How Microsoft Scales Testing and Safety for Generative AI with Sarah Bird - #691 | The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

In this podcast episode, the risks and challenges in the development of generative AI are explored. The conversation emphasizes the need for a mental framework to understand these risks, including hallucinations and jailbreaks. The importance of effective communication through the AI interface and Microsoft's commitment to responsible AI are also highlighted. The episode discusses the importance of defense in depth in AI systems and the need for intervention mechanisms and comprehensive testing. Testing and evaluation, conveying the right expectations to users, and the role of red teaming are also discussed. The NIST AI risk management framework is introduced as a useful approach to address AI risks. The episode concludes by acknowledging the significant progress in responsible AI and safety through generative AI technology and the uncertainties and potential of the future of AI.

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How Microsoft Scales Testing and Safety for Generative AI with Sarah Bird - #691

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Microsoft's Commitment to Responsible AI and the Challenges of Generative AI

Risks and Challenges in Generative AI: Understanding and Addressing the Landscape

The Intersection of Model Capabilities, Security, and Fairness in AI Systems

Lessons Learned and Progress Made: Microsoft's Journey towards Responsible AI

Building Robust and Agile AI Systems with Defense in Depth

Automation and Human Judgment in Testing and Incident Interventions

Crafting User Expectations and Designing Effective Interfaces for AI Systems

Testing and Evaluation in AI Model Development: Publisher versus Consumer Perspectives

Testing AI Systems: Balancing Quality Metrics, Safety, and Adversarial Robustness

Red Teaming and Risk Management in AI Applications: Recommendations and Frameworks

The NIST AI Risk Management Framework and the Future of Testing and Safety for Generative AI Systems

The Exciting Potential of Generative AI in Responsible AI and Safety

The Future of AI: Adaptation, Uncertainty, and Durability in the Face of New Technology

How Microsoft Scales Testing and Safety for Generative AI with Sarah Bird - #691

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

00:00Microsoft's Commitment to Responsible AI and the Challenges of Generative AI

Microsoft's Commitment to Responsible AI and the Challenges of Generative AI

03:30Risks and Challenges in Generative AI: Understanding and Addressing the Landscape

Risks and Challenges in Generative AI: Understanding and Addressing the Landscape

08:11The Intersection of Model Capabilities, Security, and Fairness in AI Systems

The Intersection of Model Capabilities, Security, and Fairness in AI Systems

12:50Lessons Learned and Progress Made: Microsoft's Journey towards Responsible AI

Lessons Learned and Progress Made: Microsoft's Journey towards Responsible AI

17:27Building Robust and Agile AI Systems with Defense in Depth

Building Robust and Agile AI Systems with Defense in Depth

21:07Automation and Human Judgment in Testing and Incident Interventions

Automation and Human Judgment in Testing and Incident Interventions

26:34Crafting User Expectations and Designing Effective Interfaces for AI Systems

Crafting User Expectations and Designing Effective Interfaces for AI Systems

30:32Testing and Evaluation in AI Model Development: Publisher versus Consumer Perspectives

Testing and Evaluation in AI Model Development: Publisher versus Consumer Perspectives

34:46Testing AI Systems: Balancing Quality Metrics, Safety, and Adversarial Robustness

Testing AI Systems: Balancing Quality Metrics, Safety, and Adversarial Robustness

40:04Red Teaming and Risk Management in AI Applications: Recommendations and Frameworks

Red Teaming and Risk Management in AI Applications: Recommendations and Frameworks

44:00The NIST AI Risk Management Framework and the Future of Testing and Safety for Generative AI Systems

The NIST AI Risk Management Framework and the Future of Testing and Safety for Generative AI Systems

48:47The Exciting Potential of Generative AI in Responsible AI and Safety

The Exciting Potential of Generative AI in Responsible AI and Safety

54:08The Future of AI: Adaptation, Uncertainty, and Durability in the Face of New Technology

The Future of AI: Adaptation, Uncertainty, and Durability in the Face of New Technology