2026-10-06T17:39:46Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33279963 2026-09-15T23:51:48Z category_25960 category_29635 category_26173 category_29092 item_type_3 month_year_09_2026

Automation Bias and Legal Reasoning in Law Students: Experimental Dataset on Generative AI Errors Miluska Rodriguez-Saavedra (23594950) Economics of education Law reform Educational administration, management and leadership Information systems education Generative Artificial Intelligence, Non-interactive Audiovisual Production, Systematic Mapping Study Automation Bias Legal reasoning law students This dataset contains experimental data collected from 360 law students to examine automation bias and legal reasoning when using generative artificial intelligence systems that may provide erroneous legal information.The study includes 2,880 student-case observations generated under controlled experimental conditions. Participants were assigned to different AI-assistance conditions designed to evaluate how exposure to accurate or erroneous AI-generated legal recommendations influences legal reasoning, error detection, reliance on AI, and decision-making.The dataset supports research on automation bias, generative AI errors, legal reasoning, trust in artificial intelligence, human-AI interaction, and legal education.The files include participant-level and case-level information required for reproducible analysis of the experimental design. The dataset does not contain personally identifying information.Participants: 360 law students Observations: 2,880 student-case observations Research area: Artificial intelligence and legal education Study design: Controlled experimental study 2026-09-15T23:51:48Z Dataset Dataset 10.6084/m9.figshare.33279963.v1 https://figshare.com/articles/dataset/Automation_Bias_and_Legal_Reasoning_in_Law_Students_Experimental_Dataset_on_Generative_AI_Errors/33279963 CC BY 4.0