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Deciphering Privacy in the Age of AI: An Expert Discussion
Manage episode 376313799 series 3486243
Giovanni Cherubin and Ahmed Salem join Nic Fillingham and Wendy Zenone on this week's episode of The BlueHat Podcast. Giovanni is a Senior Researcher in Machine Learning and Security at Microsoft Research Cambridge, and Ahmed is a researcher in Confidential Computing at the Microsoft Research lab in Cambridge, UK. They're both interested in artificial intelligence and are researching the privacy, security, fairness, and accountability risks of the different machine learning settings. In this episode, they discuss how to identify and address privacy threats in machine learning models, the connection between privacy and information leakage, and how privacy is perceived in academia and industry.
In This Episode You Will Learn:
- Algorithmic procedures for describing threats and attacks
- The rapid growth of machine learning research in attacks and defense
- The framework for fostering collaboration and understanding within the field
Some Questions We Ask:
- What are the main threats you are currently focused on?
- Who will benefit from this research besides academics and researchers?
- Can you explain the concept of privacy as it relates to information leakage?
Resources:
View Giovanni Cherubin on LinkedIn
View Nic Fillingham on LinkedIn
Discover and follow other Microsoft podcasts at microsoft.com/podcasts
Hosted on Acast. See acast.com/privacy for more information.
37 episodes
Manage episode 376313799 series 3486243
Giovanni Cherubin and Ahmed Salem join Nic Fillingham and Wendy Zenone on this week's episode of The BlueHat Podcast. Giovanni is a Senior Researcher in Machine Learning and Security at Microsoft Research Cambridge, and Ahmed is a researcher in Confidential Computing at the Microsoft Research lab in Cambridge, UK. They're both interested in artificial intelligence and are researching the privacy, security, fairness, and accountability risks of the different machine learning settings. In this episode, they discuss how to identify and address privacy threats in machine learning models, the connection between privacy and information leakage, and how privacy is perceived in academia and industry.
In This Episode You Will Learn:
- Algorithmic procedures for describing threats and attacks
- The rapid growth of machine learning research in attacks and defense
- The framework for fostering collaboration and understanding within the field
Some Questions We Ask:
- What are the main threats you are currently focused on?
- Who will benefit from this research besides academics and researchers?
- Can you explain the concept of privacy as it relates to information leakage?
Resources:
View Giovanni Cherubin on LinkedIn
View Nic Fillingham on LinkedIn
Discover and follow other Microsoft podcasts at microsoft.com/podcasts
Hosted on Acast. See acast.com/privacy for more information.
37 episodes
All episodes
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