Mon. Dec 23rd, 2024
Privacy Preserving Artificial Intelligence: Training On Encrypted Data

In the era of artificial intelligence (AI) and big data, predictive models have become essential tools in a variety of industries, including healthcare, finance, and genomics. These models rely heavily on processing sensitive information, making data privacy a major concern. A key challenge is maximizing the usefulness of the data without compromising the confidentiality and integrity of the associated information. Achieving this balance is essential for the continued advancement and acceptance of AI technologies.

Jordan Frehley

Zama’s Machine Learning Technical Lead.

Collaboration and Open Source

Creating a robust dataset for training machine learning models is a big challenge. For example, AI technologies such as ChatGPT have developed by collecting huge amounts of data available on the Internet, but healthcare data cannot be collected so freely due to privacy concerns. Building a healthcare dataset requires integrating data from multiple sources across doctors, hospitals, and borders.