This Reflection draws from an ongoing collaboration among the three authors, investigating mutual enlistment between the United States Department of Defense and research communities devoted to the advancement of the AI project. We are interested in the intersecting concerns and resonant sensibilities that draw us together – what we argue is the necessary starting point for interdisciplinary thinking – and in the differences that are the collaboration’s generative possibilities. Among the threads that join us are intersecting pathways between academic and commercial positionings within and against the AI project. Each of us has moved between locations in industry and the university, as researchers, practitioners, and students/faculty. Drawing on these experiences, we explore the possibilities that different positionings afford and what they preclude, how we have attempted to navigate these institutions within their frames of reference, and what has drawn us into relations beyond their putative boundaries. Based on Philip Agre’s call for a “critical technical practice” as a path towards more radical shifts in knowledge practices, we consider how we might weave together our biographical trajectories, disciplinary affiliations, political commitments, subjectivities, and skills into what Andrew Barry and Georgina Born name a more “auspicious interdisciplinarity”.

A uniform approach to computing with infinite objects like real numbers, tuples of these, compacts sets and uniformly continuous maps is presented. In the work of Berger, it was shown how to extract certified algorithms working with the signed digit representation from constructive proofs. Berger and the present author generalised this approach to complete metric spaces and showed how to deal with compact sets. Here, we unify this work and lay the foundations for doing a similar thing for the much more comprehensive class of compact Hausdorff spaces occurring in applications. The approach is of the same computational power as Weihrauch’s Type-Two Theory of Effectivity.

Making sense of digital security practice requires grasping how data are put to use to compose the governing of individuals. Data need to be understood in their becoming, and in their becoming something across diverse practices. To do this, we suggest embracing two conceptual tropes that jointly articulate the being together of, and in, data compositions: composting and computing. With composting, we approach data as lively entities, and we explore the decaying and recycling processes inside Big Data security. With computing, we approach data as embodied and embodying elements, and we unpack the surveillance of ‘asylum speakers’. Together, composting and computing challenge recurrent images of data. Our conceptual composition takes sound as a necessary sensory counterpoint to popular data visions, notably in light of Ryoji Ikeda's artworks.

Traditionally, navigation has been taught with methods employing Napier's rules for spherical triangles while methods derived from vector analysis and calculus appear to have been avoided in the teaching environment. In this document, vector methods are described that allow distance and azimuth at any point on a great circle to be determined. These methods are direct and avoid reliance on the formulae of spherical trigonometry. The vector approach presented here allows waypoints to be established without the need to either ascertain the position of the vertex or select the nearest pole; the method discussed here requires only one spherical triangle having an apex at the North Pole and is also easy to implement on a small computer.