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The Significance of AI System Cards with Bryan McGowan and Christopher Jambor, Trusted AI Team at KPMG | EP 08

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Manage episode 461360126 series 3603279
תוכן מסופק על ידי Responsible AI Institute. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Responsible AI Institute או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

In this episode, Patrick speaks with Brian McGowan and Chris Jambor from KPMG about the importance of responsible AI practices. They discuss the limitations of AI models, the development and significance of AI system cards, and how these tools can help mitigate risks associated with AI technologies. The conversation emphasizes the need for a structured approach to AI governance and the role of transparency and accountability in building trust in AI systems.
Takeaways

  • AI tools are evolving rapidly and need proper guardrails.
  • AI system cards provide a structured way to assess AI systems.
  • Transparency and explainability are crucial in AI governance.
  • System cards help improve AI literacy in the workplace.
  • A trust score helps users understand AI system performance.
  • AI governance must be scalable and adaptable to technology changes.
  • Robust testing and validation are key to responsible AI.

Learn more at:
https://kpmg.com/xx/en/what-we-do/services/kpmg-trusted-ai.html
Bryan McGowan is a Principal in the KPMG Advisory practice and leader of US Trusted AI for Consulting. In this role, Bryan continues to expand his passion of leveraging technology to drive efficiency, enhance insights, and improve results. Trusted AI combines deep industry expertise across the firm’s Risk Services, Lighthouse, and Cyber businesses with modern technical skills to help business leaders harness the power of AI to accelerate value in a trusted manner—from strategy and design through to implementation and ongoing operations. Bryan also leads the Trusted AI go-to-market efforts for the Risk Services business and co-developed the firm’s Risk Intelligence product suite to help identify, manage, and quantify risks across the enterprise. His primary focus areas are business process improvement, control design and automation, and managing risks associated with emerging technologies. Bryan has over 20 years’ experience running large, complex projects across a variety of industries. This includes supporting clients on their automation and analytics journey for the better part of the last decade—designing and developing bots, RPA, initial AI/ML models, and more.
Chris is a member of the KPMG AI & Digital Innovation Group's Trusted AI Team with a specialized focus on AI literacy and the responsible & ethical uses of AI. Before joining the Trusted AI team, Chris was an AI Strategy Consultant & Analytics Engineer working in industries such as technology, entertainment, healthcare, pharmaceuticals, marketing/advertising, higher education, and cybersecurity.

Support the show

Visit our website at responsible.ai

  continue reading

16 פרקים

Artwork
iconשתפו
 
Manage episode 461360126 series 3603279
תוכן מסופק על ידי Responsible AI Institute. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Responsible AI Institute או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

In this episode, Patrick speaks with Brian McGowan and Chris Jambor from KPMG about the importance of responsible AI practices. They discuss the limitations of AI models, the development and significance of AI system cards, and how these tools can help mitigate risks associated with AI technologies. The conversation emphasizes the need for a structured approach to AI governance and the role of transparency and accountability in building trust in AI systems.
Takeaways

  • AI tools are evolving rapidly and need proper guardrails.
  • AI system cards provide a structured way to assess AI systems.
  • Transparency and explainability are crucial in AI governance.
  • System cards help improve AI literacy in the workplace.
  • A trust score helps users understand AI system performance.
  • AI governance must be scalable and adaptable to technology changes.
  • Robust testing and validation are key to responsible AI.

Learn more at:
https://kpmg.com/xx/en/what-we-do/services/kpmg-trusted-ai.html
Bryan McGowan is a Principal in the KPMG Advisory practice and leader of US Trusted AI for Consulting. In this role, Bryan continues to expand his passion of leveraging technology to drive efficiency, enhance insights, and improve results. Trusted AI combines deep industry expertise across the firm’s Risk Services, Lighthouse, and Cyber businesses with modern technical skills to help business leaders harness the power of AI to accelerate value in a trusted manner—from strategy and design through to implementation and ongoing operations. Bryan also leads the Trusted AI go-to-market efforts for the Risk Services business and co-developed the firm’s Risk Intelligence product suite to help identify, manage, and quantify risks across the enterprise. His primary focus areas are business process improvement, control design and automation, and managing risks associated with emerging technologies. Bryan has over 20 years’ experience running large, complex projects across a variety of industries. This includes supporting clients on their automation and analytics journey for the better part of the last decade—designing and developing bots, RPA, initial AI/ML models, and more.
Chris is a member of the KPMG AI & Digital Innovation Group's Trusted AI Team with a specialized focus on AI literacy and the responsible & ethical uses of AI. Before joining the Trusted AI team, Chris was an AI Strategy Consultant & Analytics Engineer working in industries such as technology, entertainment, healthcare, pharmaceuticals, marketing/advertising, higher education, and cybersecurity.

Support the show

Visit our website at responsible.ai

  continue reading

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