AI Knowhow Explainable AI vs. Understandable AI
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Nov 18, 2024 In this enlightening discussion, Dom Nicastro, Editor-in-Chief at CMSWire, explores AI's transformative role in customer experience and journalism. He emphasizes the vital differences between explainable AI, focused on technical compliance, and understandable AI, which fosters trust with users. Nicastro also highlights how AI empowers frontline agents and aids journalists, enhancing their work instead of replacing it. Additionally, the episode features a segment on AI's impressive capabilities in fraud detection, showcasing its potential for good in real-world applications.
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AI Catching Billions in Fraud
- U.S. Treasury used AI and human oversight to detect over $4 billion in 2024 fraud.
- This showcases AI's potential for massive impact in fraud detection across huge payment volumes.
Explainable vs Understandable AI
- Explainable AI provides technical reasons for a model's decision, focusing on the "why" behind the prediction.
- Understandable AI ensures humans grasp what the model's output means in context, enhancing comprehension.
Trust through Explainability
- Trust in AI depends on clarity about why decisions and predictions occur.
- Even top AI scientists only approximate decision reasons; ongoing research explores neural networks deeply.