Envisioning a Human-AI collaborative system to transform policies into decision models
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…
The document presents a human-AI collaborative system designed to convert complex policy documents, particularly social service eligibility rules, into interpretable and executable decision models.
It describes the use of AI, NLP, and Knowledge Graphs to support policy experts in extracting rules and data, emphasizes the importance of standards like DMN for transparency and traceability, and discusses the challenges and need for human oversight, labeled datasets, and user feedback in automating policy-to-code translation.
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