Penn State CSRAI Research
Park, S., Cha, J., Park, E., & Sundar, S. S . (2026, April). Thriving, Not Just Growing: Structural Sustainability as the Key to Quality in Online Wellness Communities . In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-17). Chen, C., Liao, M., Phadnis, A. A., Li, Y., High, A., Abdullah, S ., & Sundar, S. S. (2026, April). Prompt coaching for inclusiveness: A media literacy approach to increase users’ awareness of algorithmic bias and prompting efficacy . In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-16). Tschopp, M. V., Chen, C., Wischnewski, M., Gieselmann, M., Schöning, J., Sundar, S. S. , & Sassenberg, K. (2026, July). Does Humanizing Chatbots Promote or Hinder Voice Shopping? . In Proceedings of the 8th ACM Conference on Conversational User Interfaces (pp. 1-14). Moran, L. H., Kee, S. C., Wiese, C. W., Arriaga, R. I., Abdullah, S ., & Sherrill, A. M. (2025). Artificial intelligence as a feedback teammate for treatment delivery: Cognitive behavioral therapists’ hopes and fears . Cognitive and Behavioral Practice . Swinger, N., Baseman, C. M., Ryu, M., Abdullah, S., Wiese, C. W., Sherrill, A. M., & Arriaga, R. I. (2025). There's No" I" in TEAMMAIT: Impacts of Domain and Expertise on Trust in AI Teammates for Mental Health Work . Proceedings of the ACM on Human-Computer Interaction , 9 (2), 1-36. Qiu, L., Saragih, I. D., Fick, D. M., Sundar, S. S. , & Abdullah, S. (2025, April). Voice assistants to deliver cognitive stimulation therapy for persons living with dementia. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-7). Dulam, S., & Dancy, C. L . (2025, September). Computational Cognitive Modeling to understand the effects of Racializing AI on Human-AI cooperation with PigChase Task. In 2025 IEEE International Symposium on Technology and Society (ISTAS) (pp. 1-9). IEEE. Wenger, J. D., Cameron, C. D., & Inzlicht, M. (2026). People choose to receive human empathy despite rating AI empathy higher . Communications Psychology . Huang, S. H., Huang, C. Y. , Shen, H., & Deng, Y. (2025). Situation Awareness of Conversational Assistants in the Age of LLMs . Ng, H. Y. S., Hsu, T. Y., Ramakrishnan, A. A., Kveton, B., Lipka, N., Dernoncourt, F., ... & Huang, T. H. K . (2025). LaMP-Cap: Personalized Figure Caption Generation With Multimodal Figure Profiles . arXiv preprint arXiv:2506.06561 . Jang, E., & Sundar, S. S. (2026). Less Interaction But More Explanation: A Communication Perspective on Agentic AI Interfaces . arXiv preprint arXiv:2605.01610 . Zhou, Y., Chen, E., Pisipati, M., Xiong, A. , & Rajtmajer, S. (2025). Effect of AI Performance, Risk Perception, and Trust on Human Dependence in Deepfake Detection AI System . Proceedings of the ACM on Human-Computer Interaction , 9 (7), 1-24. Chen, C., Liao, M., Phadnis, A. A., Li, Y., High, A., Abdullah, S ., & Sundar, S. S . (2026, April). Prompt coaching for inclusiveness: A media literacy approach to increase users’ awareness of algorithmic bias and prompting efficacy . In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-16). Zhang, H. E., Wu, C., Xie, J., Lyu, Y., Cai, J., & Carroll, J. M . (2025). Harnessing the power of AI in qualitative research: Exploring, using and redesigning ChatGPT . Computers in Human Behavior: Artificial Humans , 4 , 100144. Hwang, A. H. C., Bernstein, M. S., Sundar, S. S ., Zhang, R., Horta Ribeiro, M., Lu, Y., & Shamma, D. A. (2025, April). Human Subjects Research in the Age of Generative AI: Opportunities and Challenges of Applying LLM-Simulated Data to HCI Studies . In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-7). Choudhury, F. A., Leicht, E., Bislig, J. E., Guo, H., & Yadav, A . (2025). Designing User-Centric Metrics for Evaluation of Counterfactual Explanations . arXiv preprint arXiv:2507.15162 . Swinger, N., Moran, L., Abdullah, S. , Wiese, C. W., Lee, U., Tseng, Y. C., ... & Arriaga, R. I. (2025, April). Technoskepticism or Justified Caution? The Future of Human-Centered AI in Mental Health Care . In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-5). Zhang, H., Wu, C., Xie, J., Lyu, Y., Cai, J., & Carroll, J. M. (2025). Harnessing the power of AI in qualitative research: Exploring, using and redesigning ChatGPT. Computers in Human Behavior: Artificial Humans, 4 , 100144. Zhang, H., Fu, X., & Carroll, J. M. (2025). Augmenting Image Annotation: A Human-LMM Collaborative Framework for Efficient Object Selection and Label Generation. arXiv preprint arXiv:2503.11096. Huang, S. H., Huang, C. Y., Shen, H., Deng, Y. & Huang, T, H. K. (2025). Situation Awareness of Conversational Assistants in the Age of LLMs. In CHI'25 Workshop: "AutomationXP25: Hybrid Automation Experiences" Nahar, M., Lee, E. J., Park, J. W., & Lee, D. (2025). Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations. arXiv preprint arXiv:2504.01153. Liu, H., Wang, Y., Zhang, X., Zhang, F., Wang, W., Ma, F. , & Yu, H. (2025, April). Multi-Label Few-Shot Image Classification via Pairwise Feature Augmentation and Flexible Prompt Learning. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 39, No. 5, pp. 5433-5441). Hwang, A. H. C., Bernstein, M. S., Sundar, S. S. , Zhang, R., Horta Ribeiro, M., Lu, Y., ... & Shamma, D. A. (2025, April). Human Subjects Research in the Age of Generative AI: Opportunities and Challenges of Applying LLM-Simulated Data to HCI Studies. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-7) . Ahn, J. J., & Yin, W. (2025). Prompt-Reverse Inconsistency: LLM Self-Inconsistency Beyond Generative Randomness and Prompt Paraphrasing. arXiv preprint arXiv:2504.01282. Ma, R., Zhang, Z., Gui, X. , & Kou, Y. (2024, July). Labeling in the Dark: Exploring Content Creators’ and Consumers’ Experiences with Content Classification for Child Safety on YouTube. In Proceedings of the 2024 ACM Designing Interactive Systems Conference (pp. 1518-1532). Zhang, W., Majumdar, A., & Yadav, A. (2024). Code-mixed LLM: Improve Large Language Models' Capability to Handle Code-Mixing through Reinforcement Learning from AI Feedback. arXiv preprint arXiv:2411.09073. Hsu, Y. L., Chen, J. N., Chiang, Y. F., Liu, S. C., Xiong, A. , & Ku, L. W. (2024, June). Enhancing Perception: Refining Explanations of News Claims with LLM Conversations. In Findings of the Association for Computational Linguistics: NAACL 2024 (pp. 2129-2147). Maharjan, R., Mendu, S., Mariani, M., Abdullah, S. , & Hansen, J. P. (2024). Exploring user engagement with real-time verbal feedback from an exoskeleton-based virtual exercise coach. Digital Health, 10 , 20552076241302652. Zhang, H., Falletta, N. J., Xie, J., Yu, R., Lee, S., Billah, S. M. , & Carroll, J. M. (2025, January). Enhancing the Travel Experience for People with Visual Impairments through Multimodal Interaction: NaviGPT, A Real-Time AI-Driven Mobile Navigation System. In The 2025 ACM International Conference on Supporting Group Work (pp. 29-35). Bhadra, R., Sahu, M., Agrebi, M., Singh, P. K., & Badr, Y. (2024). A Hybrid Deep Feature Selection Framework for Speaker Accent Recognition. In Leveraging Computer Vision to Biometric Applications (pp. 154-177). Islam, M. T., Kabir, I., Pearce, E. A., Reza, M. A., & Billah, S. M. (2024, October). Identifying Crucial Objects in Blind and Low-Vision Individuals' Navigation. In Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility (pp. 1-8). Zhang, X., Tang, X., Liu, H., Wu, Z., He, Q., Lee, D. , & Wang, S. (2024). Divide-Verify-Refine: Aligning LLM Responses with Complex Instructions. arXiv preprint arXiv:2410.12207. Chen, C., Lee, S., Jang, E., & Sundar, S. S. (2024). Is Your Prompt Detailed Enough? Exploring the Effects of Prompt Coaching on Users' Perceptions, Engagement, and Trust in Text-to-Image Generative AI Tools. In Proceedings of the Second International Symposium on Trustworthy Autonomous Systems (pp. 1-12). Chen, C., Liao, M., Walther, J. B., & Sundar, S. S. (2024). When an AI doctor gets personal: The effects of social and medical individuation in encounters with human and AI doctors. Communication Research, 51 (7), 747-781. Wu, C., Wang, X., Carroll, J. , & Rajtmajer, S . (2024, May). Reacting to Generative AI: Insights from Student and Faculty Discussions on Reddit. In Proceedings of the 16th ACM Web Science Conference (pp. 103-113). Holster, J. (2024). Augmenting Music Education through AI: Practical Applications of ChatGPT. Music Educators Journal, 110 (4), 36-42. Zhang, H., Wu, C., Xie, J., Rubino, F., Graver, S., Kim, C ., Carroll, J.M. , & Cai, J. (2024). When Qualitative Research Meets Large Language Model: Exploring the Potential of QualiGPT as a Tool for Qualitative Coding. arXiv preprint arXiv:2407.14925. Huang, S. H., & Huang, T.