AI’s Best Friend: The Role of PETs in Data Use and Operationalizing Privacy

Moderator: Mark Smith, CIPP/C, CIPP/US, CIPM, Senior Manager, Privacy and Data Policy, Centre for Information Policy Leadership
Kristie Chon Flynn, Data Protection Officer, Google
Katie Skinner, Privacy Engineering Manager, Apple
Daniel Smullen, Principal Research Engineer, CableLabs

Privacy-enhancing technologies hold immense potential to help operationalize privacy by design and by default when developing artificial intelligence systems. PETs also enable broader beneficial sharing and use of data across different organizations and sectors to boost AI adoption. This panel will explore how PETs, such as federated learning, differential privacy, and homomorphic encryption, can both strengthen privacy protection and drive innovation in AI. The Centre for Information Policy Leadership will also share insights from its paper “PETs and PPTs in AI: Enabling Data Use and Operationalizing Privacy by Design and Default,” outlining how these technologies address privacy risks and create new opportunities in data sourcing, model training, security, and collaboration.

What you will learn:

• How PETs such as differential privacy, federated learning, and homomorphic encryption can enhance privacy and foster innovation, through real-world industry use cases.
• The key challenges organizations face in implementing these technologies and strategies for overcoming them, including insights into the evolving regulatory and ethical landscape. 
• What actionable steps can be taken to encourage widespread adoption of PETs and advance a more secure, trustworthy AI ecosystem.