alaa chose public service
31:39 Building AI agents for government
33:14 One chatbot to connect government information
33:31 Open source, RAG, MCP and AI
33:51 The one decision Alaa would—and wouldn't—trust AI to make
