Before we dive into AI bias, it’s worth pausing to ask a more foundational question: how do we actually think about AI? The way AI is framed—as objective, intelligent, efficient, or neutral—quietly shapes how much we trust its outputs and how rarely we question them.

In this lesson, you’ll explore five common mental models, or narratives that shape how AI shows up in HR work. Each one reveals something useful about how AI works and each one has blind spots that make biased or misleading outputs easier to miss.

By learning to spot these narratives in action, you’ll sharpen your ability to pause, rethink, and challenge AI recommendations before they turn into real-world decisions about people.

Learning objectives

By the end of this lesson, you will be able to:

• Explain why our assumptions about AI shape how we use it in HR
• Describe AI as a pattern-learning system, not a thinking or reasoning entity
• Identify five common AI narratives and what each one emphasizes
• Recognize how different narratives can create misplaced trust or hidden risks
• Use these narratives as a lens to question AI-supported recommendations in real HR moments

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