Draft:Norm Engineering

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Declined by Greenman 30 hours ago. Last edited by Greenman 30 hours ago. Reviewer: Inform author.

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Norm engineering translates complex legal texts into structured, executable models. It is an innovation within Regulatory Technology (RegTech). By converting legal language into machine-readable formats, it simplifies compliance by making regulations easier to interpret, track, and implement.

What is norm engineering?

Norm engineering converts legal language and regulations into structured data models. This standardized approach enables organizations to automate regulatory interpretation, improving accuracy in analyzing and monitoring legal requirements.

A Norm Engineering program, developed in collaboration with TNO, the University of Amsterdam, and other industry partners, focuses on creating tools for clear and unambiguous regulatory interpretation. The FLINT language^[1], a key outcome, translates social, ethical, and legal norms into a format understandable by both humans and systems, enabling seamless automation.

Key Concepts

Machine-Readable Regulations (MRR): Norm Engineering converts regulatory language into formats readable by machines. Systems can thus automate regulatory data processing, saving time and reducing errors, ensuring organizations stay current with changing standards.
Standardization: Standardizing regulatory interpretations ensures consistency across different compliance applications. By establishing universal standards, organizations can implement uniform practices across diverse frameworks, even in overlapping jurisdictions.
Relation Between Norms and Grounds: Understanding norms (rules) and grounds (conditions triggering rules) is essential for precise decision-making. By modeling these relationships, systems apply regulations based on specific contexts, potentially reducing compliance risks and enhancing accuracy. Compared to modeled regulation dependencies, documents that describe that in the format of text are often more complex and harder to interpret.^[2]

Potential Benefits of Norm Engineering

Norm engineering can offer various compliance advantages:

Efficiency: Automated models can reduce time spent on manual interpretation;

Traceability: Machine-readable models provide a structured trace from regulation to implementation;

Scalability: Standardization can support compliance solutions across different sectors and regions;

Enhanced decision-making: Linking norms and grounds can contribute to more accurate, context-specific regulatory applications.

Challenges

While having advantages, norm engineering also faces certain challenges:

Complex legal language: Translating legal terms into executable models requires navigating intricate language and interpretation;

Adoption barriers: Gaining consensus on standards can be challenging due to varying legal and industry requirements.

Applications

Norm engineering can be applied in multiple areas, including regulatory compliance and lawmaking. By supporting compliance accuracy, fostering transparency, and promoting innovation, it enables adaptable RegTech tools suited for various industries.

Conclusion

As regulations grow more complex, structured and automated compliance models offer a potential solution. Collaborative initiatives, such as FLINT^[1], are advancing norm engineering, working toward more accessible, transparent, and scalable compliance frameworks.

References

^ ^a ^b Breteler, Jeroen; van Gessel, Thom; Biagioni, Giulia; van Doesburg, Robert (2023-09-11), Acosta, Maribel; Peroni, Silvio; Vahdati, Sahar; Gentile, Anna-Lisa (eds.), "The FLINT Ontology: An Actor-Based Model of Legal Relations", Studies on the Semantic Web, IOS Press, doi:10.3233/ssw230016, ISBN 978-1-64368-424-6, retrieved 2025-01-27
^ Ghanavati, Sepideh; Amyot, Daniel; Peyton, Liam (October 2008). "Comparative Analysis between Document-based and Model-based Compliance Management Approaches". 2008 Requirements Engineering and Law. IEEE: 35–39. doi:10.1109/relaw.2008.2. ISBN 978-1-4244-4085-6.

[:0-1] Breteler, Jeroen; van Gessel, Thom; Biagioni, Giulia; van Doesburg, Robert (2023-09-11), Acosta, Maribel; Peroni, Silvio; Vahdati, Sahar; Gentile, Anna-Lisa (eds.), "The FLINT Ontology: An Actor-Based Model of Legal Relations", Studies on the Semantic Web, IOS Press, doi:10.3233/ssw230016, ISBN 978-1-64368-424-6, retrieved 2025-01-27

[2] Ghanavati, Sepideh; Amyot, Daniel; Peyton, Liam (October 2008). "Comparative Analysis between Document-based and Model-based Compliance Management Approaches". 2008 Requirements Engineering and Law. IEEE: 35–39. doi:10.1109/relaw.2008.2. ISBN 978-1-4244-4085-6.

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