This paper introduces the problem of semi-automatically building decision models from eligibility policies for social services, and presents an initial emerging approach to shorten the route from policy documents to executable, interpretable and standardised decision models using AI, NLP and Knowledge Graphs. There is enormous potential of AI to assist government agencies and policy experts in scaling the production of both human-readable and machine executable policy rules, while improving transparency, interpretability, traceability and accountability of the decision making.
The Guide to Robotic Process Automation, including the RPA Playbook provides detailed guidance for federal agencies starting a new RPA program or evolving an existing one.
This report by EPIC investigates how automated decision-making (ADM) systems are used across Washington, D.C.’s public services and the resulting impacts on equity, privacy, and access to benefits.
The U.S. Department of Homeland Security (DHS) Artificial Intelligence (AI) Roadmap outlines the agency's AI initiatives and AI's potential across the homeland security enterprise.
