The Perils of Manually Labeling Data for Machine Learning Models

“What if we’re wrong about that?” This is a question that every data scientist will ask themselves at hopefully regular points in their career. This week, Jon Krohn speaks with Watchful CEO Shayan Mohanty about ways to rethink the term and connotations of bias in data. Together, they discuss the pitfalls of data analysis when bias comes into the equation (spoiler alert: it always does), the importance of the Chomsky hierarchy in data management, and the value of simulation engines in returning real-time results to users.