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Using AI to Generate Option C Scaling Ideas: A Case Study in Early Education

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  • Faith Fatchen
  • John List
  • Francesca Pagnotta

Abstract

In recent years, field experiments have reshaped policy worldwide, but scaling ideas remains a thorny challenge. Perhaps the most important issue facing policymakers today is deciding which ideas to scale. One approach to attenuate this information problem is to augment traditional A/B experimental designs to address questions of scalability from the beginning. List 2024 denotes this approach as “Option C†thinking. Using early education as a case study, we show how AI can overcome a critical barrier in Option C thinking – generating viable options for scaling experimentation. By integrating AI-driven insights, this approach strengthens the link between controlled trials and large-scale implementation, ensuring the production of policy-based evidence for effective decision-making.

Suggested Citation

  • Faith Fatchen & John List & Francesca Pagnotta, 2025. "Using AI to Generate Option C Scaling Ideas: A Case Study in Early Education," Framed Field Experiments 00822, The Field Experiments Website.
    • Handle: RePEc:feb:framed:00822
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