User Experience Design for AI, 3 credits

This course is for students and professionals who want to understand the challenges and opportunities that artificial intelligence agents and components bring to the design of experiences. The course covers the conceptual and practical issues of designing with AI as an agent shaping the user’s environment and as a design material: it introduces the basic principles for human-AI interaction and human-AI collaboration; it describes product- and interface-level best practices for AI-enhanced experiences using textual, gestural, voice, and environmental interfaces; it discusses the human-AI relationship in respect to cognitive and algorithmic bias, the building and maintaining of trust, and ways to prevent or fix the potential misalignment between human and software actors.

What will you learn from this course?
At the end of the course, you will have both practical and theoretical understanding of what processes, methods, and techniques should be considered when designing human-centered experiences augmented by artificial intelligence components or agents.
You will be able to identify the role AI plays in an experience, choose the correct approaches, methods, and techniques that will aid you in working towards making the AI part of a solution rather than a problem. Furthermore, you will apply these methods and techniques so that you produce better experiences, and finally, communicate your results and how your approach made a difference.

The course consists of three parts that introduce the structural, agentive, and evaluative aspects of artificial intelligence and their meaning and impact on user experience design. Each part provides a general framing of the specific topic, and discusses what implications the topic has for the design of AI-augmented or AI-supported experiences in terms of identification, use, or modification of appropriate processes, methods, tools and techniques from user experience theory and practice.

1. Information architecture and structural AI (1 credits). Part one deals with the conceptual and structural issues that need to be considered when designing AI-enhanced experiences and with the systemic role of AI as an environment-shaping agent and as a new design material.
2. Interaction design and agentive AI (1 credits). Part two deals with artificial intelligence as an agentive part of the environment. It introduces basic design principles for human-AI interaction and human-AI collaboration, and product- and interface-level issues for AI-enhanced experiences using textual, gestural, voice, and other digiphysical interfaces.
3. Algorithmic experiences and evaluative AI (1 credits). Part three introduces the concept of algorithmic experiences and the evaluative role of AI in large-scale processes where AI provides human actors with information for subsequent action. It discusses issues of cognitive and algorithmic bias, the building and maintaining of trust, and ways to prevent or fix the potential misalignment between human and software actors.

Each part consists of lectures and of an assignment broadly centered on the topic discussed in the part of the course and to be carried out by students individually. Assignments will be peer-reviewed first and then discussed with the teachers and class using a design critique approach.