AI for good? The Global Governance and Politics of Technology
Postgraduate course
- ECTS credits
- 5
- Teaching semesters
- Spring
- Course code
- GOV360-5
- Number of semesters
- 1
- Teaching language
- English
- Resources
- Schedule
- Reading list
Course description
Objectives and Content
The public debate on artificial intelligence (AI) technologies is marked by a strange co-existence of hype and doomsday scenarios. Some hope that smart tools could identify cancer earlier, cut energy and waste levels in production processes, and make harvests more effective, thereby saving the lives of millions and solving climate change at once. At the same time, many fear that generative AI à la Chat-GPT could automate advanced cognitive tasks, killing jobs for university graduates, all while autonomous lethal weapons, smart grids, or highly automated financial transactions might get out of control and put human societies at risk of extinction. The accompanying call for regulating AI technologies raises several complex questions for political scientists: (1) What are the key tenants in discussions about AI regulation and governance? (2) What roles do different actors - states, corporations, international organisations, interest groups and social movements - play in carving out a global framework for governing AI tech? (3) Which voices and stakes are marginalized in global AI governance and to what effect for a vision of "AI for good"?
This elective course tackles these questions through deep reading and discussion of selected articles and Handbook chapters. These provide an overview of the state-of-the-art in respective subfields of tech governance and politics research, introduce key concepts, research foci and policy debates, and develop critical analytical approaches for future research and the global governance of AI technologies. In class, we approach the readings in a dialogue-oriented seminar structure, based on students' regular preparation of readings, one short research brief, and with rotating responsibility for co-planning and moderating the seminar session. Willingness to prepare the session readings in-depth is essential for successful participation in this course.
Learning Outcomes
A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge
The student knows
- major debates on AI technology development and use as a global challenge
- key lines of contestation about how to analyse the governance and politics of AI technology
- key empirical insights on the variable governance and politics of AI technology globally.
Skills
The student can
- evaluate, synthesize, and critically appraise existing social science research on the governance and politics of AI technology
- develop and apply their own conceptual-analytical approach to the politics and governance of AI technology as a global challenge
- identify and analyse relevant empirical cases of AI technology governance independently and in a nuanced manner.
General competence
The student can
- identify and present complex phenomena in the field of global technology governance in a nuanced and critical manner
- develop, present, discuss and defend own arguments about scholarly readings and empirical phenomena in dialogue with peers
- structure and moderate group discussions in an inclusive manner.
ECTS Credits
Level of Study
Semester of Instruction
Required Previous Knowledge
Recommended Previous Knowledge
Credit Reduction due to Course Overlap
Access to the Course
The course is open to students enrolled in master's programmes at the Department of Government.
Exchange students at master's level and students from other master's programmes at the University of Bergen with relevant backgrounds may be admitted upon application, subject to approval by the administration of the Department of Government.
Applications may be rejected due to capacity. The course gives priority to students accepted to the master's programmes at the Department of Government.
The maximum number of students is 15.
Teaching and learning methods
Compulsory Assignments and Attendance
The compulsory assignment includes:
- Submission of a set of three questions on four out of the six reading bloc.
- One research brief (2-3 pages each) delivered before the respective session based on the assigned readings and some guiding questions to be shared by the teacher.
- Each student must take co-leadership for planning/chairing part of one seminar discussion.
- Attendance of at least five sessions is compulsory
The compulsory assignment must be approved in order to take the exam. Approved compulsory assignments are valid in the current and following two semesters.
Forms of Assessment
Research essay of 2500 words (+/- 10%, excluding the title page, table of contents, references, tables, and all attachments). The teacher will share guiding questions for the task in due course.
The exam will be given in the language in which the course is taught.
The exam answer can be submitted in English.
Grading Scale
Assessment Semester
Assessment in teaching semester.
A retake exam is arranged for students with valid absence according to § 5-5 in the UiB regulations.
If there is a retake exam, this will be available for students with the follow results/absences:
- Medical certificate/valid absence
- Interruption during the exam
- Fail/failed
If you have the right to take a retake exam and a retake exam is arranged for students with valid absences, you can sign up yourself in Studentweb after 1. August.