Human-centered Artificial Intelligence, 7.5 credits
Människocentrerad artificiell intelligens, 7,5 hp
Course code: IK4052
School of Information Technology
Level: First cycle
Select course syllabus
Finalized by: Forsknings- och utbildningsnämnden, 2024-09-18 and is valid for students admitted for spring semester 2025.
Main field of study with advanced study
Informatics, First cycle, has less than 60 credits in first-cycle course/s as entry requirements. (G1F)Entry requirements
The courses Digital Design and Innovation 15 credits, Interaction Design 7.5 credits. Exemption of the requirement in Swedish is granted. English 6.
Placement in the Academic System
The course is included in Digital Design and Innovation 180 credits. The course is also given as a single subject course.
Objectives
The course introduces artificial intelligence from a design-oriented perspective on digital interactive services. The goal of the course is that the student should be able to describe and apply basic theory in AI and adaptive services in human-centered design, and in evaluation of AI-powered services. Furthermore, the student will develop his/her ability to apply methods, techniques and tools to design digital services from an AI perspective. Another goal of the course is that the student should be able to evaluate and reflect upon AI-based technology and apply an agentive perspective on the design of digital services.
Following successful completion of the course the student should be able to:
Knowledge and understanding
- describe basic terminology in the field of artificial intelligence
- identify and describe different areas of application for agentive services from an interaction perspective
- describe basic concepts relevant for adaptive services
Skills and ability
- apply methods and techniques for designing AI-powered services
- apply basic methods for evaluating adaptive services
Judgement and approach
- evaluate and critically reflect upon design and usage of AI-powered services
- evaluate and argue for and against design decisions when designing AI-powered services
Content
The course is divided into three thematic areas: (a) artificial intelligence, in particular machine learning, (b) design of AI-powered services, and (c) evaluation of adaptive services. The areas are approached theoretically, as well as from a practical perspective in workshops and laborative work. Throughout the course, the students produce and evaluate concepts for various types of AI-powered services.
Language of Instruction
Teaching Formats
Teaching consists of lectures, design workshops and laborative sessions. This course may be given in English.
Grading scale
Examination formats
The course is examined by an individual written take-home examination (4 credits) and a series of laboratory sessions for concept design and evalutation (3.5 credits).
2102: Laboratory Series, 3.5 credits
Two-grade scale (UG): Fail (U), Pass (G)
2101: Take-home Examination, 4 credits
Three-grade scale (UV): Fail (U), Pass (G), Pass with distinction (VG)
Exceptions from the specified examination format
If there are special reasons, the examiner may make exceptions from the specified examination format and allow a student to be examined in another way. Special reasons can e.g. be study support for students with disabilities.
Course evaluation
Course evaluation is part of the course. This evaluation offers guidance in the future development and planning of the course. Course evaluation is documented and made available to the students.
Course literature and other materials
Literature list 2025-01-20 – Until further notice
Amershi, Saleema et al. Guidelines for Human-AI Interaction. In Proceedings of CHI 2019 (2019).
Johnson, Matthew., & Vera, Alonso. (2019). No AI is an island: the case for teaming intelligence. AI magazine, 40 (1) p. 16-28.
Konstan, Joseph A & Reidl, John. Recommender systems: from algorithms to user experience. User Model User-Adap Inter (2012) 22:101–123.
Wärnestål, Pontus. Design av AI-drivna tjänster. Lund: Studentlitteratur, 2021.
Yang, Qian et al. Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design. In Proceedings of CHI 2020 (2020).
Scientific articles from the university library.
Reference literature
Noessel, Cristopher. Designing Agentive Technology. Rosenfeld Media, 2017.
