Description

Title: AI Ethics and HR: Practical Frameworks for a Responsible Future 

Presented virtually by Eric Brown 

Course format: Instructor-led presentation with facilitated roundtable discussion and practical action planning. 

Intended audience: HR professionals, HR leaders, people managers, compliance-minded business leaders, and employers evaluating or using AI in HR processes. 

Course description: This 90-minute session equips HR professionals and business leaders with practical frameworks for using artificial intelligence responsibly in HR. The program explores how AI is already affecting recruiting, workforce analytics, employee support, skills-based hiring, performance management, and internal decision-making. Attendees learn how to identify the ethical, legal, and operational risks associated with AI in HR, including bias, privacy, explainability, accessibility, and governance. Using real-world case examples, current regulatory developments, and practical implementation frameworks, the session helps participants evaluate AI tools more effectively, define where human judgment must remain in control, and build governance practices that reduce risk while supporting innovation. The program includes audience discussion and action-oriented takeaways designed to help organizations strengthen their approach to responsible AI in HR. 

Course relevance to HR practice: This program is directly relevant to HR because it addresses: talent acquisition and candidate screening employee data privacy and governance workforce analytics and predictive modeling compliance and discrimination risk policy development HR leadership and organizational decision-making performance management and skills-based talent practices 

Learning Objectives: 

Differentiate major forms of AI used in HR — including generative AI, machine learning, predictive analytics, and automated decision support — and explain how their risk profiles differ in employment settings. Identify key ethical and legal risks associated with AI in HR, including bias, accessibility, privacy, explainability, and accountability in hiring, performance, and workforce decisions. 

Evaluate whether an AI-enabled HR process includes appropriate human oversight, and distinguish between AI-assisted decision-making and improperly automated employment decision-making. 

Apply a practical governance framework for responsible AI in HR, including pre-deployment review, transparency, human override, ongoing monitoring, and cross-functional accountability. 

Assess current regulatory and compliance considerations affecting AI in HR, including discrimination risk, audit expectations, and emerging requirements related to automated employment decision tools. 

Identify near-term actions their organization can take to implement AI more responsibly, such as auditing tools, strengthening vendor oversight, creating acceptable use standards, and clarifying decision rights.