In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Black Box, Explainable AI (XAI), Interpretable AI, explain how these terms relate to AI and why it's important to know about them.

📖 Learn about Black Box Technology 📦: Kathleen and Ron will unravel the mystery behind Black Box technology, explaining its connection to deep learning in the realm of artificial intelligence. 🧐🔍

🔍 Unpacking Explainable AI (XAI) & Interpretable AI: Ever wondered how AI can become more transparent and understandable? Kathleen and Ron break down the concepts of XAI and Interpretable AI, explain why providing verifiable explanations of how machine learning systems, especially the so-called black box algorithms, make decisions and keep humans in the loop is important, an what it means for you at your organization. 🧠💬

Show Notes:

• FREE Intro to CPMAI mini course
• The Steps for a Machine Learning Project
• CPMAI Training and Certification
• AI Glossary
• Top 10 Ethical Considerations for AI Projects
• AI Glossary Series - DevOps, Machine Learning Operations (ML Ops)
• AI Glossary Series - Data Preparation, Data Cleaning, Data Splitting, Data Multiplication, Data Transformation
• AI Glossary Series - Data Augmentation, Data Labeling, Bounding box, Sensor fusion
• AI Glossary Series - Data, Dataset, Big Data, DIKUW Pyramid
• AI Glossary Series - V’s of Big Data, Data Volume, Exabyte / Petabyte / Yottabyte / Zettabyte, Data Variety, Data Velocity, Data Veracity
• AI Glossary Series - Machine Learning, Algorithm, Model
• Glossary Series: Machine Learning Approaches: Supervised Learning, Unsupervised Learning, Reinforcement Learning
• Glossary Series: Classification & Classifier, Binary Classifier, Multiclass Classifier, Decision Boundary