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Home > Open Access Journals > JSS > Vol. 19 > No. 2 (2026)

 

Author Biography

Sajjad Ahmed received his Master's degree in Strategic Studies from National Defence University Islamabad (Pakistan) and Ph.D. in Strategic & Security Studies from the University Malaysia Sarawak. His research interests are military AI, design security, strategy, and international relations theory.  

Ahmad Nizar Yaakub received his M.Soc.Sc. in International Relations from University of Waikato, New Zealand and his Ph.D. in International Relations from the University of Western Australia. Currently, he is Associate Professor at the University Malaysia Sarawak. His research interests are strategy and security, democracy, cross-state relations, and development.

Asma Javed earned her Master's degree from Quaid-i-Azam University Islamabad (Pakistan) in Defence and Strategic Studies. She is currently Lecturer at Islamabad Model College for Girls. Her research interests are AI, cyberspace, and conflict and strategic studies. 

DOI

https://doi.org/10.5038/1944-0472.19.2.2527

Subject Area Keywords

Asymmetric warfare, Complex operations, Defense policy, Development and security, International relations, International security, Pakistan, Security studies, Small wars and insurgencies, War studies

Abstract

Debates on military artificial intelligence (AI) remain skewed toward great power dynamics, oscillating between techno-optimist celebrations of speed and techno-pessimist warnings of collapse. This binary overlooks how middle powers, operating under nuclearized rivalry and asymmetric sanction risk, embed restraint into organizational and technical practice. This article develops Systems Restrained Realism (SRR), a framework that extends defensive realism into the machine age by theorizing restraint as a deliberate doctrinal posture rather than a symptom of incapacity. Using Pakistan as a critical case, the study draws on expert interviews, procurement manuals, and UN submissions to demonstrate how restraint is operationalized through latency as doctrine, embedded organizational oversight, and localized training regimes designed to mitigate classifier fragility. The findings reveal that while India’s accelerationist AI trajectory projects capability and ambiguity, Pakistan engineers restraint into systems and decision loops, externalizing it through normative signaling at UN forums. This posture highlights a structural asymmetry: Great powers can afford AI misfires under the banner of innovation, while middle powers face punitive scrutiny for errors, incentivizing opacity over transparency. By foregrounding SRR, the study challenges dominant narratives that equate restraint with weakness and automation with stability. It argues that in an era of machine-speed conflict, survival may hinge not on what states automate but on what they refuse to.

Acknowledgements

The authors acknowledge partial funding by UNIMAS and worthy interviewees whose insights helps the study to standalone in the field.

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