Remedies within warfare practices: Integrating artificial intelligence to improve joint targeting

The dissertation project engages in warfare practices at the heart of joint operations, where the effective use of tactical means to reach operational objectives reside. It explores how joint targeting concepts could evolve if artificial intelligence technologies and methods were used to solve current challenges within the joint targeting practices

On a general level, the study will generate knowledge by exploring emerging socio-technical practices in warfare. More specifically, the project aims to demonstrate how two AI-models solve two different problems within contemporary joint targeting practices under a specified set of conditions. It therefore pays attention to what AI means for joint targeting, where applied forms of AI could integrate into the practices, and how it could augment the practices by supporting some of the cognitive human challenges that are indicative for a new era of warfare.

Applied forms of AI in joint targeting practices

The proposed research question is: how can applied forms of AI be used in joint targeting practices? To address the aim and to answer the research question, the project builds a theoretical framework using existing decisions theories complemented with the existing contemporary practices of joint targeting.

The method used is laboratory experiments which are sequenced as follows:

1. understand the challenges of the current practices of targeting focusing on two aspects (comprehension and speed) of the cognitive limitations of humans;
2. define two use-cases that would represent relevant situations of practices that could be imitated, learned and effectively performed by AI-models two areas;
3. build two different AI-models used for the empirical part;
4. explore AI’s potential through laboratory experiments, and;
5. generate ideas for emergent concepts of AI integrations in joint targeting practices.

The results will be indicative of how applied forms of AI can be built and used to solve challenges within joint targeting practices. This will increase the understanding of what artificial intelligence means for the joint targeting process, and expand the knowledge in areas where machines can augment human cognition and how this affect the human decision-making.

Moreover, these experiments enable comparisons between the effects of AI- interventions and contemporary practice. The external relevance of this project is assessed to be policy-related, and informative for military and governmental decision-making concerning strategies on future warfighting capabilities development involving AI, research and future investments or impending integrations kindred to this area of research.

The internal relevance is that the results will provide new knowledge towards emergent joint targeting concepts and practices. Furthermore, it may indicate future displacement effect on the interactions, roles and responsibilities of humans and machines. The results may also support other scholars engaged in applied research related to military applications of AI. It may also inspire research on human-machine integrations and teamwork, adding to the body of social science knowledge where the experimental approach is used for war studies.