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January 27, 2025
Conference Proceeding
Title
Symposium on Scaling AI Assessments, SAIA 2024
Title Supplement
September 30-October 1, 2024, Cologne, Germany
Abstract
This volume presents scientific and practical contributions from the Symposium on Scaling AI Assessments (SAIA 2024). SAIA 2024 was held on September 30 and October 1, 2024 in Cologne, Germany. It gathered practitioners from the TIC sector (testing, inspection, certification), representatives from tech start-ups and AI deployers, as well as researchers in the field of trustworthy AI. Together, they discussed and promoted solution approaches towards scalable AI assessments.
Especially against the background of European AI regulation, AI conformity assessment procedures are of particular importance, both for specific use cases and for general-purpose models. But also in non-regulated domains, the quality of AI systems is a decisive factor as unintended behavior can lead to serious financial and reputation damage. As a result, there is a great need for AI audits and assessments and in fact, it can also be observed that a corresponding market is forming. At the same time, there are still (technical) challenges in conducting the required assessments and a lack of extensive practical experience in evaluating different AI systems. Overall, the emergence of the first marketable, commercial AI assessment offerings is just in the process and a definitive, distinct procedure for AI quality assurance has not yet been established.
Especially against the background of European AI regulation, AI conformity assessment procedures are of particular importance, both for specific use cases and for general-purpose models. But also in non-regulated domains, the quality of AI systems is a decisive factor as unintended behavior can lead to serious financial and reputation damage. As a result, there is a great need for AI audits and assessments and in fact, it can also be observed that a corresponding market is forming. At the same time, there are still (technical) challenges in conducting the required assessments and a lack of extensive practical experience in evaluating different AI systems. Overall, the emergence of the first marketable, commercial AI assessment offerings is just in the process and a definitive, distinct procedure for AI quality assurance has not yet been established.
Editor(s)
Publisher
Dagstuhl Publishing
Conference
Open Access
File(s)
Rights
CC BY 4.0: Creative Commons Attribution
Language
English