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Michael Krigsman에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Michael Krigsman 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Top Data Scientists Explain Bad Data, Poisoned Datasets, and Other AI Killers | CXOTalk #896

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Manage episode 512678674 series 1431021
Michael Krigsman에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Michael Krigsman 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Is your AI built on quicksand? Learn how bad data, poisoned datasets, and deep fakes threaten your AI systems, and what to do about it.

In this episode of CXOTalk (#896), AI luminaries Dr. David Bray and Dr. Anthony Scriffignano reveal the hidden dangers lurking in your AI foundations. They share practical strategies for building trustworthy AI systems and escaping the "AI quicksand" that traps countless organizations.

🎯 KEY TAKEAWAYS:

  • The Five Ms framework for identifying AI failures before they scale
  • Why red teams are essential for AI risk management
  • How nation-states are actively poisoning AI training data
  • Critical questions every leader must ask about their AI initiatives
  • The future of specialized AI models vs. mega LLMs

🔷 Show notes and resources: https://www.cxotalk.com/episode/escape-ai-quicksand-data-misuse-misadventures-and-mal-intent

🔷 Newsletter: www.cxotalk.com/subscribe

🔷 LinkedIn: www.linkedin.com/company/cxotalk

🔷 Twitter: twitter.com/cxotalk

00:00 🤖 Understanding AI Quicksand and the Challenges of Data

02:16 ⚠️ The Five Ms of AI Risks and Practical Examples

07:12 💡 The Disconnect in AI Adoption and the Importance of Purpose

09:46 🤖 The Challenges and Risks of Generative AI

14:28 ⚖️ Ethical and Intellectual Property Concerns in AI

16:30 🛡️ Responsibility and Oversight in Ethical AI

20:22 ⚖️ Liability and Critical Thinking in AI Services

22:12 📜 AI Regulation and Consumer Advocacy

25:55 🤖 Future Directions in AI Development

30:59 🤖 Exploring AI's Potential and Limitations

33:03 🧪 Data Poisoning and Its Implications

40:07 ⚠️ Addressing AI Risks and Perception of Reality

41:38 📊 The Evolution of Data Analysis and Critical Thinking

44:36 🧠 Teaching Critical Thinking and AI Critique

46:36 🤖 Embodied AI, Data Misuse, and Global AI Perspectives

50:57 🤖 The Evolution of Work and AI's Role

52:59 🌟 AI's Positive Impact on Healthcare and Society

56:23 🌈 Hope and Resilience in the Age of AI

#AI #ArtificialIntelligence #DataScience #AIEthics #MachineLearning #DataPoisoning #GenerativeAI #EnterpriseAI #AIStrategy #DigitalTransformation #CyberSecurity #AIRegulation #FutureOfWork #TechLeadership #CXOTalk

  continue reading

543 에피소드

Artwork
icon공유
 
Manage episode 512678674 series 1431021
Michael Krigsman에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Michael Krigsman 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Is your AI built on quicksand? Learn how bad data, poisoned datasets, and deep fakes threaten your AI systems, and what to do about it.

In this episode of CXOTalk (#896), AI luminaries Dr. David Bray and Dr. Anthony Scriffignano reveal the hidden dangers lurking in your AI foundations. They share practical strategies for building trustworthy AI systems and escaping the "AI quicksand" that traps countless organizations.

🎯 KEY TAKEAWAYS:

  • The Five Ms framework for identifying AI failures before they scale
  • Why red teams are essential for AI risk management
  • How nation-states are actively poisoning AI training data
  • Critical questions every leader must ask about their AI initiatives
  • The future of specialized AI models vs. mega LLMs

🔷 Show notes and resources: https://www.cxotalk.com/episode/escape-ai-quicksand-data-misuse-misadventures-and-mal-intent

🔷 Newsletter: www.cxotalk.com/subscribe

🔷 LinkedIn: www.linkedin.com/company/cxotalk

🔷 Twitter: twitter.com/cxotalk

00:00 🤖 Understanding AI Quicksand and the Challenges of Data

02:16 ⚠️ The Five Ms of AI Risks and Practical Examples

07:12 💡 The Disconnect in AI Adoption and the Importance of Purpose

09:46 🤖 The Challenges and Risks of Generative AI

14:28 ⚖️ Ethical and Intellectual Property Concerns in AI

16:30 🛡️ Responsibility and Oversight in Ethical AI

20:22 ⚖️ Liability and Critical Thinking in AI Services

22:12 📜 AI Regulation and Consumer Advocacy

25:55 🤖 Future Directions in AI Development

30:59 🤖 Exploring AI's Potential and Limitations

33:03 🧪 Data Poisoning and Its Implications

40:07 ⚠️ Addressing AI Risks and Perception of Reality

41:38 📊 The Evolution of Data Analysis and Critical Thinking

44:36 🧠 Teaching Critical Thinking and AI Critique

46:36 🤖 Embodied AI, Data Misuse, and Global AI Perspectives

50:57 🤖 The Evolution of Work and AI's Role

52:59 🌟 AI's Positive Impact on Healthcare and Society

56:23 🌈 Hope and Resilience in the Age of AI

#AI #ArtificialIntelligence #DataScience #AIEthics #MachineLearning #DataPoisoning #GenerativeAI #EnterpriseAI #AIStrategy #DigitalTransformation #CyberSecurity #AIRegulation #FutureOfWork #TechLeadership #CXOTalk

  continue reading

543 에피소드

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