A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf
.
Quality Assurance for AI-based Systems: Overview and Challenges
[article]
2021
arXiv
pre-print
The number and importance of AI-based systems in all domains is growing. With the pervasive use and the dependence on AI-based systems, the quality of these systems becomes essential for their practical usage. However, quality assurance for AI-based systems is an emerging area that has not been well explored and requires collaboration between the SE and AI research communities. This paper discusses terminology and challenges on quality assurance for AI-based systems to set a baseline for that
arXiv:2102.05351v1
fatcat:5f7i2xrsszhf7o4bhxmh3wbc6m