Designing Human-Centred AI Systems

In today's world, interactive AI-infused systems like movie and music recommendation systems, as well as health or financial digital advice systems, provide algorithmic support to individuals in achieving their short- and long-term goals. Ideally, these systems aim to align with people's values, motivations, habits, and social context, offering augmentation of capabilities by providing algorithmic solutions to tasks that may be mentally demanding or require expertise beyond the individual's reach.

As automation levels rise, ensuring meaningful control, trustworthiness, and understandability of these systems becomes crucial for user acceptance. In this course, students learn to design and evaluate these systems from a human-centred AI perspective.

The course incorporates psychological theories and concepts that inform algorithmic solutions to nudge individuals towards making good decisions or enhancing their ability to modify their behaviour without coercion or deception. By understanding human behaviour and cognitive processes, students will learn how to design AI systems that support users in a beneficial, transparent, and respectful way of their autonomy.

The course's main topics:

• Human motivation, values, cognition, behaviour, learning, change, decision-making, and persuasion

• HCAI design methods

• Technology acceptance of interactive AI-infused systems

• Design guidelines for Human-AI interaction

• Algorithmic nudges and boosts

The final grade of the course consists of the following components:

• Group Presentation: presentation of the design and evaluation of interactive AI-infused system including demonstration of computer simulation of algorithmic nudge, boost or persuasion for this system (weighting 30%)

• Individual Presentation: individual QenA session about design, evaluation of interactive AI-infused system and algorithmic nudge or boost for this system (weighting 20%)

• Digital Exam (weighting 50%)

Final grade calculation = 0.3 * Digital Presentation + 0.2 * Individual Presentation + 0.5 * Digital Exam

A passing final grade for the course can only be earned when for all components at least a 5.0 is earned, and the weighted final grade is at least a 5.8.

In case of an insufficient final result, repair options may exist in accordance with Article 17A, Times and number of examinations, sub 1, of the Teaching and Examination Regulations, for:

• Group Presentation: Repair opportunity

• Individual Presentation: Repair opportunity

• Digital Exam: Repair opportunity

Disclaimers:
1. Information may change depending on unforeseen circumstances or measures (see: TER Art 2, sub 5).
2. Note that if the expected number of students registering for the exam or resit is rather small, the teachers might decide to replace the digital examination with an oral examination with due notice.