Despite a global user base adopting large language models (LLMs) for daily writing tasks, model suggestions tend to align with Western values. Research has shown users commonly accept a high fraction of these AI suggestions, homogenizing writing styles and rendering outputs more ``Western'' than intended. While this suggests a need to reduce AI reliance, it remains unknown what kind of interventions could achieve this. Can framing the AI with specific values, and comparing it to one's own, make users less susceptible to overreliance and support more unique writing? We tested this hypothesis in a between-subjects online experiment with Indian and American participants (n=149) in which they were asked to perform AI-supported writing tasks, either 1) without an intervention, 2) after seeing an overview of the AI's framed values, or 3) after seeing an overview of the AI's framed values compared to their own. Our results show that seeing the AI's framed values reduces AI reliance, i.e., the proportion of the final essay generated by the AI, by an average of 20\%. Additionally, when participants saw an overview of the AI's framed values (without comparison to their own values), the final essays contain more unique text than without intervention. Our findings emphasize the importance of educating users about potential value biases in AI, showing that raising awareness with a simple overview of values encourages users to personalize their writing.

翻译：尽管全球用户已广泛采用大型语言模型（LLMs）进行日常写作任务，但模型给出的建议往往倾向于西方价值观。研究表明，用户通常会接受这些人工智能建议的很大部分，从而导致写作风格趋同，并使输出内容比预期更加“西化”。虽然这表明需要减少对人工智能的依赖，但目前尚不清楚何种干预措施能够实现这一目标。为人工智能设定特定价值观框架，并将其与用户自身价值观进行比较，能否降低用户过度依赖的风险，从而支持更具独特性的写作？我们通过一项针对印度和美国参与者（n=149）的受试者间在线实验验证了这一假设，实验要求参与者完成人工智能辅助写作任务：1）无干预措施；2）在了解人工智能设定的价值观框架概述后；3）在了解人工智能设定价值观框架并与自身价值观比较后。结果显示，了解人工智能的价值观框架可使人工智能依赖度（即最终作文中由人工智能生成内容的比例）平均降低20%。此外，当参与者仅了解人工智能价值观框架概述（未与自身价值观比较）时，最终作文中包含的独特文本比无干预情况下更多。我们的研究结果强调了教育用户认识人工智能中潜在价值偏差的重要性，表明通过简单的价值观框架概述提高用户意识，可促使用户实现更具个性化的写作。