_version_ 1866910200179458048
author Ziems, Caleb
Zhao, Dora
Wang, Rose E.
Jörke, Matthew
Rushdi, Ahmad
Deepak, Advit
Yu, Sunny
Agarwal, Anshika
Agarwal, Harshvardhan
Aranguiz-Dias, Gabriela
Bhagirath, Aditri
Breuch, Justine
Chen, Huanxing
Chen, Ruishi
Chen, Sarah
Fan, Haocheng
Fang, William
Fergesen, Cat Gonzales
Frees, Daniel
Gao, Tian
Huang, Ziqing
Jain, Vishal
Jiang, Yucheng
Kalinin, Kirill
Karaca, Su Doga
Khatua, Arpandeep
La, Teland
Levent, Isabelle
Li, Miranda
Li, Xinling
Li, Yongce
Liu, Angela
Oh, Minsik
Paek, Nathan J.
Qin, Anthony
Redmond, Emily
Ryan, Michael J.
Salecha, Aadesh
Shen, Xiaoxian
Singhal, Pranava
Subrahmanya, Shashanka
Tan, Mei
Thawornbut, Irawadee
Vinocour, Michelle
Wang, Xiaoyue
Wang, Zheng
Weng, Henry Jin
Wirawarn, Pawan
Wu, Shirley
Wu, Sophie
Xie, Yichen
Ye, Patrick
Zhang, Sean
Zhang, Yutong
Zhou, Cathy
Zhao, Yiling
Landay, James
Yang, Diyi
author_facet Ziems, Caleb
Zhao, Dora
Wang, Rose E.
Jörke, Matthew
Rushdi, Ahmad
Deepak, Advit
Yu, Sunny
Agarwal, Anshika
Agarwal, Harshvardhan
Aranguiz-Dias, Gabriela
Bhagirath, Aditri
Breuch, Justine
Chen, Huanxing
Chen, Ruishi
Chen, Sarah
Fan, Haocheng
Fang, William
Fergesen, Cat Gonzales
Frees, Daniel
Gao, Tian
Huang, Ziqing
Jain, Vishal
Jiang, Yucheng
Kalinin, Kirill
Karaca, Su Doga
Khatua, Arpandeep
La, Teland
Levent, Isabelle
Li, Miranda
Li, Xinling
Li, Yongce
Liu, Angela
Oh, Minsik
Paek, Nathan J.
Qin, Anthony
Redmond, Emily
Ryan, Michael J.
Salecha, Aadesh
Shen, Xiaoxian
Singhal, Pranava
Subrahmanya, Shashanka
Tan, Mei
Thawornbut, Irawadee
Vinocour, Michelle
Wang, Xiaoyue
Wang, Zheng
Weng, Henry Jin
Wirawarn, Pawan
Wu, Shirley
Wu, Sophie
Xie, Yichen
Ye, Patrick
Zhang, Sean
Zhang, Yutong
Zhou, Cathy
Zhao, Yiling
Landay, James
Yang, Diyi
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2605_06901
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Reflections and New Directions for Human-Centered Large Language Models
Ziems, Caleb
Zhao, Dora
Wang, Rose E.
Jörke, Matthew
Rushdi, Ahmad
Deepak, Advit
Yu, Sunny
Agarwal, Anshika
Agarwal, Harshvardhan
Aranguiz-Dias, Gabriela
Bhagirath, Aditri
Breuch, Justine
Chen, Huanxing
Chen, Ruishi
Chen, Sarah
Fan, Haocheng
Fang, William
Fergesen, Cat Gonzales
Frees, Daniel
Gao, Tian
Huang, Ziqing
Jain, Vishal
Jiang, Yucheng
Kalinin, Kirill
Karaca, Su Doga
Khatua, Arpandeep
La, Teland
Levent, Isabelle
Li, Miranda
Li, Xinling
Li, Yongce
Liu, Angela
Oh, Minsik
Paek, Nathan J.
Qin, Anthony
Redmond, Emily
Ryan, Michael J.
Salecha, Aadesh
Shen, Xiaoxian
Singhal, Pranava
Subrahmanya, Shashanka
Tan, Mei
Thawornbut, Irawadee
Vinocour, Michelle
Wang, Xiaoyue
Wang, Zheng
Weng, Henry Jin
Wirawarn, Pawan
Wu, Shirley
Wu, Sophie
Xie, Yichen
Ye, Patrick
Zhang, Sean
Zhang, Yutong
Zhou, Cathy
Zhao, Yiling
Landay, James
Yang, Diyi
Computation and Language
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.
title Reflections and New Directions for Human-Centered Large Language Models
topic Computation and Language
url https://arxiv.org/abs/2605.06901