Reflections and New Directions for Human-Centered Large Language Models
For LLM developers and researchers, this work offers a structured approach to prioritize human values throughout the model lifecycle, though it is primarily a conceptual framework without empirical validation.
This paper proposes a framework for Human-Centered Large Language Models (HCLLMs) that integrates NLP, HCI, and responsible AI, arguing that human concerns must be addressed at every stage of the development pipeline. It provides recommendations for each stage and a case study on the future of work.
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.