Fleur Levitz - The History of Data: Classical Foundations to Guide AI Use Cases
Bio:
Fleur Levitz is a NYC-based AI Governance SME and Data Product Owner with success as a leader in data governance and privacy operations for Fortune 1000 companies. She is part of the first cohort of AI Governance Professionals trained by the IAPP organization, as well as an AI Governance Professional certification practice exam writer and a Certified Information Privacy Professional/US Laws.
Summary:
In this insightful talk, Fleur Levitz, a principal of FDL Consulting NYC, shares her expertise on the history of data and its classical management foundations that can guide AI use cases today and tomorrow. With a background in New York City as an AI and data governance expert, independent consultant, and data coach, Levitz advises senior stakeholders and government officials on optimizing their data and AI governance practices. Her journey from advertising to a career on Wall Street, including roles at Morgan Stanley, JP Morgan, and as a Management Consultant in data practices for IBM, has shaped her into a futurist optimistic about the promises of technology.
Key Points:
The importance of historical data management practices in guiding AI use cases.
Levitz's background in advertising, Wall Street, and as a Management Consultant for IBM.
The role of data governance in responding to regulations and organizing data records.
The need for a new language and framework to leverage AI technologies effectively.
Historical references to data organization and rationalization practices over the past several hundred years.
The binomial naming system by Carl Linnaeus as an example of early efforts to standardize data classification.