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Artificial intelligence is rapidly transforming the conditions under which politics is organized, governed, represented, and studied, as well as the ways political science is practiced, researched, and taught.

The integration of platforms, data infrastructures, generative AI, and computational systems is transforming political communication, policy-making, public administration, political participation, and relations between citizens, institutions, markets, technological actors, and teaching and learning.. From algorithmic governance and platform power to digital sovereignty and geopolitical competition over AI infrastructures, these developments are redefining democratic and non-democratic politics.

AI is also transforming political science itself, reshaping the production, analysis, and communication of political knowledge, and the teaching of the discipline. AI-assisted methods and computational tools are changing research practices, scholarly communication, and academic publishing, while also impacting curricula, pedagogical models, learning environments, and disciplinary training.

The track welcomes theoretical and empirical contributions from various disciplinary and methodological perspectives. Relevant topics include, but are not limited to:
●    Algorithmic governance and political power;
●    Representation, participation, and AI-mediated public discourse;
●    Institutions, decision-making, and technological actors in AI-driven environments;
●    AI infrastructures and digital sovereignty;
●    Political science as a discipline in the age of AI;
●    Political knowledge production and research;
●    Scholarly communication and academic publishing;
●    Teaching political science in AI-mediated contexts.