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Paper short abstract

This presentation asks how phenomenological soldierly sensitivity and its associated forms of expertise change due to the use and application of predictive AI. It examines how sensory expertise in military ground operations becomes polarized, calling for new conceptions of targeting practice.

Paper long abstract

Military worlds are currently profoundly shaped by the implementation of predictive AI. Interestingly, the same tools that are used to destroy may, in certain environments, also save lives. As Louise Amoore points out, ‘algorithms designed to save lives, via robot surgery, or to end lives, via robot warfare, share the same arrangements of propositions’ (2020: 58). With the advent of predictive AI, the labor of war has taken a further twist, as decision-making based on AI predictions not only affects but also redefines how sensate regimes (McSorley 2020) are organized and redistributed.

In such contexts, versions of expert sensitivity are rearranged, reformulating affordances that have historically characterized specific regimes aimed at apprehending human bodies for the broader purpose of ‘targeting’. Soldiers engaged in operations are increasingly confronted with sensory adjustments and new kinds of embodiment that raise questions about how expertise ecologies shaped by predictive AI repurpose skills, situated experience, and decision-making processes. As Erik Reichborn-Kiennerud recently notes, “military targeting is about more than the mere act of seeing, taking aim, firing, and destroying a target” (2025: 3). In line with these ideas, my presentation examines how phenomenological soldierly capacities are reconfigured alongside emerging ‘targeting’ possibilities. It asks how sensory expertise within armed forces conducting ground operations becomes polarized, calling for new definitions of targeting practice.