This paper introduces a Regulatory Knowledge Graph (RKG) for the Abu Dhabi Global Market (ADGM) regulations, constructed using language models and graph technologies. A portion of the regulations was manually tagged to train BERT-based models, which were then applied to the rest of the corpus. The resulting knowledge graph, stored in Neo4j, and code are open-sourced on GitHub to promote advancements in compliance automation.
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.
The Technology Innovation Institute (TII) and ASPIRE, in collaboration with the General Civil Aviation Authority (GCAA), are developing an Advanced Air Mobility (AAM) regulatory framework. TII is spearheading simulation-based regulatory models for airspace corridors, focusing on wind dynamics and flight safety, with trials underway at three pilot sites in Abu Dhabi. These efforts are laying the groundwork for the safe and scalable integration of autonomous air taxis and delivery drones. Why it matters: This initiative positions the UAE as a global leader in defining the technical and regulatory standards for urban air mobility, fostering innovation and economic growth in the region.
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.