Applying AI in Practice: Key Challenges and Lessons Learned

Lukas Fischer; Lisa Ehrlinger; Verena Geist; Rudolf Ramler; Florian Sobieczky; Werner Zellinger; Bernhard Moser

doi:10.1007/978-3-030-57321-8_25

Applying AI in Practice: Key Challenges and Lessons Learned

Lukas Fischer
, Lisa Ehrlinger
, Verena Geist
, Rudolf Ramler
, Florian Sobieczky
, Werner Zellinger
, Bernhard Moser

Institute for Application-oriented Knowledge Processing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

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.

Original language	English
Title of host publication	Machine Learning and Knowledge Extraction
Editors	Andreas Holzinger, Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl, Edgar Weippl
Place of Publication	Cham
Publisher	Springer International Publishing
Pages	451-471
Number of pages	21
Volume	12279
ISBN (Print)	978-3-030-57321-8
DOIs	https://doi.org/10.1007/978-3-030-57321-8_25
Publication status	Published - Aug 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12279 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Fields of science

202007 Computer integrated manufacturing (CIM)
102001 Artificial intelligence
102006 Computer supported cooperative work (CSCW)
102010 Database systems
102014 Information design
102015 Information systems
102016 IT security
102019 Machine learning
102022 Software development
102025 Distributed systems
102033 Data mining
102035 Data science
505002 Data protection
509018 Knowledge management

JKU Focus areas

Digital Transformation

Access to Document

10.1007/978-3-030-57321-8_25

Cite this

Fischer, L., Ehrlinger, L., Geist, V., Ramler, R., Sobieczky, F., Zellinger, W., & Moser, B. (2020). Applying AI in Practice: Key Challenges and Lessons Learned. In A. Holzinger, A. Holzinger, P. Kieseberg, A. M. Tjoa, E. Weippl, & E. Weippl (Eds.), Machine Learning and Knowledge Extraction (Vol. 12279, pp. 451-471). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12279 LNCS). Springer International Publishing. https://doi.org/10.1007/978-3-030-57321-8_25

Fischer, Lukas ; Ehrlinger, Lisa ; Geist, Verena et al. / Applying AI in Practice: Key Challenges and Lessons Learned. Machine Learning and Knowledge Extraction. editor / Andreas Holzinger ; Andreas Holzinger ; Peter Kieseberg ; A Min Tjoa ; Edgar Weippl ; Edgar Weippl. Vol. 12279 Cham : Springer International Publishing, 2020. pp. 451-471 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Applying AI in Practice: Key Challenges and Lessons Learned",

abstract = "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.",

author = "Lukas Fischer and Lisa Ehrlinger and Verena Geist and Rudolf Ramler and Florian Sobieczky and Werner Zellinger and Bernhard Moser",

year = "2020",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Fischer, L, Ehrlinger, L, Geist, V, Ramler, R, Sobieczky, F, Zellinger, W & Moser, B 2020, Applying AI in Practice: Key Challenges and Lessons Learned. in A Holzinger, A Holzinger, P Kieseberg, AM Tjoa, E Weippl & E Weippl (eds), Machine Learning and Knowledge Extraction. vol. 12279, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12279 LNCS, Springer International Publishing, Cham, pp. 451-471. https://doi.org/10.1007/978-3-030-57321-8_25

Applying AI in Practice: Key Challenges and Lessons Learned. / Fischer, Lukas; Ehrlinger, Lisa; Geist, Verena et al.
Machine Learning and Knowledge Extraction. ed. / Andreas Holzinger; Andreas Holzinger; Peter Kieseberg; A Min Tjoa; Edgar Weippl; Edgar Weippl. Vol. 12279 Cham: Springer International Publishing, 2020. p. 451-471 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12279 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

TY - GEN

T1 - Applying AI in Practice: Key Challenges and Lessons Learned

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AU - Geist, Verena

AU - Ramler, Rudolf

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AU - Zellinger, Werner

AU - Moser, Bernhard

PY - 2020/8

Y1 - 2020/8

N2 - 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.

AB - 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.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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PB - Springer International Publishing

CY - Cham

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Fischer L, Ehrlinger L, Geist V, Ramler R, Sobieczky F, Zellinger W et al. Applying AI in Practice: Key Challenges and Lessons Learned. In Holzinger A, Holzinger A, Kieseberg P, Tjoa AM, Weippl E, Weippl E, editors, Machine Learning and Knowledge Extraction. Vol. 12279. Cham: Springer International Publishing. 2020. p. 451-471. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-57321-8_25

Applying AI in Practice: Key Challenges and Lessons Learned

Abstract

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Fields of science

JKU Focus areas

Access to Document

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