AI's Errors May Be Impossible To Eliminate: What That Means for Its Use in HR

This session confronts one of the most important and under-discussed realities of AI in the workplace: that current AI systems produce errors that may be structurally difficult or impossible to fully eliminate.

For HR professionals, this is not a reason to avoid AI - it is a reason to use it with informed, deliberate judgment. Participants will examine the nature of AI errors in the context of HR tasks, develop frameworks for appropriate oversight, and build the critical evaluation skills needed to use AI responsibly in a people-management context.

Why should you Attend: If you're using AI in HR without a clear framework for when to trust it and when to verify - you are carrying a risk you may not have named yet. If you've noticed AI outputs that seemed plausible but turned out to be wrong, or if you're being asked to implement AI in HR processes without adequate guidance on error management, this session gives you the grounding and the framework to do it responsibly.

Areas Covered in the Session:

• Why AI errors may be structurally irreducible: a plain-language explanation
• What AI errors look like in practice: hallucinations, bias, and confident inaccuracies
• High-risk HR contexts: where AI errors carry the greatest consequences
• The oversight imperative: building human review into AI-assisted HR processes
• Developing AI critical literacy: how HR professionals can evaluate outputs effectively
• Organizational accountability: policies, documentation, and audit trails
• Balancing efficiency and responsibility: a framework for AI use in HR

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