AI Ethics Course in Simulated Logistics Operations
Online 300-hour course in AI ethics in simulated logistics operations. 6 modules covering IEEE 1516.4 (verification, validation and accreditation in HLA), MIL-STD-3022 (VV&A documentation of models and simulations) and AnyLogic. Assigned tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this programme. 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 AI in logistics operations simulation.
Apply model verification, validation and accreditation processes.
Identify biases and hidden assumptions in data and models.
Communicate the uncertainty of simulation results.
Assess the risks of misusing results in decision-making.
Establish academic governance mechanisms for simulation projects.
Develop a logistics simulation documented responsibly.
Who it's for
- Logistics simulation engineer looking to specialise in AI Ethics in simulated logistics operations.
- Operational research investigator looking to specialise in AI Ethics in simulated logistics operations.
- Model validation analyst looking to specialise in AI Ethics in simulated logistics operations.
- Logistics data scientist looking to specialise in AI Ethics in simulated logistics operations.
- Logistics planning consultant looking to specialise in AI Ethics in simulated logistics operations.
- Simulation lecturer looking to specialise in AI Ethics in simulated logistics operations.
- Engineering or science graduates looking to enter universities.
What you'll work with
- IEEE 1516.4 (verification, validation and accreditation in HLA)
- MIL-STD-3022 (VV&A documentation of models and simulations)
- IEEE 1730 (distributed simulation engineering process, DSEEP)
- ISO/IEC 25059 (quality of AI systems)
- ISO/IEC 42001 (AI management systems)
- European Code of Conduct for Research Integrity (ALLEA)
6 modules · 300 h
1.1Discrete-event and agent-based simulation1.2Tools: AnyLogic, Simio and SimPy1.3Reinforcement learning in simulated environments1.4Logistics command exercises and wargaming1.5Model validity and fidelity1.6Simulation ethics: models that decide1.7Academic use versus operational use1.8Representation of people in simulation1.9Hidden assumptions and implicit values1.10Case study: simulation of a supply chain in an exercise
2.1VV&A: definitions and responsibilities2.2IEEE 1516 (HLA) standard and interoperability2.3Validation with historical data2.4Sensitivity and uncertainty analysis2.5Overfitting to the simulated scenario2.6Gap between simulation and reality (sim-to-real)2.7Model documentation and its limits2.8Peer review of models2.9Liability for unvalidated models2.10Laboratory: sensitivity analysis of a SimPy model
3.1Synthetic data and its representativeness3.2Bias in simulated scenarios and adversaries3.3Optimisation of inappropriate metrics3.4Poorly specified rewards and reward hacking3.5Valuing lives and property in the objective function3.6Civilian population in logistics models3.7Cultural biases in multinational exercises3.8Groupthink in wargaming3.9Red teams and critique of assumptions3.10Practice: audit of an agent's reward function
4.1From simulation to decision4.2Automation bias in planners4.3Communicating uncertainty to commanders4.4Simulation as an argument for legitimacy4.5Transparency of models for decision-makers4.6Shared responsibility between modeller and user4.7Transfer of learned policies to the real world4.8Lessons from failed models4.9Records and traceability of recommendations4.10Case study: decision based on an erroneous simulation
5.1University research with military scenarios5.2Classification of scenarios and data5.3Publication of models and open-source code5.4Dual use of humanitarian logistics models5.5Students in defence exercises5.6Ethics and review committees5.7Funding and conflict of interest5.8NATO AI principles applied to simulation5.9Good practice in responsible modelling5.10Workshop: code of good modelling practice
6.1Definition of the logistics problem6.2Conceptual model design6.3Implementation and AI agent6.4Verification and validation6.5Analysis of biases and assumptions6.6Ethical assessment of results6.7Model documentation6.8Recommendations for decision-makers6.9Report and presentation6.10Final review with the tutor
How you'll learn
Fully 100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: students progress at their own pace within the intake, which makes it possible to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is AnyLogic, Python (SimPy), Arena, Simio, in free, academic or evaluation versions. The tests are studied on real procedures from supply-chain simulation laboratories, verification and validation reviews of models, and sensitivity analysis of scenarios. Assessment is continuous per 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 AI in logistics operations simulation.
Apply model verification, validation and accreditation processes.
Identify biases and hidden assumptions in data and models.
Communicate the uncertainty of simulation results.
Assess the risks of misusing results in decision-making.
Where this takes you
Requirements
- No prior degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow the reading of technical standards.
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 between 10 and 15 hours a week on average, compatible with full-time work.
The programme uses AnyLogic, Python (SimPy), Arena, Simio. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An in-house SEIUM Institute diploma awarded upon passing the continuous assessment and the integrating project. It is in-house training, not an official title 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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