Artificial Intelligence for an Open Society

Course goals

Motivation
Artificial intelligence (AI) models, technology, and methods are heavily influencing society.  This goes both through informal and formal institutions. For example, for informal institutions, algorithms estimate what people ‘like’ and dynamically adapt what posts they see on social media and even news websites. This can create ‘filter bubbles’ and a societal divide. On the formal side, models are one of the instruments to inform institutional and governmental policy and to create behavior change. For example, cognitive models of human attention can inform policy on how frequently to display speed information above the Dutch Highways, and agent-based models of social interaction can help understand how quickly diseases spread through a network and how this can be slowed down. In essence, AI models impact society at various levels.
To shape tomorrow’s society, students need to understand how the different types of models work, and how they can impact human behavior, and thereby society.

Learning Goals
At the end of this course, students:
1. Understand how different disciplines, models, and theories contribute to AI for an open society. Particular emphasis will be placed on theories from the social and behavioral sciences, humanities, and governance.
2. Can analyze and evaluate concrete problems related to formal or informal institutions with an eye for how the aforementioned disciplines, models, and theories can contribute to it, and where opportunities are for multi- and interdisciplinary research.
3. Can create a research proposal to investigate a societal relevant problem. This proposal will require the application of AI techniques through a multi- and interdisciplinary perspective, as well as articulating its relevance to formal and/or informal institutions.

The intended level of the course is that students gain a sufficient understanding of the literature from the domains at hand that they can further explore particular elements in other courses, or by taking part in seminars organized by the Human-centered AI focus area of Institutions for an Open Society strategic theme.
 For the research proposal, the intended level is that it can form the basis for continuation in an individual BSc project outside of the course, if desired and if feasible within the students’ bachelor program.

Examination
1. Learning goals 1 and 2 will be examined through a mid-term, written exam (individual).
2. Learning goal 2 will also be tested through the development of an oral pitch of a research idea (group work).
3. Learning goal 3 will be examined through writing up a research proposal (group work).

For examination elements 2 and 3, students will work together in groups. The lecturers aim to put together students that come from different bachelor programs, so students can learn from each other’s discipline.
 

Content

This course is taught by researchers and teachers from the Utrecht Focus Area Human-centered AI (esp. the special interest groups on Social and Cognitive Modeling and on AI, Government, and Behavior) and the Utrecht Strategic Theme Institutions for Open Societies. The aim is to show students how multi- and interdisciplinary research at the intersection of Human-centered AI and Institutions for Open Societies can benefit research and society. Particular emphasis is placed on contributions that are made from the social and behavioral sciences (Faculty FSW), humanities (Faculty GW), and governance (Faculty REBO).


Expected background of students
This course is open to students from all faculties and backgrounds. Our aim is that you can learn from each other, which we facilitate through group work between students that have different backgrounds. Our minimum requirement is that you have obtained at least 45 EC credits from your own bachelor program before starting the course. In other words: that you know the basics of your discipline and can now learn about its relationship with other disciplines.
It does not matter if you have a background in AI or no AI background at all. Through the group work, you will be challenged to grow in the areas that you, so far, know less about. Although not required, this course is naturally complemented by other courses within the minor “Kunstmatige Intelligentie”.
If you are looking for a course that mostly teaches you technical aspects of AI (e.g., introductions of logic or programming), then we advise you to take other courses. We will touch upon some of these aspects, but always from the perspective of how they intersect with the social and behavioral sciences, humanities, and/or governance.


Further details on teaching structure
The course set-up is as follows. In lectures, students gain an understanding of the available AI models and theories and their relationship with IOS platforms. These models and theories come from different disciplines and can be applied in the research proposal. The examination consists of a midterm exam (testing concepts; individually), an oral pitch of an initial idea (group work), and a final research proposal (group work). Teaching will be a mix of lectures and labs.
The teaching staff and the students will ensure an interdisciplinary environment. Developing social AI models requires knowledge of both engineering science and social science. Moreover, for the connection to IOS, social science and humanities principles need to be applied to a governance context. The teachers will provide this integration. In addition, in the group work, students from different faculties will work together on an assignment. Course completion will require integration of knowledge, but also developing even wider interdisciplinary competencies (e.g., cooperating in an interdisciplinary team, shared leadership, formulating common ground, reflection).

Note: The entire course will be taught in English. This also includes assignments and exams.