AI Sandboxing
Isolated environments for testing AI systems safely before deployment, limiting their access and capabilities.
Overview
AI sandboxing refers to running AI systems in controlled, isolated environments that limit their access to external resources, data, and capabilities. This allows researchers and developers to observe AI behavior, test for safety issues, and evaluate capabilities without risk of real-world harm.
Key Details
Sandboxes can be technical (containerized environments, restricted API access, simulated environments) or regulatory (designated testing zones with relaxed rules, like the UK FCA's regulatory sandbox). For advanced AI systems, sandboxing is a key safety measure — testing whether a model attempts to access unauthorized resources, manipulate evaluators, or exhibit deceptive behavior. As AI capabilities increase, robust sandboxing becomes increasingly important for safe development.