System Architecture for Compliance and Audit of AI

 System Architecture for Compliance and Audit of AI

The focal point of AI regulation is not necessarily deep learning neural network technology. However, generative AI is one of the main problems. It relies mainly on large machine-learning models that are challenging to explain and change if necessary. The regulatory provisions, on the other hand, should be highly explainable, consistent, and transparent. A careful reader of current documents outlining what needs to be done will find areas that need clarification. Converting the letter of the law to system designs capable of in-depth AI system surveillance, legal benchmarking, or audit is, in itself, a fascinating topic that will surely energize the research community. However, transparent regulatory systems overseeing and benchmarking neural AIs architectures will probably require input from several branches of computer science and AI. We will need to formulate data structures and "engines" that utilize classical, fuzzy, or non-monotonic logic, knowledge representation, and search algorithms, to mention only a few. 

https://www.holisticai.com/blog/china-ai-regulation

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