About
Research objectives and contributions
The AutoNorms project (August 2020 – July 2026) developed a new theoretical approach allowing us to study the bottom-up process of how norms manifest and develop in practices.
Practices are patterned ways of doing things in different social contexts. This interdisciplinary concept combines sociology, constructivist International Relations, and critical legal scholarship in accentuating the constitutive quality of practices as sites of norm emergence and change. AutoNorms argued that norms, broadly defined as social understandings of appropriateness, evolve through practices, and subsequently have implications for the international order.
A focus on practices allowed the AutoNorms project to study the micro-level of norm emergence in the field of autonomous weapon systems (AWS) and AI in warfare from the bottom up, going beyond formal norm-codification activities on a macro-level.
The AutoNorms project had three research objectives:
- To analyse how and under what conditions norms emerge and change in practices.
- To analyse how understandings of perceived appropriateness about autonomising the critical functions of weapons systems emerge and evolve across military, transnational political, dual-use, and popular imagination contexts in four states (China, Japan, Russia, the US).
- To investigate how emerging norms on AWS will affect the make-up of the current international security order.
The project contributed to debates on algorithmic warfare in International Relations and beyond:
Conceptually, AutoNorms developed analytical models for how use-of-force norms emerge and are shaped in operational, hidden and public-deliberative practices. Such social norms shape what states consider ‘appropriate’ behaviour when it comes to developing and using AI in the military domain.
Empirically, the project traced the trajectories of norms in relation to weaponised AI across China, Japan, Russia, and the US.
How do weapon systems that integrate autonomous and AI technologies change international norms?
Case studies and methods
The AutoNorms Project worked with the case studies of prominently positioned states in international security that represent varied positions on the issue of AWS: China, Japan, Russia, and the United States. It demonstrated the significance of these states’ practices in shaping emerging norms on AI in the use of force.
To gain access to practices, the AutoNorms project combined five comparative, qualitative methods: (1) building a qualitative, technological database of weapon systems with automated and autonomous features; (2) narrative interviewing; (3) participant observation; (4) visual analysis; (5) and a public opinion survey.
The AutoNorms project built a nuanced, in-depth empirical basis of the degrees to which AI has become integrated into the weapon systems of prominent states