A Framework to Support Technical Assessment in AI Regulatory Sandboxes (arxiv.org)

The paper introduces the Sandbox Configurator, an open-source, modular framework designed to operationalize AI Regulatory Sandboxes (AIRS) created under the EU Artificial Intelligence Act. It responds to persistent problems—fragmented assessment methods, weak feedback loops between developers and regulators, and lack of standardisation—by letting users pick domain-relevant tests from a shared library and spin up customised sandbox environments with integrated dashboards. The goal is to give Competent Authorities (CAs) structured workflows to apply legal obligations, technical experts a plug-in surface to add robust evaluation methods, and AI providers a transparent, repeatable route toward compliance, especially useful for startups and SMEs working in high-stakes domains. Technically, the Configurator emphasizes a plug-in architecture that supports both open and proprietary modules, enabling interoperable AI assessment services while preserving IP where needed. By combining reusable test suites, configurable execution environments, and dashboarded results, it standardises evaluations, strengthens auditability and reproducibility, and tightens developer–regulator feedback loops. For the AI/ML community this promises faster, more consistent technical assessments, better cross-border collaboration, and a scalable infrastructure to balance innovation with trustworthy governance as models move into regulated, high-impact applications.