Data Protection in AI

This article discusses the challenges of data protection in artificial intelligence (AI) and the tools and methods that can be used to address these challenges.

The article is divided into three sections:

• Methods for reducing the need for training data
• Methods that uphold data protection without reducing the basic dataset
• Methods designed to avoid the black box issue

The article concludes by discussing the potential of these methods to improve data protection in AI.

For more information, please visit the following resources:

• The General Data Protection Regulation (GDPR)
• Data protection in AI – ENISA
• AI privacy tools – PrivacyTools.io