AI Ethics in Practice: Human Resources course is for AI ethics professionals advising on AI in the employment lifecycle. Covers fairness in hiring AI, the ethics of monitoring and surveillance systems, transparency obligations, and the governance of agentic AI in HR, a domain the EU AI Act explicitly classifies as high-risk.
AI now shapes every stage of the employment lifecycle, from resume screening and candidate scoring through performance management, workforce analytics, and employee monitoring. These systems make or inform some of the most consequential decisions in a person's working life, often at scale and with limited transparency to the individuals affected. HR AI sits where economic security, dignity, and legally protected rights all apply at once, and the EU AI Act explicitly classifies several of its applications as high-risk.
This microcredential helps IEEE CertifAIEd professionals apply their ethics expertise to that risk profile. Learners examine fairness analysis in AI-assisted recruitment, including proxy discrimination and disparate impact across protected characteristics. They study the ethical risks of productivity tracking, sentiment analysis, and algorithmic performance ratings, with particular attention to consent and dignity in continuous monitoring contexts. Transparency and the right to contest are treated as a multi-audience obligation, owed to employees, managers, regulators, and works councils. The final module covers lifecycle governance, stakeholder engagement with workforce representatives, and the path to IEEE CertifAIEd Product and System Certification.
Generative and agentic AI in HR, including autonomous sourcing agents, algorithmic scheduling, and AI performance coaching, are treated throughout as intensifying pre-existing concerns about automation bias, accountability diffusion, and the erosion of human judgment in employment decisions.
IEEE CertifAIEd AI Ethics Professional certificate holders working in, with, or adjacent to human resources functions. This includes HR technology leads, people analytics practitioners, talent acquisition and workforce planning professionals, and ethics practitioners advising organizations on AI deployment in employment contexts.
• Introduction
• Module 1: The HR AI Landscape
• Module 2: Fairness and Non-Discrimination in Hiring AI
• Module 3: Performance Monitoring and Surveillance AI
• Module 4: Transparency, Explainability, and the Right to Contest
• Module 5: Agentic AI and Autonomous HR Decision-Making
• Module 6: Governance, Workforce Stakeholders, and the Path to Certification
• Conclusion
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