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The many initiatives on trustworthy AI result in a confusing and multipolar landscape that organizations are operating within the fluid and complex international value chains must navigate in pursuing trustworthiness AI. The EU’s proposed Draft AI Act will now shift the focus of such organizations toward the normative requirements for regulatory compliance. Understanding the degree to which standards compliance will deliver regulatory compliance for AI remains a complex challenge. This paper offers a simple and repeatable mechanism for extracting and sharing the terms and concepts relevant to normative statements in the legal and standards texts into open knowledge graphs. This representation is used to assess the adequacy of standards conformance to regulatory compliance and thereby provide a basis for identifying areas where further technical consensus development in trustworthy AI value chains will be required to achieve regulatory compliance.
Trustworthy AI, AI Act, regulation, standards, SC42, semantic web
Trustworthy AI, AI Act, regulation, standards, SC42, semantic web
| citations The total number of citations received by all articles of the researcher of interest. | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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