In this episode, we’re tackling a huge question: How do we measure a “good” AI experience?
AI is shaping everything—from hiring decisions to medical diagnoses, from content recommendations to self-driving cars. But here’s the issue: we don’t even have clear UX standards for AI.
💡 If we don’t measure UX in AI properly, we risk building products that are functional but untrustworthy, accurate but unethical, powerful but frustrating to use.
We dive into:
〜 Why traditional UX metrics fail in AI-driven products
〜 The Amazon hiring AI scandal—how biased algorithms create bad UX
〜 The problem of explainability—why we often don’t understand AI decisions
〜 The future of AI UX standards—should there be a universal AI UX certification?
📌 Core Question: Can we trust AI to deliver great user experiences if we don’t even know how to measure them?
Let’s explore what’s missing in AI UX—and what needs to change.
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