Changing only the prompter's age and gender in AI coding prompts produces statistically significant differences in generated website interface design, template content, and code structure across 800 generated websites and a 20-person user study.
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Plural LLM setups (expert+peer in math; role-specialized pair in writing) improve post-task math performance and preserve writing idea diversity better than single-assistant or no-AI baselines.
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Biased or Personalized? The Impact of Personal Information on AI-driven Development
Changing only the prompter's age and gender in AI coding prompts produces statistically significant differences in generated website interface design, template content, and code structure across 800 generated websites and a 20-person user study.
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Human Thinking under Plural LLM Assistance: Mathematical Problem Solving and Open-Ended Writing
Plural LLM setups (expert+peer in math; role-specialized pair in writing) improve post-task math performance and preserve writing idea diversity better than single-assistant or no-AI baselines.