-H. “Kenneth.” (2024, May). On Replacing Humans with Large Language Models in Voice-Based Human-in-the-Loop Systems. In Proceedings of the AAAI Symposium Series, 3 (1), 45-49. Wu, S., Oltramari, A., Francis, J., Giles, C. L. , & Ritter, F. E. (2024). Cognitive LLMs: Towards Integrating Cognitive Architectures and Large Language Models for Manufacturing Decision-making. arXiv preprint arXiv:2408.09176. Yu, R., Lee, S., Xie, J., Billah, S. M., & Carroll, J. M. (2024). Human–AI Collaboration for Remote Sighted Assistance: Perspectives from the LLM Era. Future Internet, 16(7), 254. Gupta, V., Belland, B. R., Billups, A., & Passonneau, R. J. (2023). AI for Coding Education Meta-analyses: An Open-Science Approach that Combines Human and Machine Intelligence. In T. Schlippe, E. C. K. Cheng, & T. Wang (Eds.), Artificial Intelligence in Education Technologies: New Development and Innovative Practices (pp. 14–29). Springer Nature. Carroll, J. M. (2022). Why should humans trust AI? Interactions , 29 (4), 73–77. Cotter, K. (2023). “Shadowbanning is not a thing”: Black box gaslighting and the power to independently know and credibly critique algorithms. Information, Communication & Society , 26 (6), 1226–1243.You, Y., Kou, Y., Ding, X., & Gui, X. (2021). The Medical Authority of AI: A Study of AI-enabled Consumer-Facing Health Technology. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems , 1–16. Uchendu, A., Lee, J., Shen, H., Le, T., Huang, T.-H. “Kenneth,” & Lee, D. (2023). Does Human Collaboration Enhance the Accuracy of Identifying LLM-Generated Deepfake Texts? Proceedings of the AAAI Conference on Human Computation and Crowdsourcing , 11 (1), Article 1. Chakravorti, T., Singh, V., Rajtmajer, S., McLaughlin, M., Fraleigh, R., Griffin, C., Kwasnica, A., Pennock, D., & Giles, C. L. (2022). Artificial prediction markets present a novel opportunity for human-AI collaboration Guo, X., Huang, K., Liu, J., Fan, W., Vélez, N., Wu, Q., Wang, H., Griffiths, T. L., & Wang, M. (2024). Embodied LLM Agents Learn to Cooperate in Organized Teams Adenuga, I. J., Hanrahan, B. V., Wu, C., & Mitra, P . (2022). Living Documents: Designing for User Agency over Automated Text Summarization . In CHI Conference on Human Factors in Computing Systems Extended Abstracts (pp. 1-6). Carroll, J. M . (2022). Why should humans trust AI? . Interactions , 29 (4), 73-77.Chen, J., Doryab, A., Hanrahan, B. V., Yousfi, A., Beck, J., Wang, X., ... & Carroll, J. M . (2019). 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Designing for responsible trust in AI: A communication perspective . Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT '22) , 1257–1268. Shen, H., & Huang, T. H . (2020). How useful are the machine-generated interpretations to general users? a human evaluation on guessing the incorrectly predicted labels. In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (Vol. 8, pp. 168-172). Shin, D., Zhong, B., & Biocca, F. A. (2020). Beyond user experience: What constitutes algorithmic experiences? International Journal of Information Management , 52 , 102061. Sundar, S. S. (2020). Rise of machine agency: A framework for studying the psychology of human-AI interaction (HAII) . Journal of Computer-Mediated Communication , 25 (1), 74-88.Sundar, S. S., & Lee, E.-J. (2022). Rethinking Communication in the Era of Artificial Intelligence . Human Communication Research , 48 (3), 379–385.You, Y., & Gui, X . (2020). 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Articles
