Data Readiness for AI: A 360-Degree Survey

arXiv:2404.05779v1 Announce Type: new
Abstract: Data are the critical fuel for Artificial Intelligence (AI) models. Poor quality data produces inaccurate and ineffective AI models that may lead to incorrect or unsafe use. Checking for data readiness is a crucial step in improving data quality. Numerous R&D efforts have been spent on improving data quality. However, standardized metrics for evaluating data readiness for use in AI training are still evolving. In this study, we perform a comprehensive survey of metrics used …

abstract ai models artificial artificial intelligence arxiv cs.ai cs.lg data data quality improving intelligence quality quality data survey type