Using Large Language Models to Enrich the Documentation of Datasets for Machine Learning

arXiv:2404.15320v1 Announce Type: cross
Abstract: Recent regulatory initiatives like the European AI Act and relevant voices in the Machine Learning (ML) community stress the need to describe datasets along several key dimensions for trustworthy AI, such as the provenance processes and social concerns. However, this information is typically presented as unstructured text in accompanying documentation, hampering their automated analysis and processing. In this work, we explore using large language models (LLM) and a set of prompting strategies to automatically extract …

abstract act ai act arxiv community concerns cs.ai cs.cl cs.dl datasets dimensions documentation however information key language language models large language large language models machine machine learning processes provenance regulatory social stress trustworthy trustworthy ai type voices