PSYb2886 Artificial Intelligence in Psychology

Faculty of Social Studies
Spring 2026
Extent and Intensity
0/2/0. 4 credit(s). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
Mgr. Adéla Švestková (lecturer)
Mgr. Tomáš Vojtíšek (lecturer)
Mgr. Tomáš Kratochvíl, Ph.D. (lecturer)
Mgr. Štěpán Kaňa (lecturer)
Guaranteed by
Mgr. Adéla Švestková
Department of Psychology – Faculty of Social Studies
Contact Person: Mgr. Adéla Švestková
Supplier department: Department of Psychology – Faculty of Social Studies
Prerequisites
! PSYb1020 Personality Psychology
The course is recommended for students who have completed their first year of study, as it loosely builds on compulsory courses (e.g., social psychology, methodological and statistical courses). However, first-year students are welcome to take the course.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives

The aim of the course is to understand artificial intelligence (AI) as a tool, subject, and partner in psychology and psychological research. During the course, we will look at AI from four perspectives that are relevant to psychologists: AI as a new technology (media psychology perspective), AI as a tool for research in the social sciences (methodology, philosophy, and ethics of science perspective), AI as a participant in relationships (social psychology perspective), and AI in psychological practice.

Learning outcomes

Upon completion of the course, students will:

  • be able to describe the basic principles of artificial intelligence, the risks involved, and what its adoption entails
  • know how AI can enrich research in the social sciences and where its use has its limits, and be familiar with the rules for the appropriate use of AI at MUNI
  • be able to effectively use AI in various stages of their own academic work (from literature research to stimulus material to data analysis)
  • have an idea of the different types of parasocial relationships with chatbots in the context of other relationships
  • know how people use AI in the context of physical and mental health, including the risks, and how AI enriches psychological and psychotherapeutic practice

Syllabus

Week 1: Introduction to the course. How AI and LLM work (lecture).

Week 2: AI as a new technology. The perspective of technology acceptance models, risks associated with artificial intelligence (lecture).

Week 3: AI as a tool for research in the social sciences (lecture).

Week 4: AI as a research aid I: Effective prompting (lab session).

Week 5: AI as a research aid II: Idea generation (stimulus material, concept development)

Week 6: AI as a research aid III: Literature review and data analysis. Creation and critique of analytical procedures using LLM. ASReview for fast but thorough literature review (lab session).

Week 7: Reading week.

Week 8: AI as a research object: Discussion of studies (seminar).

Week 9: AI and social relationships (lecture).

Week 10: AI as a support (not only) for mental health (lecture)

Week 11: AI in psychotherapeutic practice, DeePsy (lecture) 

Week 12: Course summary, colloquium

Literature
    required literature
  • Radford, J., & Joseph, K. (2020). Theory in, theory out: The uses of social theory in machine learning for social science. Frontiers in Big Data, 3, 18. https://doi.org/10.3389/fdata.2020.00018
  • Xu, R., Sun, Y., Ren, M., Guo, S., Pan, R., Lin, H., Sun, L., & Han, X. (2024). AI for social science and social science of AI: A survey. Information Processing & Management, 61(3), 103665. https://doi.org/10.1016/j.ipm.2024.103665
Teaching methods
Lectures incorporating interactive teaching methods, seminars designed as discussions on literature or as "lab sessions," i.e., space for practicing practical skills. Theoretical preparation for seminars in the form of reflection on required literature or simple preparation of materials.
Assessment methods
The colloquium is awarded based on attendance, submission of all seminar assignments, and completion of a final assignment, which will be presented at the final meeting.
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught every week.
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