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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-30439
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dc.contributor.authorDenzel, Philipp-
dc.contributor.authorBrunner, Stefan-
dc.contributor.authorBilleter, Yann-
dc.contributor.authorForster, Oliver-
dc.contributor.authorFrischknecht-Gruber, Carmen-
dc.contributor.authorReif, Monika Ulrike-
dc.contributor.authorSchilling, Frank-Peter-
dc.contributor.authorWeng, Joanna-
dc.contributor.authorChavarriaga, Ricardo-
dc.contributor.authorAmini, Amin-
dc.contributor.authorRepetto, Marco-
dc.contributor.authorIranfar, Arman-
dc.date.accessioned2024-04-12T09:17:03Z-
dc.date.available2024-04-12T09:17:03Z-
dc.date.issued2024-05-31-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/30439-
dc.description.abstractCertifying the trustworthiness of Artificial Intelligence (AI)-based systems based on dimensions including reliability and transparency is crucial given their increased uptake. Likewise, as regulatory requirements are established, actionable guidelines for certification will be useful for developers and certification bodies to ensure trustworthiness of AI. Here, we present an ongoing effort to develop a validated AI certification scheme which is a framework for assessing the trustworthiness of AI systems including specific objectives with their corresponding means of compliance (i.e. process, documentation or technical methods). Importantly, the scheme makes an explicit link between legal requirements and validated techniques for assessing the compliance of AI systems, resulting in the implementation of a workflow to support AI certification. We explain the rationale for developing the certification scheme and demonstrate the assessment of an example use case with a concrete workflow traversing from objectives to corresponding means, focused on reliability and transparency.de_CH
dc.language.isoende_CH
dc.publisherZHAW Zürcher Hochschule für Angewandte Wissenschaftende_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectArtificial intelligencede_CH
dc.subjectMachine learningde_CH
dc.subjectCertificationde_CH
dc.subjectReliabilityde_CH
dc.subjectTransparencyde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleTowards the certification of AI-based systemsde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitCentre for Artificial Intelligence (CAI)de_CH
zhaw.organisationalunitInstitut für Angewandte Mathematik und Physik (IAMP)de_CH
dc.identifier.doi10.21256/zhaw-30439-
zhaw.conference.details11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedIntelligent Vision Systemsde_CH
zhaw.webfeedResponsible Artificial Intelligence Innovationde_CH
zhaw.funding.zhawcertAInty – A Certification Scheme for AI systemsde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Denzel, P., Brunner, S., Billeter, Y., Forster, O., Frischknecht-Gruber, C., Reif, M. U., Schilling, F.-P., Weng, J., Chavarriaga, R., Amini, A., Repetto, M., & Iranfar, A. (2024, May 31). Towards the certification of AI-based systems. 11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024. https://doi.org/10.21256/zhaw-30439
Denzel, P. et al. (2024) ‘Towards the certification of AI-based systems’, in 11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. Available at: https://doi.org/10.21256/zhaw-30439.
P. Denzel et al., “Towards the certification of AI-based systems,” in 11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024, May 2024. doi: 10.21256/zhaw-30439.
DENZEL, Philipp, Stefan BRUNNER, Yann BILLETER, Oliver FORSTER, Carmen FRISCHKNECHT-GRUBER, Monika Ulrike REIF, Frank-Peter SCHILLING, Joanna WENG, Ricardo CHAVARRIAGA, Amin AMINI, Marco REPETTO und Arman IRANFAR, 2024. Towards the certification of AI-based systems. In: 11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024. Conference paper. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. 31 Mai 2024
Denzel, Philipp, Stefan Brunner, Yann Billeter, Oliver Forster, Carmen Frischknecht-Gruber, Monika Ulrike Reif, Frank-Peter Schilling, et al. 2024. “Towards the Certification of AI-Based Systems.” Conference paper. In 11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-30439.
Denzel, Philipp, et al. “Towards the Certification of AI-Based Systems.” 11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024, ZHAW Zürcher Hochschule für Angewandte Wissenschaften, 2024, https://doi.org/10.21256/zhaw-30439.


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