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Cognitive Forcing in a Meal-Substitution Experiment
In a meal-substitution experiment, Buçinca, Malaya, and Gajos compared three cognitive forcing designs—requesting advice, deciding before seeing advice, and waiting 30 seconds—with simple explainable-AI designs. Among 199 retained participants, the forcing designs reduced agreement with incorrect simulated-AI advice when identifying the ingredient highest in carbohydrates. This significant finding concerned the design-category comparison, not superiority of every individual design; the overreliance difference for the complete replacement decision was nonsignificant. Overreliance remained, and lower-overreliance designs received less favorable subjective ratings. These findings concern the tested simulated-AI task, not general LLM or clinical effectiveness. Buçinca, Malaya, and Gajos (2021)
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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