AI Governance for Occupational Health and Safety in Africa

AI governance

AI Governance for Occupational Health and Safety in Africa

  • Pacfaie Courses
Course menu
Module 1: AI fundamentals for OHS professionals
  • Welcome: AI governance for workplace safety and how this course works
  • What AI is (and isn’t) in workplace safety
  • How a safety vision model learns
  • The AI lifecycle in an OHS management system
  • Generative and agentic AI in OHS
  • How AI fails at work
  • Measuring performance: missed hazards and false alarms
  • The Africa lens and ten questions to ask
  • Module 1 quiz
Module 2: AI across African workplaces
  • Where AI sits across workplace safety
  • Mining and extractives
  • Construction and manufacturing
  • Agriculture, logistics and the informal economy
  • Suppliers, contractors and who is accountable
  • Mapping opportunity and harm
  • Module 2 quiz
Module 3: Ethics, worker rights and dignity
  • Principles for worker-centred AI
  • Dignity, autonomy and proportionate monitoring
  • Fairness and discrimination at work
  • Worker voice and consultation
  • Responsibility and just culture
  • Workers who need extra protection
  • Module 3 quiz
Module 4: OHS and AI regulation in Africa
  • The regulatory landscape for AI at work
  • OHS duties applied to AI
  • Worker data, employment and labour law
  • Machinery, product safety, standards and the EU AI Act
  • Mapping obligations for an AI system at work
  • Assignment 1: A regulatory obligations map
  • Module 4 quiz
Module 5: Building an AI governance framework for workplace safety
  • AI governance inside the OHS management system
  • Roles, committees and worker participation
  • The AI inventory
  • Risk tiering for workplace AI
  • Proportionate controls for each tier
  • Smaller employers and shared sites
  • Module 5 quiz
Module 6: Worker data, privacy and surveillance
  • What worker data AI collects
  • Lawful basis, purpose and transparency
  • Biometrics and health data at work
  • Privacy by design for safety video
  • Suppliers, cloud and security
  • Data protection impact assessments for workplace AI
  • Module 6 quiz
Module 7: Safety assurance of AI-enabled systems
  • Why AI challenges safety assurance
  • Hazard analysis for AI systems
  • Operational design domains and site validation
  • Alarms, interfaces and human factors
  • Safety cases and evidence
  • Updates and ongoing assurance
  • Assignment 2: Safety assurance of an AI proximity system
  • Module 7 quiz
Module 8: Robots, autonomous machinery and human-machine interaction
  • Robots and autonomous machines at work
  • Keeping people and machines safe together
  • Mixed fleets and transitions
  • Drones at work
  • Remote operation and new work
  • Workforce transition and skills
  • Module 8 quiz
Module 9: Algorithmic management and psychosocial risk
  • What algorithmic management is
  • Psychosocial and physical risks
  • Platform work in Africa
  • Fair targets, transparency and human review
  • Assessing psychosocial risk from algorithmic tools
  • Wellbeing tools, harassment and AI
  • Module 9 quiz
Module 10: AI policy, procurement and shadow AI
  • Putting up an organisational AI policy
  • Drafting, consulting and rolling out the policy
  • Procuring AI safety technology
  • Contracts and supplier management
  • Shadow AI at work
  • Responding to shadow AI
  • Generative AI rules for safety work
  • Assignment 3: AI policy, procurement and shadow AI
  • Module 10 quiz
Module 11: Monitoring, evaluation and compliance assurance
  • Monitoring AI safety systems in use
  • Drift, seasons and AI incidents
  • Evaluating whether AI made work safer
  • Compliance assurance
  • Layers of assurance
  • Reporting, inspection readiness and improvement
  • Assignment 4: A monitoring and assurance plan
  • Module 11 quiz
Module 12: Final exam and capstone
  • Putting it all together: a 12-month roadmap
  • Final exam
  • Capstone: an AI governance programme for Kalahari Resources Group
  • Where to go from here
Length
About 45 hours, self-paced
Lessons
87
Language
English

Sign in to join this course.

Sign in to enrol Create an account

Across Africa, AI now watches mine haul roads for workers too close to trucks, checks construction sites for missing helmets, predicts which machines will fail, scores drivers for fatigue, and schedules shifts in warehouses. Done well, it can prevent injuries and deaths in some of the world’s most dangerous workplaces. Done badly, it can create new hazards, give a false sense of safety, and turn safety tools into surveillance that erodes workers’ rights and dignity. This course trains OHS professionals and others to govern AI so it does the first and not the second.

Who it’s for

OHS managers and officers, safety engineers, HR and wellness leads, operations managers in mining, oil and gas, construction, manufacturing, agriculture and logistics, labour inspectors, trade union and worker safety representatives, insurers covering workers’ compensation, and technology suppliers to these sectors. No technical background or coding is needed: everything is built up from first principles, with workplace examples throughout.

What you’ll be able to do

  • Explain how machine learning, computer vision, generative AI and autonomous systems work in workplaces, and how they fail.
  • Map where AI is used across African workplaces, including informal and contractor-heavy ones.
  • Apply ethics, worker rights and dignity to AI used for safety and management.
  • Identify the OHS, labour, data protection and product safety rules that apply, including ILO conventions and ISO 45001.
  • Design an AI governance framework within an OHS management system.
  • Assure the safety of AI-enabled systems, robots and autonomous machinery.
  • Govern worker surveillance and algorithmic management, including psychosocial risk.
  • Write an AI policy, procure AI safety technology responsibly and bring shadow AI under control.
  • Monitor, evaluate and provide compliance assurance for AI in use.

How it works

Twelve modules, about 45 hours in total, including assignments and the capstone, at your own pace. Each module mixes short readings with interactive practice set in fictional African mines, sites, factories, farms and warehouses. Practice is never marked.

Assessment: a quiz after each module, four applied assignments marked against a published rubric, a timed final exam, and a capstone in which you design AI governance for a fictional African mining and construction group, with peer review and assessor marking.

Certificate

Complete every step to earn the Certificate in AI Governance for Occupational Health and Safety, a verifiable digital certificate and Open Badge. Your capstone result (pass, merit or distinction) is shown on it.

Certificate and badge

Completed twelve modules covering AI fundamentals, AI across African workplaces, ethics and worker rights, OHS and AI regulation, governance frameworks, worker data and surveillance, safety assurance of AI systems, robots and autonomous machinery, algorithmic management and psychosocial risk, AI policy, procurement and shadow AI, and monitoring, evaluation and compliance assurance; passed every module quiz, four rubric-marked applied assignments and a timed final exam; and completed an assessor-marked capstone.

Instructor

  • Pacfaie Courses
Scroll to Top