让大模型更懂人，从设计到部署全程考虑用户需求。
Reflections and New Directions for Human-Centered Large Language Models
- 构建全流程人本大模型框架，融合NLP、HCI与责任AI视角。
- 强调在数据、训练、评估等各阶段持续关注人类价值与偏好。
- 适合关注AI伦理、用户体验与负责任AI的开发者与研究者。
大型语言模型正日益影响用户的私人与职业生活，在商业、教育、金融、医疗、法律和科学等领域广泛应用。随着其全球影响力上升，亟需以兼顾技术能力与人类优先原则的方式构建、评估和部署这些系统。本文提出人本大模型（HCLLM）框架，整合自然语言处理（NLP）、人机交互（HCI）与负责任AI的视角。我们认为，模型开发者应不仅在训练后阶段简单考虑人类关切，而应在整个模型生命周期中严谨、细致地回应人类的需求、偏好、价值观与目标。本文为系统设计、数据获取、模型训练、评估及负责任部署等各阶段提供以人为本的洞见与建议，并通过一个案例研究探讨人本大模型对未来工作的影响。
原文摘要 · Abstract (English)
Large Language Models (LLMs) are increasingly shaping the private and professional lives of users, with numerous applications in business, education, finance, healthcare, law, and science. With this rise in global influence comes greater urgency to build, evaluate, and deploy these systems in a manner that prioritizes not only technical capabilities but also human priorities. This work presents a framework for developing Human-Centered Large Language Models (HCLLMs), which integrates perspectives from Natural Language Processing (NLP), Human-Computer Interaction (HCI), and responsible AI. Considering the ethics, economics, and technical objectives of language modeling, we argue that model developers need to address human concerns, preferences, values, and goals, not only during a cursory post-training stage, but rather with rigor and care at every stage of the pipeline. This paper offers human-centered insights and recommendations for developers at each stage, from system design to data sourcing, model training, evaluation, and responsible deployment. Then we conclude with a case study, applying these insights to understand the future of work with HCLLMs.
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