Human-AI Interaction, 7.5 Credits

Contents

The course is divided into a theoretical part (4.5 ECTS) and a practical part (3 ECTS). The theoretical part covers theoretical frameworks and methods for developing and evaluating intelligent interactive systems and provides introduction into how using these in practice. Parts of the content in the theoretical part are applied in the practical part, which is conducted in parallel, and that consists of a group project.

The main theme of the course is theories, methods and technologies for the development of future intelligent interactive systems where humans and proactive, reactive, autonomous and social software agents communicate and cooperate to reach goals. Sometimes the software agents are embedded in robotic systems or in other artefacts/materials in the physical environment. The student will acquire knowledge about main research themes and experimental practices in the field of intelligent interactive systems as well as develop her/his skills in constructing and evaluating intelligent interactive systems. Different artificial intelligence methods and theories are introduced for developing intelligent interactive systems, e.g., knowledge graphs, OWL ontologies, SWRL, human activity recognition and human-aware planning. Paradigms such as mixed reality and virtual reality are also discussed as part of the modalities of interaction with between humans and intelligent systems.

Different societal challenges will be addressed through cross-disciplinary collaboration in student projects. In the laboratory part of the course theories, methods and techniques discussed in the theoretical part are put into practice. From a societal perspective, the aim may be designing for empowerment, increasing autonomy, safety, competence, cohesion, social inclusion, relatedness, motivation and behaviour change in people; from a technology perspective the aim may be designing the interactivity by integrating self-learning, self-adaptation, sensor networks, semi-autonomous multi-agent systems, intelligent user interfaces, etc. that are instrumental for reaching the societal aims and meeting the individual's preferences and needs.

Expected learning outcomes

Knowledge and understanding
After completing the course, the student should be able to: 

• (FSR 1) explain and characterize different artificial intelligence paradigms relevant for designing and constructing interactive intelligent systems,
• (FSR 2) account for the central issues/topics that need to be taken into consideration in the design of interactive intelligent systems from the perspective that the system will be proactive, reactive, social and (semi-)autonomous,
• (FSR 3) account for which main types of interactive intelligent systems that are in use today and analyse the technical strengths and limitations for different types of applications/purposes,
• (FSR 4) explain the basics of architectures that are specific for interactive intelligent systems, and exemplify different techniques that can be used for realising interactive intelligent systems,
• (FSR 5) account for and apply concepts, methods and theories for proactive, reactive, autonomous and social agents.

Competence and skills
After completing the course, the student should be able to:

• (FSR 6) demonstrate practical skills in communicating and integrating multiple perspectives (e.g. ethical, security, safety, personal, societal)  in the design of interactive intelligent environments/systems in a multi-professional work process,
• (FSR 7) demonstrate practical skills in developing interactive intelligent environments/systems,
• (FSR 8) demonstrate practical skills in designing and evaluating proactive, reactive, autonomous and social agents/agent societies.

Judgement and approach
After completing the course, the student should be able to:

• (FSR 9) evaluate different interactive intelligent systems from different perspectives (ethical, security, safety, personal, societal),
• (FSR 10) evaluate the quality in different design proposals based on the purpose and the need for interactive intelligent systems,

Required Knowledge

At least 90 ECTS, including 60 ECTS Computing Science, or 120 ECTS within a study programme. At least 15 ECTS programming; 7.5 ECTS human-computer interaction; and 7.5 ECTS artificial intelligence. Proficiency in English equivalent to the level required for basic eligibility for higher studies.

Form of instruction

The course consists of lectures, project work in computer labs and other environments, and exercises in small groups. In addition to scheduled activities the course also requires individual work with the material.

Examination modes

Examination of the theoretical part (FSR 1-5, 9-10) is done through a written examination in halls. The grade on this part is one of the grades Fail (U), Pass (G), or Pass with Distinction (VG).

The examination of the practical part (FSR 6-10) is done through completing a project in group according to instructions provided during the course. Parts of the project work may be done through field studies outside the university in collaboration with societal organisations, and meetings during the project can be located at such organisation. The grade on the practical part is one of the grades Fail (U) or Pass (G).

On the whole course one of the grades Fail (U), Pass (G), or Pass with Distinction (VG) is given. The grade on the course as a whole is determined by the grade on the theoretical part.

Adapted examination
The examiner can decide to deviate from the specified forms of examination. Individual adaptation of the examination shall be considered based on the needs of the student. The examination is adapted within the constraints of the expected learning outcomes. A student that needs adapted examination shall no later than 10 days before the examination request adaptation from the Department of Computing Science. The examiner makes a decision of adapted examination and the student is notified.

Other regulations

In an exam This course may not be included, in whole or in part, simultaneously with another course of similar content. If in doubt, consult the student counselors at the Department of Computer Science and / or program director of the study program.

In particular, this course can not, in whole or in part, be used in a degree together with 5DV174 / 5DV185 Interactivity in smart environments.

If the syllabus has expired or the course has been discontinued, a student who at some point registered for the course is guaranteed at least three examinations (including the regular examination) according to this syllabus for a maximum period of two years from the syllabus expiring or the course being discontinued.