This paper introduces the AI Pentad model, comprising humans/organizations, algorithms, data, computing, and energy, as a framework for AI regulation. It also presents the CHARME²D Model to link the AI Pentad with regulatory enablers like registration, monitoring, and enforcement. The paper assesses AI regulatory efforts in the EU, China, UAE, UK, and US using the CHARME²D model, highlighting strengths and weaknesses.
This commentary discusses the EU AI Act and its potential impact on AI regulation globally. It highlights the importance of balancing innovation with safety and security, particularly in sensitive sectors like healthcare. The author, Prof. Mérouane Debbah of TII, welcomes the EU's emphasis on transparency and the role of open-source models. Why it matters: The EU AI Act is likely to influence AI policy in the Middle East, prompting a need for regional alignment and consideration of its implications for research and development.
Researchers introduce a new task for generating question-passage pairs to aid in developing regulatory question-answering (QA) systems. The ObliQA dataset, comprising 27,869 questions from Abu Dhabi Global Markets (ADGM) financial regulations, is presented. A baseline Regulatory Information Retrieval and Answer Generation (RIRAG) system is designed and evaluated using the RePASs metric.