Logo des Repositoriums
 

Towards the Operationalization of Trustworthy AI: Integrating the EU Assessment List into a Procedure Model for the Development and Operation of AI-Systems

dc.contributor.authorKortum,Henrik
dc.contributor.authorRebstadt,Jonas
dc.contributor.authorBöschen,Tula
dc.contributor.authorMeier,Pascal
dc.contributor.authorThomas,Oliver
dc.contributor.editorDemmler, Daniel
dc.contributor.editorKrupka, Daniel
dc.contributor.editorFederrath, Hannes
dc.date.accessioned2022-09-28T17:10:21Z
dc.date.available2022-09-28T17:10:21Z
dc.date.issued2022
dc.description.abstractArtificial intelligence (AI) is increasingly permeating all areas of life and not only changing coexistence in society for the better. Unfortunately, there is an increasing number of examples where AI systems show problematic behavior, such as discrimination or insufficient accuracy, missing data privacy or transparency. To counteract this trend, an EU initiative has drafted a legal framework and recommendations on how AI can be more trustworthy and comply with people's fundamental rights. However, fundamental rights are currently not reflected in procedure models for the development and operation of AI systems. Our work contributes to closing this gap so that companies, especially SMEs with small IT departments and limited financial resources, are supported in the development process. Within the framework of a structured literature review, we derive a procedure model for the development and operation of AI systems and subsequently integrate concrete recommendations for achieving trustworthiness.en
dc.identifier.doi10.18420/inf2022_26
dc.identifier.isbn978-3-88579-720-3
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39524
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2022
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-326
dc.subjectTrustworthy AI
dc.subjectProcedure model
dc.subjectExplainable AI
dc.subjectMachine Learning
dc.subjectSME
dc.titleTowards the Operationalization of Trustworthy AI: Integrating the EU Assessment List into a Procedure Model for the Development and Operation of AI-Systemsen
gi.citation.endPage299
gi.citation.startPage283
gi.conference.date26.-30. September 2022
gi.conference.locationHamburg
gi.conference.sessiontitleKünstliche Intelligenz für kleine und mittlere Unternehmen (KI-KMU 2022)

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
kikmu_04.pdf
Größe:
706.7 KB
Format:
Adobe Portable Document Format