WASHINGTON (April 30, 2025)- According to TechTarget, “Data governance is a core component of an overall data management strategy.”
Data governance is the practice of setting internal standards—data policies—that apply to how data is gathered, stored, processed, and disposed of, is crucial to data integrity, usability and security.
While data valuation is described by Monda as, “the process of determining the monetary value of a dataset or collection of data.”But why are these definitions important to consider today?
Susan Ariel Aaronson is a research professor of international affairs, is also the director of the Digital Trade and Data Governance Hub and co-PI at the NSF Trustworthy AI Institute, TRAILS at the George Washington University. Her research focuses on AI governance, data governance, competitiveness in data-driven services such as XR, and AI and digital trade. Aaronson currently directs projects on governing data for generative AI, ensuring that data is globally accurate, complete, and representative and on AI protectionism.
Aaronson said, “There is no AI without data, yet only China has policies to create transparent data markets, to value data as an asset, and to ensure that it is seen as a factor of protection. China's leadership met last week to make those points. The US and EU, while describing AI as essential to economic growth, have limited policies on data.”
To speak with Dr. Susan Ariel Aaronson, please contact Media Relations Specialist Shannon Mitchell at shannon [dot] mitchell
gwu [dot] edu (shannon[dot]mitchell[at]gwu[dot]edu).
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