Technologies increasingly shape the ways in which conflicts emerge, are conducted, governed, represented, and resolved. The aim of the course is to introduce students to the analysis of the relationship between conflict and technology, examining how nuclear weapons, artificial intelligence, cyber capabilities, surveillance systems, drones, platforms, and data-driven tools transform contemporary security dynamics.

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The course aims to introduce students to the analysis of the relationship between conflict, security, and technology from a variety of perspectives. It explores how technologies have shaped the conduct, representation, governance, and experience of conflict across different historical and contemporary settings, from earlier debates on war and military innovation, with a special emphasis on the issue of armaments, particularly nuclear weapons, to contemporary issues such as cyber warfare, artificial intelligence, drones, surveillance systems. The course seeks to blend knowledge of academic literature on the subjects and understanding of empirical realities. Students are expected to actively participate in class by reading the assigned material in advance and by preparing group presentations on case studies related to relevant technologies and conflict dynamics.

Key Readings include: (1) Solingen, Etel (1994) ‘The political economy of nuclear restraint’, International Security, 19(2): 126-169 (2) Waltz, Kenneth (1990) ‘Nuclear myths and political realities’, The American Political Science Review, 84(3): 731-745 (3) Tannenwald, Nina (2018) ‘How Strong Is the Nuclear Taboo Today?’, The Washington Quarterly, 41:3, 89-109 (4) Greathouse, C. B. (2013). Cyber war and strategic thought: Do the classic theorists still matter?. In Cyberspace and International Relations: Theory, prospects and challenges (pp. 21-40). Berlin, Heidelberg: Springer Berlin Heidelberg (5) Nye Jr, J. S. (2016). Deterrence and dissuasion in cyberspace. International security, 41(3), 44-71 (6) Iliadis, A., & Russo, F. (2016). Critical data studies: An introduction. Big Data & Society, 3(2), 2053951716674238. The complete list of readings will be given at the beginning of the course.

The course includes a mix of frontal lectures, group discussions and guest lectures by experts in the field. An active class participation is strongly encouraged. Students should come to class having read the assigned readings.

Track 1: to be a Track 1 course-taker you will have to attend at least 75% of classes, attendance will be checked regularly. Assessment is based on group presentation (30%) and final oral exam (70%) The oral exam is based on the discussion of a research paper written by the student (2.000 words, plus bibliography). Indications on topic-selection and requirements will be discussed in class. Track 2: course-takers who do not attend 75% of classes will be assessed solely on the oral exam (100%).

To be discussed.