AI Generated Synthetic Data in Policy Applications

Jiri Hradec, Margherita Di Leo and Alexander Kotsev ()
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Jiri Hradec: European Commission - JRC, https://joint-research-centre.ec.europa.eu/index_en
Alexander Kotsev: European Commission - JRC, https://joint-research-centre.ec.europa.eu/index_en

No JRC138521, JRC Research Reports from Joint Research Centre

Abstract: This policy brief explores the potential of three distinct levels of data to inform policy-making: original datasets, synthetic replicas, and fully AI-generated data. Original datasets: These are the foundation of data-driven policy-making, providing authentic insights into real-world phenomena. However, original datasets often come with limitations, including privacy concerns, accessibility issues, and utility constraints. Synthetic replicas: To address these limitations, synthetic replicas of original datasets can be created. These replicas mimic the statistical properties of the original data, offering a privacy-safe alternative for analysis and research. Synthetic data can facilitate the integration of siloed data, enhancing data-driven decision-making without compromising sensitive information. Fully AI-generated data: The latest advancement in data synthesis is the use of artificial intelligence (AI) to generate fully synthetic data. This technology has the potential to revolutionize policy-making by providing detailed and context-rich data that can support groundbreaking research and product development. AI-generated data can be particularly valuable in sectors like healthcare and AI, where data privacy concerns are paramount. However, the adoption of synthetic and AI-generated data also introduces challenges, including data quality, biases, and ethical considerations. To address these challenges, rigorous quality controls and robust governance frameworks are necessary. This policy brief advocates for a unified approach towards the responsible use and governance of AI-generated data, ensuring its effective integration into policy-making frameworks within the European Union. This approach promises not only to enhance the precision of policy outcomes but also to democratize data access, fostering a more inclusive and insightful policy-making process. By recognizing the distinct characteristics and potential of each level of data, policymakers can harness the power of AI-generated data to inform more effective and responsible decision-making.

Date: 2024-07
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