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.
Government agencies adopting generative AI tools seems inevitable at this point. But there is more than one possible future for how agencies use generative AI to simplify complex government information.
This report presents evidence on the use of algorithmic accountability policies in different contexts from the perspective of those implementing these tools, and explores the limits of legal and policy mechanisms in ensuring safe and accountable algorithmic systems.
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.
The state of Indiana developed a policy framework for the ethical and efficient use of artificial intelligence (AI) within state agencies. The policy adopts the National Institute of Standards and Technology’s AI Risk Management Framework to manage potential risks effectively. It also details the applicability of the actions undertaken by the Office of the Chief Data Officer (OCDO) to enable the deployment of trustworthy AI systems.
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.
Organisation for Economic Co-operation and Development (OECD)
This study evaluates the use of RPA technology by three states to automate SNAP administration, focusing on repetitive tasks previously performed manually.
This essay explains why the Center on Privacy & Technology has chosen to stop using terms like "artificial intelligence," "AI," and "machine learning," arguing that such language obscures human accountability and overstates the capabilities of these technologies.
This report explores how AI is currently used, and how it might be used in the future, to support administrative actions that agency staff complete when processing customers’ SNAP cases. In addition to desk and primary research, this brief was informed by input from APHSA’s wide network of state, county, and city members and national partners in the human services and related sectors.
American Public Human Services Association (APHSA)
