70 409 Creative Practice with Generative AI (Spring 2026)

Students must have passed foundation level coures (BA-level) at AHO or equivalent, 180 ECTS.

No prior experience with AI is required.

This course offers a practice-based exploration of artificial intelligence in design, architecture, and related creative fields. Through intensive hands-on experimentation with state-of-the-art generative tools and creative research, students engage deeply with AI’s fundamental contradictions—its remarkable capacity for expression and innovation alongside its complex entanglements with surveillance, cultural disruption, labor automation, and ecological harm. This dual perspective encourages students to consider not only what they create with these systems, but also what these systems, in turn, create in and with them.

The course’s ultimate goal is to cultivate an authentic creative practice, empowering students to thoughtfully decide when, how, and why to embrace or resist generative AI based on their individual needs, values, contexts, and creative intentions. It also supports learners in adapting their creative approaches as these factors evolve over time.

Students will acquire skills to integrate AI tools and workflows into their preferred media and creative practices, effectively bridging digital and physical processes as well as online and offline presences. Through this, they develop flexible and adaptive approaches to making and knowing that respond to the rapid technological and cultural changes shaping contemporary creative work.

Knowledge:

• Understand the fundamental principles of generative AI tools and methods for integrating them into design, architecture and other creative practices.
• Be familiar with how AI systems shape and are shaped by significant cultural, social, and political issues across local and global contexts with attention to their historical development, experimental approaches, and current debates surrounding authorship and creative agency.

Skills:

• Experiment with state-of-the-art generative AI tools and workflows, integrating them into physical and digital making practices across diverse creative media.
• Develop critical methodologies for investigating AI's role in creative practice, including iterative testing, reflection, and aesthetic judgment of AI-generated outputs.
• Evaluate and adapt creative strategies in response to evolving technological and cultural landscapes, communicating processes and outcomes effectively for interdisciplinary collaboration.

General Competence:

• Develop proficiency across diverse AI tools and platforms, adapting technical workflows and creative methods as new technologies emerge, while maintaining reflective and responsible practice.
• Exercise independent judgment in deciding when, how, and why to adopt or resist AI tools within personal and professional creative contexts, demonstrating reflective and responsible practice.
• Navigate ethical and political dimensions of AI use, including authorship, labor, data, and environmental impact, while collaborating effectively in interdisciplinary settings with awareness of broader societal effects.

The course offers a practice-based, experiential-learning workshop sequence that combines lectures with hands-on AI tool labs, “common prompting” sessions, and guided experiments. Students work individually and in small teams through iterative exercises, with weekly pin-ups/critique and reading-driven micro-seminars to situate practice. AI-Tool clinics and guest sessions support technical depth; ethics and environmental check-ins frame responsible use. Continuous documentation (process logs, code/notebooks, and prototypes) feeds into a cumulative portfolio and a public exhibition-oriented final.

Mandatory activities

In order to be assessed in this course, you must have the following mandatory activities approved:

• Participation: Attendance and active participation in at least 80% of workshops, common prompting sessions, and group critiques.
  
• Assignments: Completion of three short experimental exercises that document hands-on engagement with generative AI tools and methods.
  

Students who do not meet the attendance requirement or fail to complete a mandatory exercise must submit an additional written reflection (approximately 1000 words) demonstrating equivalent learning outcomes and critical engagement with the missed content.

These activities are designed to ensure students acquire the necessary practical and reflective competencies to achieve the course’s intended learning outcomes.

Assessment method

Form of assessment: Portfolio assessment

Grouping: Individual

Grading scale: Pass/fail

The portfolio consists of:

• Part 1: Final Project and Exhibition — a resolved creative work or research-based design experiment that synthesizes technical, conceptual, and critical dimensions of the course.
  
• Part 2: Reflection Note and Final Presentation — a short written or recorded reflection articulating the student’s process, contextual framing, and critical position regarding the role of AI in their creative practice + presentation.
  

All parts must be assessed as passed in order to pass the course.
Assessment emphasizes experimentation, conceptual depth, critical reflection, and the integration of theory and practice.