This article examines the interplay between contemporary algorithmic security technology and the political theory of the state of exception. I argue that the exception, as both a political and a technological concept, provides a crucial way to understand the power operating through machine learning technologies used in the security apparatuses of the modern state. I highlight how algorithmic security technology, through its inherent technical properties, carries exceptions throughout its political and technological architecture. This leads me to engage with Theodor Adorno’s (...) negative dialectics to interrogate the question of ‘ground truth’ in machine learning. I conclude that most machine learning technology asserts identity between itself and bourgeois reality – and thus inherently reinforces and reproduces the relations of domination entailed in that image of the world. However, space still exists for machine learning to operate within spaces of political non-identity, or exceptions to the bourgeois totality, and aid in liberatory politics. (shrink)

This paper analyses how security affects well-being. Security is understood as someone’s sureness of enjoying some good in the future; well-being is treated as a matter of human flourishing. Security can contribute to our well-being in various ways: if we are in fact bound to enjoy a good, in principle this is positive for our flourishing in the future; if we also believe that we will enjoy this good, we can be more efficient in pursuing our well-being; if we also (...) feel secure, this supports our enjoyment of our physical and mental capacities. For some of these benefits to obtain fully, however, it is important that our beliefs and feelings align with the facts. Furthermore, mirroring security’s upsides, there are also ways in which security can hamper our flourishing: it can obstruct the change, surprise, and pleasurable fear that are sometimes required for a good life too. (shrink)