I gave a lecture at an Executive MBA course on the interactions between regulations and standards in AI, data, and digital technologies—both globally and in Australia. Here are the key takeaways.

• Technology does not exist in isolation. There are inputs to technology, such as data for AI, and there are domains where AI is applied—such as critical infrastructure and financial services—that are heavily regulated. AI can also be deployed in less regulated environments, but even in those cases, the specific use case can have broader implications, such as in ESG.
• Standards come in different forms. They range from management and governance standards to measurement and testing methods, as well as product standards that define performance and threshold requirements. These need to be considered differently.
• A key challenge in AI standards and regulation stems from the shift from technologies designed for specific problems to general-purpose AI. Compounding this is the fact that AI can be treated as monolithic software rather than a system composed of distinct components. These factors introduce unique regulatory and standardisation challenges.

I highlighted potential solutions to these challenges, including ongoing efforts in Australia to develop AI safety standards that are currently being established.

Dropbox slides (5 out of 60): https://www.dropbox.com/scl/fi/m7hm49igtvh310jmspog5/20250212-CKGSB-Enabling-Technologies-Ecosystems-and-Regulations-in-Oceania.pdf?rlkey=ljtydpi3nfyhuk1vfx24l0o01&dl=1