Nowadays, we have unprecedented access to data, plus the computing power and advanced algorithms to find correlations. We look at a cautionary case study of a cancer center that embarked on an ambitious plan to use AI to eradicate cancer. When AI is being asked to make decisions with significant consequences, such as life and death healthcare recommendations, it needs to be trustworthy. But if you don't follow best practices, if you don't include the knowledge of subject matter experts, and if you don't enforce business rules, your AI project will not be successful. In this latest Data Science Central podcast, learn four AI governance practices that can help you achieve AI success.
Colin Priest, VP of AI Strategy - DataRobot
Sean Welch, Host and Producer - Data Science Central