6 Topics
5 Days
30 Sessions
Programme Overview
Training Description
Who Should Attend
• HR Professionals and Managers
• HR Technology Specialists
• Talent Acquisition Leads
• Learning and Development Experts
• DEI and Ethics Officers
• Data Protection and Compliance Officers
• HR Consultants and Analysts
• Workforce Planners
• HR Policy Makers
Session Objectives
- Understand the intersection of AI, ethics, and human resource management
- Explore ethical dilemmas and risks in HR automation and analytics
- Identify and mitigate algorithmic bias in recruitment and HR decisions
- Align AI practices with legal and regulatory compliance
- Develop responsible AI governance frameworks for HR
- Integrate fairness, explainability, and transparency into HR AI tools
- Promote inclusive, non-discriminatory outcomes through AI-driven processes
- Ensure data privacy and employee trust in AI-enabled HR functions
- Design AI systems that reflect organizational values and human dignity
About the Course
As artificial intelligence (AI) continues to revolutionize human resource management, organizations must embrace ethical frameworks to ensure fairness, transparency, and accountability in their HR processes. The AI Ethics and Responsible Application in HR Practices Training Course provides HR professionals, talent strategists, and compliance officers with the tools to ethically harness AI in areas such as recruitment, employee monitoring, performance evaluation, and workforce planning. With regulatory scrutiny increasing globally and concerns around bias, privacy, and trust, this course equips participants with strategies to integrate AI in HR responsibly, aligning with international best practices and human-centric design principles.
Participants will explore real-world HR use cases of AI deployment and learn to assess algorithmic fairness, mitigate biases, and build ethical oversight into AI systems. This course also focuses on compliance with data protection laws, aligning AI applications with DEI goals, and developing governance frameworks for future-proofing HR innovations. Whether you are piloting AI or scaling intelligent systems, this training ensures you implement AI in HR with integrity, respect, and confidence.
Curriculum & Topics
6 Topics | 30 Sessions
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Workshop 1.1:
Defining AI and its applications in human resources
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Workshop 1.2:
Introduction to AI ethics principles and frameworks
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Workshop 1.3:
Ethical decision-making in HR contexts
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Workshop 1.4:
Opportunities and risks of AI in talent management
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Workshop 1.5:
Overview of HR automation and predictive analytics
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Workshop 2.1:
Understanding sources of bias in AI algorithms
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Workshop 2.2:
Disparate impact and fairness audits in hiring tools
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Workshop 2.3:
Auditing job matching and resume screening systems
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Workshop 2.4:
Case studies of biased recruitment algorithms
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Workshop 2.5:
Strategies to enhance equity and inclusivity in AI hiring
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Workshop 3.1:
The need for explainable AI (XAI) in HR functions
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Workshop 3.2:
Communicating algorithmic decisions to employees
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Workshop 3.3:
Tools for model interpretability and trust building
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Workshop 3.4:
Managing black-box systems in sensitive HR areas
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Workshop 3.5:
Employee rights to explanation and recourse
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Workshop 4.1:
Ethical concerns with employee data collection
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Workshop 4.2:
Boundaries of AI-powered monitoring tools
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Workshop 4.3:
Consent and transparency in workplace analytics
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Workshop 4.4:
Data anonymization and minimization practices
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Workshop 4.5:
Ethical use of wearables, sensors, and biometrics
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Workshop 5.1:
Overview of GDPR, EEOC, and AI legislation
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Workshop 5.2:
Discrimination laws and AI in employment practices
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Workshop 5.3:
Risk assessments and algorithmic impact analysis
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Workshop 5.4:
Developing HR AI compliance documentation
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Workshop 5.5:
Emerging global regulatory trends in HR tech
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Workshop 6.1:
Bias in AI-powered performance reviews
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Workshop 6.2:
Personalized learning paths and fairness concerns
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Workshop 6.3:
Ethical issues in productivity tracking and nudging
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Workshop 6.4:
Data ethics in training recommendation systems
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Workshop 6.5:
Transparency in upskilling and internal mobility AI tools
