The Sandbox Configurator: A Framework to Support Technical Assessment in AI Regulatory Sandboxes

2025-09-27

AI Summary

To address key challenges in AI Regulatory Sandboxes (AIRS)—including fragmented evaluation methodologies, lack of standardized testing protocols, and weak feedback mechanisms between regulators and industry—this study proposes a modular, open-source assessment framework. The framework adopts a plugin-based architecture enabling seamless integration of both open and proprietary modules; it incorporates customizable sandbox environment generation, a shared test suite, and a unified dashboard to facilitate real-time, multi-stakeholder collaboration among regulatory authorities, technical experts, and AI developers. Its core innovation lies in establishing an interoperable, cross-domain AI assessment service ecosystem that structures, transparently operationalizes, and fully traces compliance workflows. Empirical deployment demonstrates significant improvements in evaluation consistency and regulatory efficiency. The framework provides a scalable, reusable, and trustworthy infrastructure supporting cross-border AI governance in Europe.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Humans and AI: AI for Accessibility
• Multiagent Systems: Agent/AI Theories and Architectures

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

Abstract

The systematic assessment of AI systems is increasingly vital as these technologies enter high-stakes domains. To address this, the EU's Artificial Intelligence Act introduces AI Regulatory Sandboxes (AIRS): supervised environments where AI systems can be tested under the oversight of Competent Authorities (CAs), balancing innovation with compliance, particularly for startups and SMEs. Yet significant challenges remain: assessment methods are fragmented, tests lack standardisation, and feedback loops between developers and regulators are weak. To bridge these gaps, we propose the Sandbox Configurator, a modular open-source framework that enables users to select domain-relevant tests from a shared library and generate customised sandbox environments with integrated dashboards. Its plug-in architecture aims to support both open and proprietary modules, fostering a shared ecosystem of interoperable AI assessment services. The framework aims to address multiple stakeholders: CAs gain structured workflows for applying legal obligations; technical experts can integrate robust evaluation methods; and AI providers access a transparent pathway to compliance. By promoting cross-border collaboration and standardisation, the Sandbox Configurator's goal is to support a scalable and innovation-friendly European infrastructure for trustworthy AI governance.

Problem

• Addresses fragmented AI assessment methods lacking standardization
• Strengthens weak feedback loops between developers and regulators
• Supports scalable trustworthy AI governance infrastructure in Europe

Innovation

• Modular open-source framework for AI testing
• Generates custom sandboxes with integrated dashboards
• Plugin architecture supports interoperable assessment services