Algorithmic Transparency & Data Integrity in AI: Dr. Jay Lee on Ai Today with Dr. Allen Badeau

🔍 Welcome to Ai Today, where Dr. Allen Badeau explores the groundbreaking potential and ethical challenges of Artificial Intelligence. In this episode, Dr. Badeau is joined by Dr. Jay Lee, a visionary in Industrial AI and the Clark Distinguished Chair at the University of Maryland, to discuss algorithmic transparency, data bias, and ensuring data integrity in AI systems.

Dr. Lee shares his expertise on how engineers and businesses can build trustworthy AI models by addressing bad data, enabling algorithm validation, and ensuring a sustainable lifecycle for AI tools.

🌟 In This Episode:
What is algorithmic transparency, and why is it essential?
How bad data (the 3B problem: broken, bad baseline, and poor background) derails AI models.
Why businesses must invest in making their data AI-ready.
Dr. Lee’s 3T framework: Transparency, Traceability, and Transferability in AI systems.
Practical strategies for building reliable and ethical AI for real-world applications.
🎯 Key Takeaway: Good data drives great AI. Without proper data preparation and clear purpose, even the best algorithms will fail to deliver meaningful insights.

⏰ Timestamps:
0:00 - Introduction to Dr. Jay Lee and the importance of algorithmic integrity
3:20 - The role of transparency, traceability, and transferability in AI development
7:10 - Why bad data leads to bad models: The 3B problem
11:40 - Making data AI-ready: Purpose, process, and problem-solving
15:15 - How to evaluate the reliability of commercial AI tools

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📚 About Dr. Jay Lee:
Dr. Jay Lee is a world-renowned expert in Industrial AI and the Director of the Industrial AI Center at the University of Maryland. Learn more about his cutting-edge work at UMD Mechanical Engineering.

🌟Hashtags:
#AIIntegrity #AlgorithmicTransparency #AllenBadeau #IndustrialAI #DataBias #JayLee #AIEthics #DataIntegrity #AiTodayPodcast

💬 Your Turn: What challenges have you faced with AI tools or data bias? Let us know in the comments! Don’t forget to like, subscribe, and share for more insightful dis