Course in Ethics of Citizen Data Use
Online 300-hour course in ethics of citizen data use. 6 modules covering Regulation (EU) 2024/1689 on Artificial Intelligence, Regulation (EU) 2016/679 General Data Protection Regulation and Fairlearn. Assigned tutor and enrolment open.
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
Differentiate between legal compliance and ethics in data use.
Identify sources of bias and discrimination in urban data.
Audit algorithmic systems using fairness metrics.
Design mechanisms for transparency and accountability.
Apply international ethical frameworks to municipal systems.
Analyse urban cases involving complex ethical dilemmas.
Propose models of ethical governance for citizen data.
Who it's for
- Data ethics officer looking to specialise in Ethics in Citizen Data Use.
- Data protection officer looking to specialise in Ethics in Citizen Data Use.
- Algorithmic auditor looking to specialise in Ethics in Citizen Data Use.
- Responsible AI consultant looking to specialise in Ethics in Citizen Data Use.
- Public innovation officer looking to specialise in Ethics in Citizen Data Use.
- Digital policy analyst looking to specialise in Ethics in Citizen Data Use.
- Graduates in engineering or science seeking to enter local government.
What you'll work with
- Regulation (EU) 2024/1689 on Artificial Intelligence
- Regulation (EU) 2016/679 General Data Protection Regulation
- Charter of Digital Rights (Government of Spain, 2021)
- UNESCO Recommendation on the Ethics of Artificial Intelligence (2021)
- OECD Recommendation of the Council on Artificial Intelligence
- Ethics Guidelines for Trustworthy AI by the European Commission's High-Level Expert Group
- Law 15/2022 on comprehensive equal treatment and non-discrimination
- ISO/IEC 42001 Artificial intelligence management systems
6 modules · 300 h
1.1Data ethics versus legal compliance1.2Principles: autonomy, justice, beneficence, non-maleficence1.3The citizen as subject, not as a resource1.4Surveillance capitalism and public space1.5Consent in shared urban spaces1.6Reasonable expectations of privacy1.7Data as a common good1.8Municipal technological sovereignty1.9Charters of digital rights1.10Case study: ethical dilemma of sensors in a park
2.1Sources of bias in urban data2.2Under-representation of vulnerable groups2.3Algorithmic discrimination in social services2.4Algorithmic fairness metrics2.5Predictive policing and its critiques2.6Allocation of benefits through algorithms2.7Explainability and the right to an explanation2.8Independent algorithmic auditing2.9The SyRI case in the Netherlands and BOSCO in Spain2.10Laboratory: bias audit of a benefits model
3.1Public registers of algorithms3.2Model cards and datasheets3.3Clear communication with citizens3.4Participation in system design3.5Complaint and human review mechanisms3.6Oversight by independent bodies3.7Algorithmic impact assessment3.8Accountability in supplier chains3.9Transparency in AI procurement3.10Workshop: public record of a municipal algorithm
4.1Ethics guidelines for trustworthy AI4.2UNESCO Recommendation on the Ethics of AI4.3OECD Principles on AI4.4Spain's Charter of Digital Rights4.5Municipal data ethics committees4.6Cities for Digital Rights coalition4.7Professional codes of conduct4.8Spanish Agency for the Supervision of AI4.9ALTAI assessment framework4.10Practice: ALTAI self-assessment of an urban system
5.1Intelligent video surveillance and facial recognition5.2Mobility data and tracking of individuals5.3Health data in health crises5.4Public space management with analytics5.5Targeted advertising on street furniture5.6Children's data and school environments5.7Secondary use of data for research5.8Collaboration with private platforms5.9Smart city and surveillance of dissent5.10Case study: contact tracing during the pandemic
6.1Selection of the system or service6.2Map of stakeholders and values at stake6.3Identification of ethical risks6.4Bias and fairness audit6.5Proposal of transparency measures6.6Participation and review mechanisms6.7Proposed ethical governance framework6.8Ethical monitoring indicators6.9Report and presentation6.10Final review with the tutor
How you'll learn
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 Fairlearn, AI Fairness 360, Python, Miro, ALTAI (self-assessment tool), in free, academic or evaluation versions. The case studies are based on real bias-auditing procedures in a benefits allocation system, drafting a public record of a municipal algorithm, and ethical deliberation on video analytics in public space. Assessment is continuous across modules, plus a final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Differentiate between legal compliance and ethics in data use.
Identify sources of bias and discrimination in urban data.
Audit algorithmic systems using fairness metrics.
Design mechanisms for transparency and accountability.
Apply international ethical frameworks to municipal systems.
Where this takes you
Requirements
- No prior qualification is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical regulatory texts.
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 comprises 300 hours in total, spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
The programme uses Fairlearn, AI Fairness 360, Python, Miro, ALTAI (self-assessment tool). Free, academic or evaluation versions are used, and the tutor indicates the open-source alternative where one exists.
A SEIUM own diploma upon passing the continuous assessment and the integrating project. This is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area can be credited towards the advanced programme. Check the recognition policy when you enrol.
Related programmes
Course in Introduction to Large Bridge Structures
Online course of 300 hours in large bridge structures, structured in 6 modules covering bridge types, design actions, long-span typologies, substructure and foundations, and construction processes,…
Electronic Interlocking and Safety Course
Online course of 300 hours in electronic interlockings and safety, structured in 6 modules covering interlocking logic, electronic interlocking architectures, functional safety, software and application data,…
Direct Current Railway Electrification Course
Online course of 300 hours in DC Railway Electrification: 6 modules covering DC traction systems, rectifier substations, catenary and third rail, the return circuit and stray…
More in Civil, Rail & Smart Cities
All Civil, Rail & Smart Cities programmes → · How to apply · Fees & financing · Scholarships