In the context of AI, this refers to systematic errors in how AI models interpret data or make decisions, often reflecting imbalances in the data they were trained on. In a contact center, bias can lead to unfair or inconsistent treatment of certain customer groups — such as misinterpreting intent, offering different levels of service or reinforcing stereotypes. Mitigating bias is essential to building ethical, inclusive AI systems that deliver fair and trustworthy customer experiences.
