Scope

Artificial intelligence has become deeply embedded in our daily lives, transforming how we work, learn, manage our health, and interact, enjoy entertainment, and engage with public services. As AI systems grow more sophisticated and pervasive, the quality of human-AI interaction emerges as the critical factor determining whether these technologies truly benefit users and society.

HAXD 2025 focuses on the design and experience of human-AI interaction—examining not just what AI can do, but how people actually interact with these systems and what experiences result from these interactions. We are interested in understanding and improving the full spectrum of user outcomes: usefulness, usability, trust, cognitive workload, user satisfaction, safety, fairness, accessibility, and long-term societal impact.

The symposium welcomes research and design work spanning diverse AI technologies—including foundation models, conversational agents, recommendation systems, computer vision and speech interfaces, interactive machine learning systems, and emerging AI paradigms. We welcome submissions that consider the full diversity of users, from researchers to practitioners, multilingual communities, cross-cultural populations, and people with disabilities. Similarly, we embrace work across all environments where human-AI interaction occurs: homes, workplaces, educational settings, healthcare contexts, civic technologies, creative tools, social platforms, and emerging application domains.

We welcome submissions concerning how humans and AI systems communicate, collaborate, and co-create value together. Whether you are designing new interaction paradigms, evaluating existing AI experiences, developing methodologies for AI usability research, or exploring the societal implications of AI interaction design, we want to hear from your work.

HAXD 2025 aims to build a community of researchers, designers, and practitioners committed to ensuring that as AI becomes more powerful, it also becomes more human-centered, inclusive, and genuinely beneficial to the diverse communities it serves.

Research Topics

🎯

Human-AI Interaction Design

  • Conversational interfaces and dialogue design for AI systems
  • Multimodal interaction paradigms (voice, gesture, text, visual)
  • Adaptive and personalized AI interfaces
  • Trust and transparency in AI system design
  • User agency and control in automated systems
  • Explainable AI interfaces and visualization
  • Error handling and failure recovery in AI interactions

User Experience for AI Systems

  • UX methodologies for AI-enabled products and services
  • User journey mapping for AI-assisted workflows
  • Onboarding and mental model formation for AI systems
  • User feedback and AI system improvement
  • Accessibility and inclusive design for AI interfaces
  • Cross-cultural design considerations for global AI systems
  • Emotional design and affective computing in AI interfaces
🤝

Collaborative AI and Agentic Systems

  • Human-AI collaboration frameworks and design patterns
  • Agentic AI workflow design and user experience
  • Co-creation and co-design with AI systems
  • AI assistants and virtual agents interaction design
  • Human-in-the-loop AI system design
  • Delegation and supervision in AI-assisted tasks
  • Team dynamics in human-AI collaborative environments
🛡️

Evaluation and Methodology

  • Usability testing methods for AI systems
  • User research techniques for AI interaction design
  • Metrics and evaluation frameworks for human-AI experiences
  • Longitudinal studies of AI system adoption and use
  • Comparative analysis of AI interaction paradigms
  • Design thinking and participatory design for AI systems
  • Prototyping tools and techniques for AI interfaces
🛡️

Ethics and Responsible AI Design

  • Privacy and data protection in AI user interfaces
  • Bias mitigation through inclusive design practices
  • Algorithmic transparency and user understanding
  • Consent and user control in AI data collection
  • Ethical considerations in persuasive AI design
  • Fairness and equity in AI system access and use
  • Social implications of AI interaction design decisions
🛡️

Domain Applications

  • Healthcare AI interfaces and patient experience
  • Educational AI systems and learning experience design
  • Workplace AI tools and productivity interfaces
  • Creative AI systems and artistic collaboration
  • Autonomous systems and human oversight interfaces
  • Smart home and IoT AI interaction design
  • Financial AI services and user trust
🛡️

Emerging Technologies and Future Directions

  • Virtual and augmented reality AI interfaces
  • Brain-computer interfaces for AI interaction
  • Embodied AI and robotics interaction design
  • Large language model interface design
  • Generative AI user experience and creative workflows
  • AI-powered personalization and recommendation systems
  • Future interaction paradigms and speculative design