Runtime Enforcement for Operationalizing Ethics in Autonomous Systems

2026-04-04

AI Summary

This work addresses the challenge of enabling autonomous systems to dynamically comply with social, legal, ethical, empathetic, and cultural (SLEEC) norms during runtime. It proposes [e-mail], a novel framework that integrates Abstract State Machines (ASM) with the MAPE-K architecture to establish a runtime enforcement mechanism capable of dynamically adding or removing ethical rules and adapting them contextually. By leveraging formal modeling, the framework supports real-time monitoring, evaluation, and adjustment of system behavior. Empirical evaluation in an assistive robotics scenario demonstrates that the system rigorously adheres to ethical principles while incurring negligible runtime overhead, thereby validating the framework’s effectiveness and practicality.

Abstract

This paper addresses the challenge of operationalizing ethics in autonomous systems through runtime enforcement. It first conceptualizes the system's ethical space and outlines a structured ethics assurance process. Building on this foundation, it introduces an enforcement subsystem that operationalizes ethical rules, specifically social, legal, ethical, empathetic, and cultural (SLEEC) requirements, through the Abstract State Machine (ASM) formalism. The enforcement subsystem is built on the MAPE-K control-loop architecture for monitoring and controlling the system's ethical behavior, and it relies on an ASM-based runtime model of the ethical rules to enforce. This enables the dynamic evaluation, adaptation, and enforcement of ethical behavior within a runtime formal model. The overall approach, named [e-mail], is demonstrated on an assistive robot scenario, showcasing how both the robot's behavior and the governing ethical rules can dynamically adapt to contextual changes. By leveraging a flexible runtime model, [e-mail] accommodates changes such as the addition or removal of SLEEC rules, ensuring a robust and evolvable approach to ethical assurance in autonomous systems. The evaluation of [e-mail] shows that it effectively ensures the system's adherence to ethical principles with negligible execution time overhead.

Problem

• Runtime Enforcement
• Ethics Operationalization
• Autonomous Systems
• SLEEC Requirements
• Ethical Assurance

Innovation

• Runtime Enforcement
• Abstract State Machine (ASM)
• MAPE-K Architecture
• Ethical Assurance
• SLEEC Requirements