AI Governance and Workers' Rights Training Course

AI Governance and Workers’ Rights Training Course

Introduction

Artificial Intelligence (AI) is rapidly transforming global workplaces, reshaping employment structures, decision-making systems, productivity models, and labor relations. As organizations adopt AI-driven automation, algorithmic management, and data-centric workforce analytics, urgent questions emerge around ethical AI governance, labor protection, digital surveillance, bias mitigation, transparency, accountability, and workers’ rights in the algorithmic economy. AI Governance and Workers’ Rights Training Course equips participants with practical and policy-level understanding of how AI intersects with labor rights, ensuring compliance with emerging global frameworks such as EU AI Act standards, ILO labor principles, data protection regulations, and responsible AI governance frameworks.

The course focuses on building capacity among policymakers, HR professionals, union leaders, compliance officers, and tech practitioners to navigate the evolving landscape of AI ethics, workplace automation risks, algorithmic discrimination, gig economy regulation, and digital labor rights protection. Participants will explore real-world case studies of AI misuse and success in workforce management, while developing actionable governance strategies that balance innovation with fairness, accountability, and human dignity in the workplace.

Course Duration

5 days

Course Objectives

1. Understand AI governance frameworks in modern workplaces 
2. Analyze algorithmic bias and workplace discrimination risks
3. Evaluate AI-driven employee surveillance systems
4. Apply ethical AI compliance standards (EU AI Act, OECD AI principles)
5. Strengthen workers’ digital rights protection mechanisms
6. Assess risks in automated HR decision-making systems
7. Promote transparent algorithmic accountability models
8. Integrate data privacy and GDPR-aligned workforce policies
9. Identify challenges in gig economy algorithmic labor platforms
10. Develop strategies for responsible AI deployment in HR tech
11. Enhance understanding of human-in-the-loop AI systems
12. Address impacts of workplace automation and job displacement
13. Build capacity for ethical digital transformation governance

Target Audience

1. HR managers and HR analytics professionals 
2. Policy makers and government labor regulators 
3. Trade union leaders and worker representatives 
4. Corporate compliance and legal officers 
5. AI developers and data scientists 
6. Organizational development consultants 
7. ESG and sustainability officers 
8. Academic researchers and graduate students in labor studies or AI ethics 

Course Modules

Module 1: Foundations of AI Governance in Workplaces

• Core principles of AI governance 
• Ethical frameworks and accountability systems 
• AI lifecycle governance models 
• Stakeholder roles in AI oversight 
• Regulatory landscape overview
• Case Study: Amazon warehouse algorithmic scheduling controversies 

Module 2: Algorithmic Bias and Workplace Fairness

• Bias detection in AI systems 
• Discrimination in recruitment algorithms 
• Fairness metrics in machine learning 
• Mitigation strategies for biased datasets 
• Audit frameworks for HR algorithms
• Case Study: LinkedIn gender bias in job recommendations 

Module 3: AI Surveillance and Employee Monitoring

• Workplace tracking technologies 
• Productivity scoring systems 
• Ethical boundaries of surveillance 
• Psychological impacts of monitoring 
• Transparency and consent frameworks
• Case Study: Uber driver performance algorithm monitoring 

Module 4: Digital Labor Rights in the Gig Economy

• Platform work governance challenges 
• Algorithmic task allocation systems 
• Income fairness and transparency 
• Worker classification issues 
• Legal protection gaps
• Case Study: Uber and Deliveroo worker classification lawsuits 

Module 5: Data Privacy and Workforce Analytics

• Employee data protection laws 
• GDPR and workplace compliance 
• Data minimization principles 
• Consent in workplace analytics 
• Secure HR data governance systems
• Case Study: Microsoft workplace productivity analytics debate 

Module 6: Ethical AI in Recruitment and Performance Management

• AI-based hiring systems 
• Resume screening algorithms 
• Performance prediction models 
• Risk of exclusion and bias 
• Human-in-the-loop hiring systems
• Case Study: Amazon AI recruiting tool failure case 

Module 7: Automation, Job Displacement and Workforce Transition

• AI-driven job transformation 
• Skills disruption forecasting 
• Reskilling and upskilling frameworks 
• Social protection systems 
• Future of work policies
• Case Study: IBM workforce automation restructuring program 

Module 8: Responsible AI Policy Design and Implementation

• AI ethics governance boards 
• Corporate AI compliance structures 
• Multi-stakeholder policy design 
• Risk assessment frameworks 
• Continuous monitoring systems
• Case Study: EU AI Act implementation across industries 

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you