AI507: Artificial Intelligence and Society
Entry requirements
None. But the course is oriented towards students of the B.A. in Artificial Intelligence in the fourth semester.
Academic preconditions
Academic preconditions. Students taking the course are expected to have knowledge aquired in AI501 (Introduction into artificial intelligence) and AI502 (Ethic and privacy).
Course introduction
The purpose of the course is to provide knowledge for understanding the social consequences of the use of artificial intelligence and to learn how to take them into consideration in the development of intelligent systems. The course builds upon knowledge aquired in AI501 and AI 502 and provides an academic basis for studying the topics in AI510 (Cybersecurity and innovation), which is placed later in the program.
Expected learning outcome
The course provides students with a theoretical and methodological foundation informed by the social sciences, equipping them to assess both the opportunities and risks associated with the use of AI. Students can take this knowledge into consideration in the development of artificially intelligent systems.
Knowledge: The lecture element of the course will provide students with basic knowledge about central social scientific theories and models (predominantly from psychology and communication) to evaluate the opportunities and risks of the use of AI in different areas including automation, the internet of things, the media, social media and virtual games. The research seminar element of the course will provide students with initial insights into the methodological foundations of the social sciences.
Skills: The course will enable students to master various instrumental techniques: These include (a) critically evaluating scientific evidence about AI and society; and (b) working collaboratively in small research groups to (c) employ AI to answer a currently open research question related to AI in social contexts and (d) presenting their insights following rigorous scientific principles. This hands-on approach ensures that students not only understand theoretical concepts but can also apply them in practical scenarios.
Competences: By the end of the course, students will be capable of forming an empirically grounded opinion about the consequences of AI for individuals, social groups, and society at large. Through the gained knowledge and the obtained skills, they will be able to evaluate social scientific evidence related to AI and integrate their insights into the development of intelligent systems and communicate them to others.
Content
The course has two central elements: A lecture “Introduction into social scientific perspectives on AI” and a research seminar: “Applications of AI in society”. The lecture will introduce students to key theoretical and empirical contributions from the social sciences (particularly psychology and communication) relevant to the creation, implementation, and effects of AI in different areas such as automation, the internet of things, the media, social media and virtual games.
The research seminar will introduce students to methodological principles of the social sciences before they work together in small groups to answer an open research question regarding AI and society and present their results following rigorous scientific principles. The question will be agreed upon with the teacher, allowing the class to adapt to current innovations and development in AI and society.
Literature
Examination regulations
Exam element a)
Timing
Tests
Portfolio exam
EKA
Assessment
Grading
Identification
Language
Duration
Examination aids
The exam is with limited aids. Only the following aids are allowed:
- language translation dictionaries (e.g. Danish/English, Danish/German etc) in "ordbogsprogrammet" (the dictionary programme) from http://www.ordbogen.com/ in electronic form. The browser version is not allowed. See the complete list of which dictionaries are allowed in the separate "Instruction to ordbogen dot com". All dictionaries other than the allowed dictionaries must be switched off in “ordbogsprogrammet” (the dictionary programme).
Internet is not allowed. However, you may access the course page in itslearning to open system "DE–Digital Exam" and complete any tests within the system.
ECTS value
Additional information
1. Short group presentations in the research seminar
2. Joint research report about the small group work in the research seminar
1. An indicidual presentation
Indicative number of lessons
Teaching Method
At the faculty of science, teaching is organized after the three-phase model, i.e., introduction, training and study phase. This course realizes these phases through two central elements: A lecture “Introduction into social scientific perspectives on AI” and a research seminar: “Applications of AI in society”.
The lecture will provide a comprehensive introduction about social scientific theories and evidence related to the creation, implementation, and effects of AI in society. Input by the teacher will be complemented by guest speakers and activating methods (e.g. discussions, quizzes). This phase aims to furnish students with the necessary knowledge and a social-scientifically grounded reference framework to comprehend the interplay between AI and individuals, groups, and society. Furthermore, students will practice their skills in critically evaluating evidence provided by the social sciences. Therewith, the lecture will enhance students' personal competencies to form evidence-based opinions about the consequences of AI for individuals, social groups, and society at large.
The research seminar will introduce students to social scientific research methods, providing them with introductory knowledge about the genesis of social scientific evidence. In the training phase, students will be assigned to small groups and collaboratively work on a research project in which they apply AI to answer a currently open research question related to implementation or effects of AI on individuals, social groups, or society. Students will present their research ideas, empirical approaches and the results of their small groups’ work and will write a joint research report about their group project. This will practice their collaborative skills as well as their skills related to the application of AI and the rigorous communication of their own empirical insights.
Together, the lecture and the research seminar will enhance students' personal competences, enabling them to form evidence-based opinions about the consequences of AI for individuals, social groups, and society at large and to integrate their insights into the development of intelligent systems.
Duration of the single elements:
- Lecture: 28 hours
- Research Seminar: 42 hours of which 12 hours are lectures and activating methods by the teacher (introductory phase), 15 are feedback sessions to concrete steps in the research project (training phase), and 15 are lab sessions during with the research is conducted (study phase)