Postgraduate DiplomaRobotics, Automation & Control Applications open

Diploma in Ethics and Governance of Collaborative Systems

Online postgraduate diploma of 800 hours in ethics and governance of collaborative systems: 8 modules covering the ethics of collaborative automation, labour and social impact, the European regulatory framework, governance of autonomous systems, transparency and explainability, bias, fairness and privacy, ethical evaluation and auditing, and a final project, with an assigned technical tutor.

Duration6–8 months
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma

Diploma in Ethics and Governance of Collaborative Systems — studying from New Zealand

Robotics and automation are increasingly important in New Zealand, especially in dairy processing, food manufacturing, forestry, horticulture and logistics. Research groups at the University of Auckland and the University of Canterbury lead in robotics and control engineering, and firms in these regions develop automated systems for primary industries. Engineers work on process control, industrial automation and robotic integration for manufacturers and technology providers.

Fees for New Zealand: NZ$2,960 (New Zealand dollar), with instalments and employer sponsorship available.

Relevant bodies in New Zealand

  • Institute of Electrical and Electronics Engineers (IEEE) New Zealand Section
  • Engineering New Zealand
  • Robotics Society of New Zealand

Typical roles

  • Robotics Engineer
  • Automation Engineer
  • Control Systems Engineer
  • Process Automation Specialist

Questions from New Zealand

Which New Zealand bodies recognise robotics and control engineering?

Engineering New Zealand is the professional body, and the Chartered Professional Engineer pathway is the recognised route to professional status. Universities such as the University of Auckland and the University of Canterbury offer accredited engineering degrees. SEIUM's qualifications are private and not accredited by any national body, so their recognition rests with employers or the relevant body.

Do robotics and automation employers in New Zealand value this training?

New Zealand has demand for automation skills in dairy processing, food manufacturing, forestry, and advanced manufacturing. Employers generally value practical project experience and programming ability highly. A SEIUM qualification can strengthen a CV, but whether it counts is for each employer to decide.

Is the programme workable alongside a full-time job in New Zealand?

Yes. The programme is 100% online and taught in English, so you can study from anywhere in New Zealand without a student visa. Master's programmes total 1,900 hours, postgraduate diplomas 800 hours and specialist courses 300 hours. You have an assigned technical tutor, and fees are payable in instalments or sponsored by an employer where possible.

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Learning outcomes

What you will be able to do

01

Apply ethical frameworks to the design and deployment of collaborative systems.

02

Assess the labour and social impact of collaborative automation.

03

Interpret the AI Act and the Machinery Regulation for collaborative systems.

04

Design governance structures based on ISO/IEC 42001.

05

Implement transparency measures and effective human oversight.

06

Manage bias, fairness and privacy in systems that use worker data.

07

Plan ethical audits with stakeholder participation.

Profile

Who it's for

  • Technology governance managers.
  • AI ethics consultants advising industrial clients.
  • Data protection officers dealing with sensors, vision systems and worker data.
  • Compliance managers preparing for the AI Act and the Machinery Regulation.
  • Collaborative systems engineers who want to build ethics into their designs.
  • Digital transformation managers leading automation programmes.
  • Engineering or science graduates looking to enter manufacturing.
Standards & tools

What you'll work with

  • Regulation (EU) 2024/1689 on artificial intelligence (EU AI Act)
  • Regulation (EU) 2023/1230 on machinery (EU machinery safety regulation)
  • Regulation (EU) 2016/679 GDPR (EU General Data Protection Regulation)
  • ISO/IEC 42001:2023 (AI management systems)
  • ISO/IEC 23894:2023 (AI risk management guidance)
  • IEEE 7000-2021 (addressing ethical concerns during system design)
  • BS 8611:2023 (ethical design and application of robots and robotic systems)
  • ISO 10218-2:2025 (safety of industrial robot applications and cells)
  • European Commission ALTAI
  • IBM AI Fairness 360
  • Microsoft Responsible AI Toolbox
  • SHAP
  • OneTrust
Syllabus

