As AI Blurs the Lines Between Real and Synthetic Data, Strong Governance Is Essential.
By Arun Sundararajan and Lauren Woodman
Once a niche tool used to address data gaps or safeguard privacy, synthetic data (artificially generated information that mimics real-world data) is transforming the use of artificial intelligence (AI) in many industries. It can fill data gaps, protect privacy and enable the testing of new scenarios, providing a scalable and cost-effective alternative when real-world data is limited or sensitive.
But as the proliferation of synthetic data expands, the line between real and artificial blurs, threatening trust, distorting knowledge and embedding systemic risks.
The opportunities for using synthetic data are vast, but success will rely on strong governance, inclusive and high-quality data practices and transparent collaboration among developers, scientists, policy-makers and organizational leaders.
Read the full World Economic Forum article.
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Arun Sundararajan is Harold Price Professor of Entrepreneurship, Director, Fubon Center for Technology, Business and Innovation, Professor of Technology, Operations and Statistics and Undergraduate Faculty Advisor, Entrepreneurship