Explainable AI: Transparency and Trust in Artificial Intelligence скачать в хорошем качестве

Explainable AI: Transparency and Trust in Artificial Intelligence

Descript Referral Link: https://get.descript.com/968yizg2t4r3 Explore the world of Explainable AI (XAI) and discover how it’s revolutionizing the way we understand and trust artificial intelligence. This episode dives into the black box problem, showcasing techniques like LIME and SHAP that bring transparency to AI decision-making. 💡 What You’ll Learn: What is the black box problem in AI? How techniques like LIME and SHAP enhance explainability The balance between accuracy and explainability in AI systems Real-world examples from healthcare, finance, and telecommunications Ethical considerations and the future of XAI 📌 Timestamps: 00:00 Introduction to Explainable AI (XAI) 00:44 Understanding the Black Box Problem 02:37 Techniques for Explainable AI 03:53 Challenges in Explainable AI 05:00 Real-World Applications of XAI 07:10 Ethical Considerations and Future Directions 11:13 The Future of XAI and Its Impact 12:49 Conclusion and Final Thoughts 🎥 Join us to understand how Explainable AI is building trust and accountability in AI systems worldwide. More from Ian Ochieng: 🌐 Website: ianochiengai.substack.com 📺 YouTube: Ian Ochieng AI 🐦 Twitter: @IanOchiengAI 📸 Instagram: @IanOchiengAI