Why AI fails: Overcoming AI challenges (sponsored by IBM)
We know artificial intelligence will be the most disruptive class of technologies over the next decade, fueled by near-endless amounts of data and unprecedented advances in deep learning. However, Brittany Bogle explains, for AI to thrive, and for businesses to reap its benefits, it’s imperative for organizations to realize there will be failures along the way and learn how to close the gap and address some of the major AI challenges, like trust, talent, and data.
This session is sponsored by IBM.
What you'll learn
- Learn how to address the AI challenges of the future
Brittany Bogle is a senior data scientist and machine learning engineer on the science elite team at IBM, where she collaborates with clients to execute data science use cases across a range of industries, including healthcare, finance, hospitality, and manufacturing. She also aggregates lessons from experiences and shares with executive and technical audiences. Brittany’s expertise in data science spans descriptive analytics, predictive analytics, and decision optimization, with an emphasis on using these tools in healthcare settings. Previously, she completed a fellowship at the University of North Carolina, where she collaborated directly with emergency medicine physicians, cardiologists, and epidemiology researchers. She built predictive models for cardiac arrest, established and implemented natural language processing (NLP) methodology to emulate manual adjudication of myocardial infarction and chronic heart failure, and she’s a coinvestigator on a pilot study to assess the effectiveness of AED-equipped drone delivery and optimize drone placement strategies. She holds a bachelor of science in industrial engineering from the University of Arkansas, an MS and PhD in industrial engineering and management sciences, and a master’s in public health from Northwestern University.
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