NAIC-ISAO’s Michael Thiessmeier Talks MLOps, Data Governance, and AI Ethics
Integrating artificial intelligence into cybersecurity requires a robust approach. Many companies are looking for advanced AI solutions but struggle to implement basic cybersecurity practices, such as asset management and vulnerability remediation, said Michael Thiessmeier, executive director of ISAO, the U.S. National Agency for AI and Cybersecurity. Without a solid foundation, AI deployment becomes risky and ineffective, he said.
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Machine learning operations play a crucial role in securing AI deployments. According to Thiessmeier, MLOps ensures that changes to AI models and their environments occur in a controlled manner. This allows organizations to establish a baseline, which is essential for detecting anomalies.
But aligning AI deployment with ethical standards and governance remains a challenge, he said. “Most companies don’t understand what the assets are, but they also don’t understand what this data is. It all comes back to data governance first,” Thiessmeier said. “If we don’t have data governance defined, if we don’t understand where the data is, what its value is, what the classification is supposed to be, and if it only exists on paper but not in a computerized form that we can act on, how are we supposed to do anything else?”
In this video interview with Information Security Media Group at Black Hat 2024Thiessmeier also discussed:
- How deception technologies can play an important role in AI safety;
- The need to employ dynamic security configurations to disrupt attackers and improve productivity;
- The importance of dialogue between different stakeholders – including academia, industry and the public sector – for successful integration of AI.
Thiessmeier has over 20 years of experience in the technology field and is an expert in cybersecurity, artificial intelligence, cyber diplomacy and compliance. At NAIC-ISAO, he promotes international cooperation and develops strategies to leverage AI to improve cybersecurity.