Bouneffouf, D., Riemer, M., & Varshney, K. R. (2026, March). The Shepherd Test: How Will Super Intelligent Agents Balance Care and Control in Asymmetric Relationships? . In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 40, No. 46, pp. 39675-39681). Li, Z., Kim, N., & Lou, C. (2026). Into the black box: Laypeople's folk theories about generative artificial intelligence chatbots . Big Data & Society , 13 (2), 20539517261447838. Ng, R., & Chow, T. Y. J. (2026). Prompt engineering in the age of generative AI: Insights from public discourse on social media . PLoS One , 21 (6), e0351077. Wang, D., Song, W., Ni, J., Zheng, Q., Zhou, Y., Liang, K., ... & Cao, C. G. (2026, April). Should the AI Speak First? Evaluating Proactive vs. Reactive Facilitation in Mixed-Reality Medical Training . In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-19). Geuenich, J., Joublin, F., Ceravola, A., Brandenburg, S., & Dodge, J. (2026). AI Can See What You Can’t See: How LLM-Agents Complement Human-Based Gender-Inclusive Usability Testing . ACM Transactions on Interactive Intelligent Systems , 16 (2), 1-34. Lehmann, F., Shauchenka, K., & Buschek, D. (2026, April). Collaborative Document Editing with Multiple Users and AI Agents . In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-27). Yin, M., Chiang, A., Cox, S. R., & Xiao, R. (2026). " It Felt a Bit Eerie": Exploring Humanlike Interactions During Collaborative Writing with an Artificial Agent . arXiv preprint arXiv:2605.24729 . Zhu, H., Wang, C., Xiao, Q., & Shen, H. (2026). Design Principles for Human-Agent Interaction . arXiv preprint arXiv:2606.20630 . Shi, H., & DiFranzo, D. (2026). Human Control Is the Anchor, Not the Answer: Early Divergence of Oversight in Agentic AI Communities . arXiv preprint arXiv:2602.09286 . Zhao, J., Li, S., Shen, X., Sukuti, S. S., Barbareschi, G., & Sato, C. (2026, June). Using Generative AI to Design a Recreational Service in a Japanese Aging Community . In Proceedings of the 2026 Designing Interactive Systems Conference (pp. 832-852). Zhang, W., Liu, T., Taclis Luo, Y., & Pang, P. (2026). Dynamic Evolution of Needs and Interaction Experiences in GenAI Health Video Co-Design Workshops for Older Adults: BERTopic-Based Analysis . International Journal of Human–Computer Interaction , 1-25. Cui, M., Li, W., & Kamoche, K. (2026). Building trust in decision‐support artificial intelligence: A boundary spanning perspective . Information Systems Journal , 36 (3), 435-456. Regona, M., Yigitcanlar, T., Hon, C., & Teo, M. (2026). Building Trust in Artificial Intelligence: A Systematic Review through the Lens of Trust Theory . ACM Computing Surveys . Humberd, B. K., & Latham, S. F. (2026). When AI becomes an agent of the firm: examining the evolution of AI in organizations through an agency theory lens . Journal of Management Studies , 63 (2), 668-694. 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In Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-10). Neumann, A., Pi, Y., & Singh, J. (2026, April). Who Controls the Conversation? User Perspectives on Generative AI (LLM) System Prompts . In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-37). Böckle, M., Mohme, U., & Bick, M. (2026). Design Thinking and AI: Facilitating HCAI Solutions . In Handbook of Human-Centered Artificial Intelligence (pp. 1-61). Singapore: Springer Nature Singapore. Weisz, J. D., He, J., & Muller, M. (2025). Human-Centered AI Design Principles for Generative AI . In Handbook of Human-Centered Artificial Intelligence (pp. 1-73). Singapore: Springer Nature Singapore. Rezaev, A. V., & Tregubova, N. D. (2025). Looking at human-centered artificial intelligence as a problem and prospect for sociology: An analytic review . Current Sociology , 73 (1), 120-138. Schmager, S., Pappas, I. O., & Vassilakopoulou, P. (2025). 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ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing . In Proceedings of the CHI Conference on Human Factors in Computing Systems (pp. 1-18). Subramonyam, H., Pea, R., Pondoc, C., Agrawala, M., & Seifert, C. (2024, May). Bridging the Gulf of Envisioning: Cognitive Challenges in Prompt Based Interactions with LLMs. In Proceedings of the CHI Conference on Human Factors in Computing Systems (pp. 1-19). Fabio, R. A., Plebe, A., & Suriano, R. (2024). AI-based chatbot interactions and critical thinking skills: An exploratory study. Current Psychology, 1-14. Lim, S., Schmälzle, R., & Bente, G. (2024). Artificial Social Influence: Rapport-Building, LLM-Based Embodied Conversational Agents for Health Coaching. CONNECT Workshop: 24th ACM International Conference on Intelligent Virtual Agents. Zhang, Y., & Liu, J. (2024). Falling behind again? Characterizing and assessing older adults' algorithm literacy in interactions with video recommendations. 