Against the background of the growing use of machine learning (ML) based technologies by the military, our article calls for an analytical perspective on ML platforms to understand how ML proliferates across the military and to what effects. Adopting a material–technical perspective on platforms as developed within new media studies, and bringing this literature to critical security studies, we suggest that a focus on platforms and the technical work they do is needed to understand how digital technologies are emerging and shaping security practices. Through a detailed study of Google's open-source ML platform TensorFlow and a discussion of the US Department of Defense Algorithmic Warfare Cross-Functional Team, or Project Maven, we make two broader contributions. First, we identify a broader “platformization” of the military, with which we refer to the growing involvement and permeation of the (technomaterial) ML platform as the infrastructure that enables new practices of decentralized and experimental algorithm development across the military. Second, we draw out how this platformization is accompanied by new entanglements between the military and actors in the corporate domain, especially Big Tech, which play a key role in this context, as well as the open-source community that is organized around these platforms.

Google is increasingly developing a manifold of security products for its users, businesses, and national security actors like the US Department of Defence. However, the company and its employees struggle with whether, and how, it should be involved in practices of security, war or weaponry. To unpack how Google emerges as a security actor, I bring new media studies perspectives regarding the socio-political roles Google plays in today’s society to critical security studies. With this interdisciplinary approach to studying Big Tech’s role in security, this article analyses how Google appropriates security throughout its ecosystem of platforms, products and projects. The article illustrates that Google’s first and foremost objective is to secure its platform by carefully balancing between being perceived as both neutral and progressive. Google thus appropriates (in)security by developing seemingly mundane and neutral security products, services and projects that align with its platform logic. In doing so, Google locks in new users into its platforms, whilst reshaping (in)security issues into platform issues and identifying the platform as a public and security concern.