Automated Policy Evolution Analysis and Suggestion System
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Solution Overview
Problem
Existing systems face challenges in systematically and efficiently comparing and understanding changes in large policy documents and their implications across different jurisdictions, especially in response to external events like pandemics or natural disasters, which requires rapid adaptation of legislative and regulatory policies.
Innovation Solution
A computer-implemented method and system that uses Natural Language Processing and machine learning to compare textual content of policy versions over time, identify semantic differences, and determine causal links between policy changes and external events, providing stakeholders with automated suggestions for policy adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If systematic comparison of large policy documents is performed manually, then understanding of policy changes and implications is achieved, but the process is inherently difficult and time consuming
Solution Approach 1:
The patent replaces manual mechanical comparison methods with automated Natural Language Processing (NLP) systems and machine learning models. These computational systems systematically analyze policy documents, identify semantic differences, and generate change summaries automatically, thereby maintaining high understanding precision while dramatically reducing the time required for policy comparison tasks.
2Loss of information
If manual analysis of policy changes across different jurisdictions is performed, then contextual understanding is achieved, but the process cannot keep pace with rapid policy evolution in response to external events
Solution Approach 1:
The system substitutes human analysts with automated NLP pipelines that can process multiple policy documents from different jurisdictions simultaneously. The machine learning models capture contextual information about policy changes and their implications, maintaining comprehensive understanding while achieving the processing speed necessary to keep pace with rapid policy evolution during crises.
Solution Approach 2:
The system performs preliminary automated analysis of policy changes as they occur, rather than waiting for manual review. By continuously monitoring and analyzing policy documents across jurisdictions in real-time, the system proactively identifies trends and implications, enabling faster response to external events before manual analysis could catch up.
3Measurement precision
If detailed semantic comparison of policy versions is conducted, then accurate identification of changes is achieved, but the complexity of analyzing large policy documents increases
Solution Approach 1:
The patent segments the complex task of policy comparison into multiple manageable components: document preprocessing, entity recognition, semantic relationship extraction, change detection, and implication analysis. Each component is handled by specialized NLP modules or machine learning models, reducing overall system complexity while maintaining high precision in identifying policy changes through systematic breakdown of the analysis process.
Data Source
AI summary
A system and method for analyzing and explaining the temporal evolution of policies. The analysis of the temporal evolution of policies includes determining semantically related changes in the text of the corresponding policies over time and across the different versions of the (two or more) policy documents. An explanation of the temporal evolution of policies is provided consisting of human interpretable information relating each change to one or more events and/or contextual data. A next steps policy change is also suggested that includes a set of policy conditions based on potential future changes of similar policies and contextual data and event data. The suggestions are related to the policy relevant to the target cohort or individual. The system adapts machine learned models by receiving user feedback provided on an analysis of the correctness of the temporal evolution of policies, corresponding explanations and suggestions of the next actions.