For years public concern about technological risk has focused on the misuse of personal data. But as companies embed more and more AI in products and processes, attention is shifting to the potential for bad or biased decisions by algorithms — particularly the complex, evolving kind that diagnose cancers, drive cars, or approve loans. Inevitably, many governments will feel regulation is essential to protect consumers from that risk. In this session, we discuss the moves regulators are most likely to make and the main challenges businesses need to consider as they adopt and integrate AI in the context of three main areas. The first is ensuring fairness, the second is transparency and explainability, and the third is governance.
Ahmad Khan is the Head of AI/ML Strategy at Snowflake where he helps customers optimize their ML workloads on Snowflake. He also works closely with the Snowflake product team to help define the ML feature set within Snowflake based on the voice of the customer. Prior to Snowflake, Ahmad spent over 4 years at AWS where he focused on the AWS; stack of ML services and was involved in early proof of concepts for AWS SageMaker. Ahmad holds a Masters in Electrical & Computer Engineering from University of Southern California.
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