Ethics in Artificial Intelligence in C4ISR Course
Online 300-hour course in ethics in artificial intelligence in C4ISR. 6 modules covering Additional Protocol I, Arts. 36 and 57 (weapons review and precautions), NATO Principles for the Responsible Use of AI (2021) and Python (TensorFlow). Assigned tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Describe the use of machine learning in C4ISR systems.
Define requirements for meaningful human control.
Evaluate the reliability and explainability of fusion and classification models.
Analyse the legal obligations for reviewing new capabilities.
Assign responsibilities across the chain of command and development.
Establish governance processes for the AI lifecycle.
Develop a responsible AI project for a C4ISR system.
Who it's for
- C4ISR systems engineer wishing to specialise in Ethics in Artificial Intelligence in C4ISR.
- Defence data scientist wishing to specialise in Ethics in Artificial Intelligence in C4ISR.
- Human-machine interaction specialist wishing to specialise in Ethics in Artificial Intelligence in C4ISR.
- Operational legal adviser wishing to specialise in Ethics in Artificial Intelligence in C4ISR.
- AI verification analyst wishing to specialise in Ethics in Artificial Intelligence in C4ISR.
- Systems lifecycle manager wishing to specialise in Ethics in Artificial Intelligence in C4ISR.
- Engineering or science graduates seeking to enter the defence sector.
What you'll work with
- Additional Protocol I, Arts. 36 and 57 (weapons review and precautions)
- NATO Principles for the Responsible Use of AI (2021)
- US DoD Directive 3000.09 (autonomy in weapon systems)
- ISO/IEC 23894 (AI risk management)
- IEEE 7001 (transparency of autonomous systems)
- ISO/IEC TR 24028 (trustworthiness in AI)
- Convention on Certain Conventional Weapons (CCW, 1980)
6 modules · 300 h
1.1Command, control, communications, computers and ISR1.2OODA loop and decision support1.3Points of AI integration in C4ISR1.4Data fusion and situational awareness1.5Language models to support staff headquarters1.6Course-of-action recommenders1.7Decision speed and time pressure1.8Limitations of operational data1.9NATO and European defence AI initiatives1.10Workshop: map of automatable decisions in C4ISR
2.1The concept of meaningful human control2.2Human in the loop, on the loop and out of the loop2.3Automation bias and complacency2.4Calibration of trust2.5Interface design for critical decisions2.6Operator cognitive load2.7DoD Directive 3000.092.8NATO principles for the responsible use of AI2.9Training of operators and commanders2.10Practice: evaluation of a decision-support interface
3.1Explainability: SHAP, LIME and saliency maps3.2Model uncertainty and its communication3.3Robustness against adversarial data3.4Deception and disinformation in sources3.5Data drift in operations3.6Testing, evaluation, verification and validation3.7Risk management according to ISO/IEC 238943.8AI management systems according to ISO/IEC 420013.9Documentation of models and data3.10Laboratory: measuring the uncertainty of a classifier
4.1IHL applied to decision-support systems4.2Article 36 reviews under Additional Protocol I4.3Command responsibility and automation4.4The responsibility gap4.5AI-assisted target selection: current debate4.6ICRC reports on AI and military decision-making4.7Political Declaration on Responsible Military Use of AI (2023)4.8Records for subsequent investigation4.9Institutional accountability4.10Case study: erroneous recommendation from a fusion system
5.1AI governance in ministries of defence5.2NATO AI strategy5.3Responsible acquisition of AI systems5.4Independent auditing5.5Defence ethics committees5.6AI red teaming5.7Withdrawal and decommissioning of models5.8Transparency towards parliament and society5.9International cooperation and standards5.10Workshop: governance policy for a C4ISR system
6.1Selection of a decision-support function6.2Description of the system and its data6.3Human control analysis6.4Risk and robustness assessment6.5Legal analysis6.6Test and validation plan6.7Governance framework6.8Final ethical assessment6.9Report and presentation6.10Final review with the tutor
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded lectures and an assigned technical tutor. No fixed timetable: students progress at their own pace within the intake, which makes it possible to combine study with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (TensorFlow), MATLAB, SHAP, MLflow, in free, academic or evaluation versions. Trials are studied using real procedures from model robustness assessments, human control studies in command systems and data fusion case analyses. Assessment is continuous by module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Describe the use of machine learning in C4ISR systems.
Define requirements for meaningful human control.
Evaluate the reliability and explainability of fusion and classification models.
Analyse the legal obligations for reviewing new capabilities.
Assign responsibilities across the chain of command and development.
Where this takes you
Requirements
- No previous degree required.
- Internet connection and a computer capable of running the programme's software.
- A sufficient level of Spanish to follow technical regulatory reading.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 300 hours spread over 3 to 5 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
The programme works with Python (TensorFlow), MATLAB, SHAP, MLflow. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An SEIUM Institute in-house diploma upon passing continuous assessment and the integrating project. It is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the advanced programme. Check the recognition policy when you enrol.
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