Human-AI Interaction

Upon completion of the course, the student will be able to:
• explain key concepts, theories, and socio-technical perspectives related to Human–AI Interaction;
• critically analyse ethical, societal, and usability challenges of AI-enabled systems, including fairness, transparency, explainability, human values, and AI-related harms;
• apply human-centred and value-sensitive design approaches to the analysis and development of AI systems;
• identify and frame research problems related to Human–AI Interaction;
• design and communicate research-informed conceptual interventions, low-fidelity prototypes, or analytical frameworks for existing AI systems;
• evaluate AI interaction concepts using appropriate research and design methods;
• discuss the implications of Human–AI Interaction research for responsible AI development and practice.

Assistant professor Afsaneh Razi, Department of Information Science, Drexel University
Postdoctoral researcher Heidi Hartikainen, Interact research unit, Faculty of ITEE, Oulu University

Learning materials consist primarily of scientific articles and book chapters related to Human–AI Interaction, human-centered AI, AI ethics, and conversational systems.

Key readings include works by:

• Markoff;
• Crawford and Joler;
• Amershi et al.;
• Yang et al.;
• Keyes et al.;
• Capel and Brereton;
• Namvarpour and Razi.

Additional materials may be provided through Moodle.

To complete the course, students are required to:
• Select 2-3 articles from the reading list and write a short reflection
• actively participate in lectures, discussions, workshops, and group activities during the course;
• complete a project related to an existing AI-enabled system and submit a short project report;
• present and discuss project work during the course
Full participation during the workshop is required.

The course is implemented as a three-day doctoral course consisting primarily of face-to-face teaching, supported by digital learning environments for delivering pre-reading materials and returning course submissions.
Teaching methods include:
• lectures;
• guided discussions;
• group activities;
• project-based learning;
• independent research and writing;
• peer feedback and presentations.
The course uses Moodle as the primary learning environment.
The course includes approximately 20 hours of contact teaching and 55–60 hours of independent work, resulting in a total workload of approximately 80 hours (3 ECTS).
Limited remote participation in lecture sessions may be enabled if necessary.

Assessment is based on: completing reflective essay based on pre-readings and active participation and contribution during the course

The course is intended for doctoral researchers interested in Human–AI Interaction, human-centered AI, digital ethics, AI-supported systems, and socio-technical aspects of artificial intelligence.
The course is particularly relevant for doctoral researchers in information technology, human sciences, design, education, health, and interdisciplinary AI-related research.
Doctoral researchers from all doctoral programmes at the University of Oulu may participate if space permits.

The course emphasizes interdisciplinary discussion and research-oriented learning. Students are encouraged to connect course themes to their own doctoral research.