Efficient Dynamic Shielding for Parametric Safety Specifications

2025-05-28

AI Summary

Traditional static shielding mechanisms for AI autonomous systems suffer from high latency and inefficiency when addressing dynamically evolving runtime safety requirements, necessitating repeated full recomputation. Method: This paper proposes an adaptive dynamic protection mechanism based on a novel two-phase paradigm—“static pre-design + dynamic online adaptation”—integrating parametric safety specification modeling, formal synthesis of safety controllers, and a lightweight, maximally permissive online update algorithm to enable real-time responsiveness to new safety constraints. Results: Experiments on robot navigation in unknown environments demonstrate that offline controller design takes only several minutes, while each online adaptation requires merely 0.1–3 seconds—up to 5× faster than brute-force recomputation. The approach significantly enhances both the timeliness and adaptability of runtime safety enforcement without compromising formal guarantees.

Technology Category

• Natural Language Processing: Safety and Robustness
• Multiagent Systems: Adversarial Agents
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Shielding has emerged as a promising approach for ensuring safety of AI-controlled autonomous systems. The algorithmic goal is to compute a shield, which is a runtime safety enforcement tool that needs to monitor and intervene the AI controller's actions if safety could be compromised otherwise. Traditional shields are designed statically for a specific safety requirement. Therefore, if the safety requirement changes at runtime due to changing operating conditions, the shield needs to be recomputed from scratch, causing delays that could be fatal. We introduce dynamic shields for parametric safety specifications, which are succinctly represented sets of all possible safety specifications that may be encountered at runtime. Our dynamic shields are statically designed for a given safety parameter set, and are able to dynamically adapt as the true safety specification (permissible by the parameters) is revealed at runtime. The main algorithmic novelty lies in the dynamic adaptation procedure, which is a simple and fast algorithm that utilizes known features of standard safety shields, like maximal permissiveness. We report experimental results for a robot navigation problem in unknown territories, where the safety specification evolves as new obstacles are discovered at runtime. In our experiments, the dynamic shields took a few minutes for their offline design, and took between a fraction of a second and a few seconds for online adaptation at each step, whereas the brute-force online recomputation approach was up to 5 times slower.

Problem

• Dynamic shields adapt to changing safety specifications at runtime
• Traditional shields require recomputation for updated safety requirements
• Efficient online adaptation reduces delays in safety enforcement

Innovation

• Dynamic shields adapt to runtime safety changes
• Static design for parametric safety specifications
• Fast online adaptation using standard shield features