W2: HCI Design in an AI-empowered World

Aim of the Workshop

The rapid advances and widespread deployment of generative artificial intelligence have profoundly transformed the landscape of Human–Computer Interaction (HCI) design—reshaping both what is being designed and how design is conducted. AI technologies dramatically expand and redefine both the problem space and the solution space of HCI, creating unprecedented opportunities while also introducing new conceptual, methodological, and ethical challenges.

Whereas understanding users, tasks, and contexts remains central to determining “what problem needs to be solved,” each of these constructs is evolving. The notion of “users” now extends beyond end users to include actors critical to the development, deployment, and governance of AI systems. “Tasks” performed by users are being reshaped as AI systems alter workflows, redistribute cognitive responsibilities, and enable new forms of human-AI collaboration. Meanwhile, the dynamic, data-dependent operation contexts of AI-empowered systems lead to issues such as inconsistent system behaviors, emergent failure modes such as hallucinations, and broader socio-technical impacts that unfold over time. The interaction mode is shifted towards mixed-initiative interaction, where initiative and control are dynamically shared and negotiated between users and systems. "Good design" for such systems requires not only considerations for usability and user experience, but also attention to ensure transparency, calibrate trust, preserve human agency and meaningful control, and proper evaluation needs to move beyond immediate interaction outcomes to consider long-term effects at individual, organizational, and societal levels.

For HCI designers, this wave of generative AI changes the materials, tools, and roles of design. Beyond traditional interface elements, they also need to familiarize themselves with algorithms, models, and data--as well as their capabilities, uncertainties, and limitations--that determine the behavior of AI-empowered systems in runtime. Designers must understand how these computational substrates shape system capabilities and affect user interactions. With the development and integration of AI-augmented tools for user research, ideation, and prototyping, the design processes and workflows need to be reconfigured. These changes raise important questions about how HCI designers collaborate with AI, how their expertise evolves, and how their roles within interdisciplinary teams should be defined and clarified.

To support the HCI design of AI-empowered systems in a systematic and responsible manner, this workshop brings together researchers, designers, and practitioners to explore emerging approaches for creating human-centered experiences in an era where AI plays an increasingly active, adaptive, and collaborative role. The aims are to identify foundational challenges, synthesize emerging knowledge and practices, and chart a shared roadmap for future HCI research and practice. Key issues motivating this workshop include, among others:

• articulate emerging design challenges introduced by adaptive, generative, and mixed-initiative AI
• share and discuss methodological innovations for involving end users and stakeholders throughout the design lifecycle
• explore strategies for conceptualizing, prototyping, and evaluating adaptive AI behaviors
• identify and compare new design patterns, approaches, and skill sets for future HCI practice
• build community consensus toward best practices and standards

Workshop agenda

Workshop event: 8:30 am – 12:30 pm, Tuesday, 28 July 2026

The following is a framework for the program of the Workshop:

Workshop deadlines

Useful links and References

• Stephanidis, C., Salvendy, G., Antona, M., Duffy, V. G., Gao, Q., Karwowski, W., ... & Zhou, J. (2025). Seven HCI grand challenges revisited: Five-year progress. International Journal of Human–Computer Interaction, 1-49. https://doi.org/10.1080/10447318.2025.2450411
• Shi, J., Jain, R., Doh, H., Suzuki, R., & Ramani, K. (2023). An HCI-centric survey and taxonomy of human-generative-AI interactions. arXiv preprint arXiv:2310.07127. https://doi.org/10.48550/arXiv.2310.07127
• Garibay, O. O., Winslow, B., Andolina, S., Antona, M., Bodenschatz, A., Coursaris, C., Falco, G., Fiore, S. M., Garibay, I., Grieman, K., Havens, J. C., Jirotka, M., Kacorri, H., Karwowski, W., Kider, J., Konstan, J., Koon, S., Lopez-Gonzalez, M., Maifeld-Carucci, I., … Xu, W. (2023). Six human-centered artificial intelligence grand challenges. International Journal of Human–Computer Interaction, 39(3), 391–437. https://doi.org/10.1080/10447318.2022.2153320
• Shneiderman, B. (2022). Human-centered AI. Oxford University Press.
• Shneiderman, B. (2020). Human-centered artificial intelligence: Reliable, safe & trustworthy. International Journal of Human–Computer Interaction, 36(6), 495-504. https://doi.org/10.1080/10447318.2020.1741118
• Yang, Q., Steinfeld, A., Rosé, C., & Zimmerman, J. (2020). Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–13. https://doi.org/10.1145/3313831.3376301