MINIMIZING THE DOWNSIDE RISKS OF AI AND MACHINE LEARNING
- Published: 29 April 2019
YOGESH MALHOTRA | Chief Scientist and Executive Director, Global Risk Management Network, LLC
This article discusses how model risk management in operationalizing machine learning or algorithm deployment can be applied in national systemic and cyber risk management projects such as Project Maven.
After an introduction about why model risk management is crucial to robust AI, ML, deep learning, and neural networks deployment, the article presents a knowledge management framework for model risk management to advance beyond ‘AI automation’ to ‘AI augmentation.’