Machine learning is an established discipline and tool set that has proven extremely powerful across a wide range of applications. This power has brought with it a number of challenges and various types of incidents -- many of them related directly to the methods used to build the models themselves. Considerations like model robustness, transparency and fairness are critical for risk management and organizational adoption of machine learning. Moreover, many jurisdictions are increasing their regulatory requirements in these areas, adding legal urgency to ethical ML questions.

Join Patrick Hall as he discusses AI incidents, the nascent NIST AI risk management framework and how PiML can streamline your journey to higher quality machine learning implementations.

Patrick Hall
Principal Scientist, BNH.AI
Visiting Faculty at the George Washington University School of Business

January 20, 2023

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