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Documentation Matters: Human-Centered AI System to Assist Data Science Code Documentation in Computational Notebooks. ACM Transactions on Computer-Human Interaction , 29 (2), 1–33. Umbrello, S., & van de Poel, I. (2021). Mapping value sensitive design onto AI for social good principles. AI and Ethics , 1 (3), 283–296. Zhou, M. X. (2021). Introduction to the Special Column for Human-Centered Artificial Intelligence. ACM Transactions on Interactive Intelligent Systems , 11 (3–4), 1–1. Inkpen, K. (2020). Does My AI Help or Hurt? Exploring Human-AI Complementarity. In Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization (p. 2). Association for Computing Machinery. Macdonald, N., Perks, M., & Reimann, R. (2004). Beyond human centered design? Proceedings of the 5th Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques , 373–374. Margetis, G., Ntoa, S., Antona, M., & Stephanidis, C. (2021). 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Sankaran, S., Zhang, C., Gutierrez Lopez, M., & Väänänen, K. (2020). Respecting Human Autonomy through Human-Centered AI. Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society , 1–3. Schmidt, A. (2020). Interactive Human Centered Artificial Intelligence: A Definition and Research Challenges. Proceedings of the International Conference on Advanced Visual Interfaces , 1–4. Stanford University, United States of America, & Auernhammer, J. (2020, September 10). Human-centered AI: The role of Human-centered Design Research in the development of AI . Design Research Society Conference 2020. Sum, C. M., Alharbi, R., Spektor, F., Bennett, C. L., Harrington, C. N., Spiel, K., & Williams, R. M. (2022). Dreaming Disability Justice in HCI. CHI Conference on Human Factors in Computing Systems Extended Abstracts , 1–5. Wang, D., Churchill, E., Maes, P., Fan, X., Shneiderman, B., Shi, Y., & Wang, Q. (2020). From Human-Human Collaboration to Human-AI Collaboration: Designing AI Systems That Can Work Together with People. Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems , 1–6. Shneiderman, B. (2020a). Human-Centered Artificial Intelligence: Three Fresh Ideas. AIS Transactions on Human-Computer Interactions , 12 (3), 109–124. Shneiderman, B. (2020b). Bridging the Gap Between Ethics and Practice: Guidelines for Reliable, Safe, and Trustworthy Human-centered AI Systems. ACM Transactions on Interactive Intelligent Systems , 10 (4), 1–31. Ramos, G., Suh, J., Ghorashi, S., Meek, C., Banks, R., Amershi, S., Fiebrink, R., Smith-Renner, A., & Bansal, G. (2019). Emerging Perspectives in Human-Centered Machine Learning. Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems , 1–8. Riedl, M. O. (2019). Human-centered artificial intelligence and machine learning. Human Behavior and Emerging Technologies , 1 (1), 33–36. Xu, W. (2019). Toward human-centered AI: A perspective from human-computer interaction. Interactions , 26 (4), 42–46. Benjamins, R., Barbado, A., & Sierra, D. (2019). Responsible AI by Design in Practice d’Aquin, M., Troullinou, P., O’Connor, N. E., Cullen, A., Faller, G., & Holden, L. (2018). Towards an “Ethics by Design” Methodology for AI Research Projects . Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society , 54–59. Zhu, J., Liapis, A., Risi, S., Bidarra, R., & Youngblood, G. M. (2018). Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation. 2018 IEEE Conference on Computational Intelligence and Games (CIG) , 1–8.
Books
Xu, W. (2026). Human-Centered AI: Advancing Research and Applications in Human-AI Interaction Bapna, R., & Ghose, A. (2026). Thrive: Maximizing well-being in the age of AI De Kai. (2025). Raising AI: An essential guide to parenting our future Zerilli, J. (2025). A citizen's guide to artificial intelligence . The MIT Press. Germanakos, P., Juhasz, M., Kongot, A., Marathe, D., & Sacharidis, D. (Eds.). (2025). Human-Centered AI: An Illustrated Scientific Quest . Springer Nature. Shneiderman, B. (2022). Human-Centered AI. Oxford University Press. AI by Design —Google Books. (n.d.) Addo, A., Centhala, S., & Shanmugam, M. (2020). Artificial Intelligence Design and Solution for Risk and Security. Business Expert Press.
Blogs
