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ECR pour l'évaluation humain-IA
This report examines human uplift studies — randomized controlled trial (RCT)-style evaluations of artificial intelligence (AI) systems. Analysis of interviews with 16 practitioners identifies methodological challenges and emerging solutions
Articles sources
RAND Corporation (United States) | Mar 19, 2026
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Implementing RCTs in AI evaluations could slow down innovation, as the rigorous process may hinder rapid development and deployment of new technologies.
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RCTs provide a rigorous framework for evaluating AI systems, ensuring their effectiveness and reliability in real-world applications.
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While RCTs can enhance understanding of AI impacts, they should be complemented with qualitative insights for a holistic view.
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Relying on RCTs for AI evaluation may overlook important contextual factors, leading to misleading conclusions about system performance.
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The challenges identified in RCTs for AI evaluation highlight the need for innovative methodologies to better assess AI's societal implications.
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