BUILDING RESPONSIBLE AI TESTBED INFRASTRUCTURE

FOR U.S. EDUCATION IN 2025

By Leanlab Education, InnovateEDU, & SCALE Initiative, Stanford Accelerator for Learning

Current educational research and procurement cycles can't keep pace with rapidly evolving AI tools. New technologies emerge faster than researchers can evaluate them and faster than district leaders can process their implications. Without a coordinated infrastructure, insights arrive too late, leaving educators to navigate a confusing marketplace filled with unproven promises.

Our research proposes a national AI testbed infrastructure—sophisticated sandboxes that provide researchers, developers, and policymakers with essential infrastructure to test, evaluate, and refine AI systems in contained, real-world settings.

 

This approach, informed by years of fieldwork from the Global EdTech Trialing Network (GETN), would operationalize shared American values: educator-led, innovative, transparent, privacy-protective, and accessible to all learners.

Key Pillars of  Responsible AI Testbeds for Education:

  • Dual-layer benchmarking for technical accuracy and real-world effectiveness

  • Addressing the "missing middle" in education R&D funding

  • Clear market signals to support smart adoption decisions

  • Federated network approach honoring local context while enabling national learning

  • Investor-friendly commercialization pipelines