DSPO 27A40 - Artificial Intelligence in Policy Making

Artificial Intelligence is being progressively introduced in the public sector as a hype method globally used to deliver public services. The aim of this course is to analyse how policy making and Artificial Intelligence may be intertwined in a dynamic that has major impacts on the definition of public service itself. This course will put some perspective on the integration of Artificial Intelligence related tools. How are they likely to affect policy making processes? Will they change the relation between the administration and citizens? Do they enable the delivery of new public services? Students will be able to emphasize the adoption of AI in a historical context of progressive adoption of technologies, from traditional bureaucracies to essentially digital governance and e-bureaucratic forms. We will focus on the study of major AI technologies and their potential uses, and the value of data as a resource and product of administrations as well as data ethics. Students will analyse use cases of AI adoption in major policies such as health, education, bureaucracies, security, or climate change mitigation. The adoption of AI will be analysed with regards to the implementation contexts, from international to citizen related approaches. Students will learn to critically assess the relation between AI public-based policies and the creation of public value, the potential leverages, risks or barriers, and the geopolitics of public AI. Finally, they are expected to develop a critical approach on how not only public agents, but also citizens, have major roles to play in the adoption of these technologies.

Josefina GIMENEZ-CAHUZAC,Nicolas SPATOLA

Séminaire

English

None

Spring 2024-2025

- Participation (10%): students are expected to actively engage in discussions in class, making appropriate use of the literature. - Data trial (10%): Students will work in groups to mock a trial on data. Information will be provided during the class, and complementary research can be carried during the class. Students will be assessed on their capacity to mobilize concepts and examples to defend the statement they will be assigned. - Midterm Assignment (30%): Class presentation and slide pack. In groups, students will freely choose a use case on a particular policy. They will be assessed on the oral performance in class (20 minutes max) and on the content of the slide pack (6 slides max). - Final Assignment (50%): Essay (4000 words max). Students will freely choose one particular topic studied on the third part of the course, and critically analyse one of the major challenges that the integration of AI in the public sector raises (geopolitical, citizen implication, foresight…), suggesting scenarios or alternative solutions (geopolitical, citizenship, foresight…).