Ethical, legal, and social challenges of data economy in defence the case of battlefield data

Abstract Battlefield data have become a critical asset in contemporary defence. Yet there is a gap in the relevant literature, whilst it addresses various aspects of defence data management—including cybersecurity, interoperability, and decision-making support—it overlooks how these data should be collected, curated, and accessed to enhance the responsible development of AI-enabled defence capabilities. This article addresses this gap first by reviewing existing data policies strategies of NATO and Five Eyes Member States to assess the extent to which they focus on battlefield data, and then by outlining how national defence organisations should manage these data to maximise their strategic value whilst mitigating the attendant ethical, legal, and social risks. We argue that due to their non-rivalrous, artificially excludable nature, battlefield data should be conceptualised as an artificial club good and that national defence organisations have ethical obligations to act as club manager to leverage the potential of these data to develop more robust, reliable and controllable AI defence capabilities. We conclude the analysis proposing two sets of policy recommendations to aid national defence organisations in discharging their responsibilities as club managers for battlefield data.

Authors

Institutions

Publication Details

Journal
AI & Society
Published
2025-09-22
DOI
https://doi.org/10.1007/s00146-025-02610-5
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ethical, legal, and social challenges of data economy in defence the case of battlefield data

Mariarosaria Taddeo, Brian Kot, Jack Burling Nebe
AI & Society
Ethics and Social Impacts of AI
article

Ethical, legal, and social challenges of data economy in defence the case of battlefield data

Mariarosaria Taddeo, Brian Kot, Jack Burling Nebe
article en

Abstract

Abstract Battlefield data have become a critical asset in contemporary defence. Yet there is a gap in the relevant literature, whilst it addresses various aspects of defence data management—including cybersecurity, interoperability, and decision-making support—it overlooks how these data should be collected, curated, and accessed to enhance the responsible development of AI-enabled defence capabilities. This article addresses this gap first by reviewing existing data policies strategies of NATO and Five Eyes Member States to assess the extent to which they focus on battlefield data, and then by outlining how national defence organisations should manage these data to maximise their strategic value whilst mitigating the attendant ethical, legal, and social risks. We argue that due to their non-rivalrous, artificially excludable nature, battlefield data should be conceptualised as an artificial club good and that national defence organisations have ethical obligations to act as club manager to leverage the potential of these data to develop more robust, reliable and controllable AI defence capabilities. We conclude the analysis proposing two sets of policy recommendations to aid national defence organisations in discharging their responsibilities as club managers for battlefield data.

AI & SocietyVol. 41(2)
University of Oxford (GB)
Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 75%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.