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AI-Powered Rules as Code: Experiments with Public Benefits Policy
This report documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
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AI-Powered Rules as Code: Experiments with Public Benefits Policy: Summary + Key Takeaways
This is the summary version of a report that documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
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AI-Driven Statutory Reasoning via Software Engineering Methods
This article explores how legal documents can be treated like software programs, using methods like software testing and mutation analysis to enhance AI-driven statutory analysis, aiding legal decision-making and error detection.
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Takeoff Velocity and Rocket Fuel: How to Continue Forward Momentum at BenCon 2024
NYC's My File NYC and New Jersey's unemployment insurance system improvements demonstrate how successful digital innovations can be scaled across various programs, leveraging trust-building, open-source technology, and strategic partnerships.
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Framework for State, Local, Tribal, and Territorial Use of Artificial Intelligence for Public Benefit Administration
This framework outlines USDA’s principles and approach to support States, localities, Tribes, and territories in responsibly using AI in the implementation and administration of USDA’s nutrition benefits and services. This framework is in response to Section 7.2(b)(ii) of Executive Order 14110 on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.
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OECD AI Principles Overview
The OECD AI Principles promote use of AI that is innovative and trustworthy and that respects human rights and democratic values. The principles were adopted in 2019; this webpage provides an overview of the principles and key terms.
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Framing the Risk Management Framework: Actionable Instructions by NIST in their “Govern” Section
This post introduces EPIC's exploration of actionable recommendations and points of agreement from leading A.I. frameworks, beginning with the National Institute of Standards and Technology's AI Risk Management Framework.
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Trustworthy AI (TAI) Playbook
This playbook provides federal agencies with guidance on implementing AI in a way that is ethical, transparent, and aligned with public trust principles.