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Navigating AI Safety and Security Challenges with Yonatan Zunger
Manage episode 432930696 series 3486243
Yonatan Zunger, CVP of AI Safety & Security at Microsoft joins Nic Fillingham and Wendy Zenone on this week's episode of The BlueHat Podcast. Yonatan explains the distinction between generative and predictive AI, noting that while predictive AI excels in classification and recommendation, generative AI focuses on summarizing and role-playing. He highlights how generative AI's ability to process natural language and role-play has vast potential, though its applications are still emerging. He contrasts this with predictive AI's strength in handling large datasets for specific tasks. Yonatan emphasizes the importance of ethical considerations in AI development, stressing the need for continuous safety engineering and diverse perspectives to anticipate and mitigate potential failures. He provides examples of AI's positive and negative uses, illustrating the importance of designing systems that account for various scenarios and potential misuses.
In This Episode You Will Learn:
- How predictive AI anticipates outcomes based on historical data
- The difficulties and strategies involved in making AI systems safe and secure from misuse
- How role-playing exercises help developers understand the behavior of AI systems
Some Questions We Ask:
- What distinguishes predictive AI from generative AI?
- Can generative AI be used to improve decision-making processes?
- What is the role of unit testing and test cases in policy and AI system development?
Resources:
View Yonatan Zunger on LinkedIn
View Nic Fillingham on LinkedIn
Related Microsoft Podcasts:
Discover and follow other Microsoft podcasts at microsoft.com/podcasts
37 tập
Manage episode 432930696 series 3486243
Yonatan Zunger, CVP of AI Safety & Security at Microsoft joins Nic Fillingham and Wendy Zenone on this week's episode of The BlueHat Podcast. Yonatan explains the distinction between generative and predictive AI, noting that while predictive AI excels in classification and recommendation, generative AI focuses on summarizing and role-playing. He highlights how generative AI's ability to process natural language and role-play has vast potential, though its applications are still emerging. He contrasts this with predictive AI's strength in handling large datasets for specific tasks. Yonatan emphasizes the importance of ethical considerations in AI development, stressing the need for continuous safety engineering and diverse perspectives to anticipate and mitigate potential failures. He provides examples of AI's positive and negative uses, illustrating the importance of designing systems that account for various scenarios and potential misuses.
In This Episode You Will Learn:
- How predictive AI anticipates outcomes based on historical data
- The difficulties and strategies involved in making AI systems safe and secure from misuse
- How role-playing exercises help developers understand the behavior of AI systems
Some Questions We Ask:
- What distinguishes predictive AI from generative AI?
- Can generative AI be used to improve decision-making processes?
- What is the role of unit testing and test cases in policy and AI system development?
Resources:
View Yonatan Zunger on LinkedIn
View Nic Fillingham on LinkedIn
Related Microsoft Podcasts:
Discover and follow other Microsoft podcasts at microsoft.com/podcasts
37 tập
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