On September 26, SibIASA plans to take part in the webinar “Künstliche Intelligenz datenschutzkonform entwickeln” (“Developing artificial intelligence in compliance with data protection rules”).
When storing and processing data, data protection should always come first. At the same time, data analysis is essential in both research and countless business processes. In order to make confidential or personal data usable, it is usually anonymous, but anonymous data is in no way secure. Information about individual data units is easy to obtain from completely anonymous data. However, there is a method that also provides a high level of data protection and benefits for AI algorithms: differential privacy. The webinar will discuss how this mathematical principle works and how it is successfully used in Gradient Zero on the DQ0 platform.
Key questions of the webinar:
- Why AI is a special challenge for data protection
- Common methods (anonymization) and their limitations
- The principle of differential privacy
- How differential privacy works for AI
- Case Study: Safely Handling Health Data with KI and DQ0
Jona Boddinghaus, founder of Gradient Zero (G0).
After working in the industry for several years, he founded his own company, which he sold in 2014. Prior to G0, he held various leadership positions in AI companies.