Karin Schöfegger is a seasoned ML product manager who knows how to create successful AI/ML products and mitigate the risks involved. In this episode, she shares her insights about challenges in building AI products. Tune in to learn about:

1. How to align the business side and the data science side of product development
2. What's the difference between traditional software development and machine learning development
3. How to bring customer understanding into data science and engineering
4. What are the most common traps in data science
5. Why it's essential to work with realistic data instead of picture-perfect datasets
6. How to get buy-in from stakeholders for ethical AI