19 min

Episode 42: The Growing Importance of Data Governance in an AI-Driven World The Data Governance 360 Podcast

    • Technology

In this podcast episode titled "The Growing Importance of Data Governance in an AI-Driven World," George Tziahanas, VP of Compliance at Archive 360, interviews Michael Rasmussen, an analyst and expert in governance, risk, and compliance (GRC). They discuss the role of data governance in the context of AI and analytics, as well as the regulatory landscape surrounding AI. Rasmussen emphasizes that data governance is the foundation for AI model governance and risk management. He highlights the risks associated with the uncontrolled use of AI, such as legal liability and exposure of sensitive information. Rasmussen also explains that data governance ensures data quality, security, and compliance, which are crucial for effective AI and analytics. He mentions the EU AI Act as an example of AI-specific regulation and discusses its requirements, including data quality, protection measures, and adherence to ethical standards. Zahanis and Rasmussen also stress the importance of trust and governance in data and AI systems, and they recommend organizations to approach data governance and AI governance in a way that enhances integrity and trust.

In this podcast episode titled "The Growing Importance of Data Governance in an AI-Driven World," George Tziahanas, VP of Compliance at Archive 360, interviews Michael Rasmussen, an analyst and expert in governance, risk, and compliance (GRC). They discuss the role of data governance in the context of AI and analytics, as well as the regulatory landscape surrounding AI. Rasmussen emphasizes that data governance is the foundation for AI model governance and risk management. He highlights the risks associated with the uncontrolled use of AI, such as legal liability and exposure of sensitive information. Rasmussen also explains that data governance ensures data quality, security, and compliance, which are crucial for effective AI and analytics. He mentions the EU AI Act as an example of AI-specific regulation and discusses its requirements, including data quality, protection measures, and adherence to ethical standards. Zahanis and Rasmussen also stress the importance of trust and governance in data and AI systems, and they recommend organizations to approach data governance and AI governance in a way that enhances integrity and trust.

19 min

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