%0 Conference Proceedings
%T Applying AI in Practice: Key Challenges and Lessons Learned
%+ Software Competence Center Hagenberg (SCCH)
%+ University of Linz - Johannes Kepler Universität Linz (JKU)
%A Fischer, Lukas
%A Ehrlinger, Lisa
%A Geist, Verena
%A Ramler, Rudolf
%A Sobieczky, Florian
%A Zellinger, Werner
%A Moser, Bernhard
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 4th International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE)
%C Dublin, Ireland
%Y Andreas Holzinger
%Y Peter Kieseberg
%Y A Min Tjoa
%Y Edgar Weippl
%I Springer International Publishing
%3 Machine Learning and Knowledge Extraction
%V LNCS-12279
%P 451-471
%8 2020-08-25
%D 2020
%R 10.1007/978-3-030-57321-8_25
%K Machine learning systems
%K Data quality
%K Domain adaptation
%K Hybrid models
%K Software engineering
%K Embedded systems
%K Human centered AI
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X The main challenges along with lessons learned from ongoing research in the application of machine learning systems in practice are discussed, taking into account aspects of theoretical foundations, systems engineering, and human-centered AI postulates. The analysis outlines a fundamental theory-practice gap which superimposes the challenges of AI system engineering at the level of data quality assurance, model building, software engineering and deployment.
%G English
%Z TC 5
%Z TC 8
%Z TC 12
%Z WG 8.4
%Z WG 8.9
%Z WG 12.9
%2 https://inria.hal.science/hal-03414730/document
%2 https://inria.hal.science/hal-03414730/file/497121_1_En_25_Chapter.pdf
%L hal-03414730
%U https://inria.hal.science/hal-03414730
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-TC12
%~ IFIP-TC8
%~ IFIP-WG8-4
%~ IFIP-WG8-9
%~ IFIP-CD-MAKE
%~ IFIP-WG12-9
%~ IFIP-LNCS-12279