Knowledge Management Challenges for AI Quality

Abstract

Developing an AI-based system is uniquely challenging as it requires knowledge across multiple domains. Though the project team is required to be versatile, it is possible that their repertoire cannot cover all of the requirements of the system, which results in damage to the software quality. Therefore, it is critical to have an effective team knowledge management (KM) strategy to detect the valuable “unknown”, optimize the “known” task assignment, and enlarge the team knowledge base. Moreover, it is more effective to support the process with data-driven approaches.