The Difficulties and Limitations of Implementing AI at the CFTC and Beyond
Featured Speaker: Dr. Tamara Roust, Chief Data Officer, US Commodity Futures Trading Commission (CFTC)
Most institutions necessarily institute artificial intelligence (AI) to solve individual use cases in their enterprise, a form of “first-generation AI”. A chess program, speech recognition, an algorithm to rapidly buy and sell financial products. These are straightforward applications of structured data problems. One of the chief difficulties is in getting understanding in the enterprise beyond these structured data cases, particularly in the domain of limited budgets. Once the “first generation AI” is implemented, successfully or not, the next step is more lateral movement – development of more standalone cases, rather than layering and refactoring to produce additional complexity, the neural nets and deep learning AI problem sets. Join this interactive session to learn some of the difficulties associated with implementing AI as well as the difficulties moving from “first generation” to “second generation” AI in order to achieve business process improvement by modifying data architecture to reflect how data is actually used.
- 11:30-12:30pm: Featured Presentation
- 12:30-1:00pm: Your Q&A and interaction
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