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Artificial Intelligence (AI) assessment to mitigate risks arising from biased, unreliable, or regulatory non-compliant systems remains an open challenge for researchers, policymakers, and organizations across industries. Due to the scattered nature of research on AI across disciplines, there is a lack of overview on the challenges that need to be overcome to move AI assessment forward. In this study, we synthesize existing research on AI assessment applying a descriptive literature review. Our study reveals seven challenges along three main categories: ethical implications, regulatory gaps, and technical limitations. This study contributes to a better understanding of the challenges in AI assessment so that AI researchers and practitioners can resolve these challenges to move AI assessment forward.
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Brecker et al. (2023) studied this question.