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In this episode of the AI Voice Bot Podcast, Dave explores one of the most pressing — and least discussed — challenges in voice technology: algorithmic bias.
Despite AI voice systems managing over a billion customer interactions daily, research shows they’re up to 25% less accurate for minority accents and dialects — leading to real-world frustration, exclusion, and even discrimination in essential services like healthcare and banking.

The discussion reveals how these biases aren’t random bugs but structural issues embedded in the training data itself. From accent and gender bias to socioeconomic blind spots (like noisy workplaces or old devices), the episode exposes how AI can unintentionally reinforce existing inequalities.

Dave breaks down how companies and regulators are tackling this — through EU AI Act mandates, synthetic data balancing, bias audits, and Zero Trust principles that verify every step of the AI pipeline for fairness and accountability.

The takeaway is clear: if we don’t fix AI bias now, we risk building a two-tiered digital society. But the good news? Every user report, every piece of feedback, helps make the system smarter and fairer.

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