8 modules

  1. 1.1Main ethical theories applied to technology
  2. 1.2Collaborative robotics and human work
  3. 1.3Autonomy, dignity and human control
  4. 1.4Moral responsibility in autonomous systems
  5. 1.5AI ethics and EU principles
  6. 1.6Conflicting values in design
  7. 1.7Value-sensitive design
  8. 1.8Risks of dehumanisation
  9. 1.9Professional ethics of the engineer
  10. 1.10Case study: ethical dilemmas in a plant with cobots
  1. 2.1Transformation of employment by robotics
  2. 2.2Reskilling and lifelong learning
  3. 2.3Surveillance and monitoring of workers
  4. 2.4Intensification of the pace of work
  5. 2.5Psychosocial health and robotics
  6. 2.6Social dialogue and collective bargaining
  7. 2.7Inclusion and diversity
  8. 2.8The digital divide on the shop floor
  9. 2.9Social impact indicators
  10. 2.10Workshop: labour impact assessment of an automation project
  1. 3.1Regulation (EU) 2024/1689 on artificial intelligence
  2. 3.2High-risk systems and safety components
  3. 3.3Regulation (EU) 2023/1230 on machinery
  4. 3.4Human oversight requirements
  5. 3.5General Data Protection Regulation
  6. 3.6Workers' rights in the face of algorithms
  7. 3.7Directive on liability for defective products
  8. 3.8Cyber Resilience Act
  9. 3.9Implementation timeline
  10. 3.10Practical exercise: risk classification of an AI-enabled collaborative system
  1. 4.1Technology governance models
  2. 4.2AI management system according to ISO/IEC 42001
  3. 4.3Roles and responsibilities
  4. 4.4Ethics and oversight committees
  5. 4.5Acceptable use policies
  6. 4.6AI risk management with ISO/IEC 23894
  7. 4.7Third-party and supplier management
  8. 4.8Governance indicators
  9. 4.9Internal audits
  10. 4.10Case study: governance structure for a cobot fleet
  1. 5.1Right to explanation and transparency
  2. 5.2Explainability techniques
  3. 5.3Technical documentation of AI systems
  4. 5.4Model cards and dataset datasheets
  5. 5.5Decision logging and traceability
  6. 5.6Communication with workers
  7. 5.7Information to trade union representatives
  8. 5.8Limits of explainability
  9. 5.9Designing effective human oversight
  10. 5.10Practical exercise: transparency sheet for a collaborative system
  1. 6.1Bias in data and algorithms
  2. 6.2Fairness in task allocation
  3. 6.3Privacy in shop-floor sensors
  4. 6.4Data protection impact assessment
  5. 6.5Data minimisation and anonymisation
  6. 6.6Biometrics in industrial environments
  7. 6.7Consent in the workplace
  8. 6.8Security of personal information
  9. 6.9Bias auditing
  10. 6.10Workshop: data protection impact assessment of a vision system
  1. 7.1Algorithmic impact assessments
  2. 7.2The European Commission ALTAI checklist
  3. 7.3IEEE 7000 and ethical design
  4. 7.4Independent audits
  5. 7.5Trust and acceptance metrics
  6. 7.6Stakeholder participation
  7. 7.7Complaint mechanisms
  8. 7.8Continual improvement of governance
  9. 7.9Sustainability and ESG reporting
  10. 7.10Case study: ethical audit of a collaborative deployment
  1. 8.1System description and context
  2. 8.2Analysis of values and impacts
  3. 8.3Applicable regulatory framework
  4. 8.4Proposed governance structure
  5. 8.5Transparency measures
  6. 8.6Privacy and fairness measures
  7. 8.7Audit plan
  8. 8.8Critical evaluation
  9. 8.9Report and presentation
  10. 8.10Final project: final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM Institute campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, which makes the programme compatible with full-time work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is European Commission ALTAI, IBM AI Fairness 360, Microsoft Responsible AI Toolbox, SHAP and OneTrust, in free, academic or evaluation versions. Practical work is based on real procedures: labour and ethical impact assessment of an automation project, risk classification of a system under the AI Act and a governance audit of a cobot deployment. Assessment is continuous by module, plus the final project.

Standards covered: Regulation (EU) 2024/1689 on artificial intelligence, Regulation (EU) 2023/1230 on machinery, Regulation (EU) 2016/679 GDPR, ISO/IEC 42001:2023, ISO/IEC 23894:2023, IEEE 7000-2021, BS 8611:2023, ISO 10218-2:2025.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of Regulation (EU) 2024/1689, Regulation (EU) 2023/1230 and Regulation (EU) 2016/679 (GDPR) applied to real cases, not as a theoretical annex.
Industry software:European Commission ALTAI, IBM AI Fairness 360, Microsoft Responsible AI Toolbox, SHAP and OneTrust, in free, academic or evaluation versions.
Final project:a complete governance framework for a collaborative system, from value and impact analysis to transparency, privacy and fairness measures and an audit plan, reviewed by your tutor.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Context and impacts
Describe the collaborative system and analyse its values and impacts.
Regulatory framework
Identify the applicable AI, machinery and data protection requirements.
Governance structure
Propose the governance structure with its roles and policies.
Transparency and privacy
Define transparency, privacy and fairness measures and the audit plan.
Final project
Present the governance framework with a critical evaluation for review by your tutor.
Career opportunities

Where this takes you

Technology governance managerAI ethics consultantData protection officerCompliance managerCollaborative systems engineerDigital transformation manager
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. No university degree is required.
  • An internet connection and a computer capable of running the programme software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

FAQ

Frequently asked questions

The programme totals 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with European Commission ALTAI, IBM AI Fairness 360, Microsoft Responsible AI Toolbox, SHAP and OneTrust, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.

Prior technical training or professional experience in the sector (no university degree required), a computer capable of running the programme software and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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