Explainability as the key ingredient for AI adoption in Industry 5.0 settings

Detalhes bibliográficos
Autor(a) principal: Agostinho, Carlos
Data de Publicação: 2023
Outros Autores: Dikopoulou, Zoumpolia, Lavasa, Eleni, Perakis, Konstantinos, Pitsios, Stamatis, Branco, Rui, Reji, Sangeetha, Hetterich, Jonas, Biliri, Evmorfia, Lampathaki, Fenareti, Rodríguez Del Rey, Silvia, Gkolemis, Vasileios
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/164433
Resumo: Funding Information: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The research leading to this work has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement no: 957362. Publisher Copyright: Copyright © 2023 Agostinho, Dikopoulou, Lavasa, Perakis, Pitsios, Branco, Reji, Hetterich, Biliri, Lampathaki, Rodríguez Del Rey and Gkolemis.
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spelling Explainability as the key ingredient for AI adoption in Industry 5.0 settingsbusiness valuedecision-makingexplainable AIFuzzy Cognitive Mapsmanufacturing industryXMANAI platformArtificial IntelligenceSDG 9 - Industry, Innovation, and InfrastructureFunding Information: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The research leading to this work has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement no: 957362. Publisher Copyright: Copyright © 2023 Agostinho, Dikopoulou, Lavasa, Perakis, Pitsios, Branco, Reji, Hetterich, Biliri, Lampathaki, Rodríguez Del Rey and Gkolemis.Explainable Artificial Intelligence (XAI) has gained significant attention as a means to address the transparency and interpretability challenges posed by black box AI models. In the context of the manufacturing industry, where complex problems and decision-making processes are widespread, the XMANAI platform emerges as a solution to enable transparent and trustworthy collaboration between humans and machines. By leveraging advancements in XAI and catering the prompt collaboration between data scientists and domain experts, the platform enables the construction of interpretable AI models that offer high transparency without compromising performance. This paper introduces the approach to building the XMANAI platform and highlights its potential to resolve the “transparency paradox” of AI. The platform not only addresses technical challenges related to transparency but also caters to the specific needs of the manufacturing industry, including lifecycle management, security, and trusted sharing of AI assets. The paper provides an overview of the XMANAI platform main functionalities, addressing the challenges faced during the development and presenting the evaluation framework to measure the performance of the delivered XAI solutions. It also demonstrates the benefits of the XMANAI approach in achieving transparency in manufacturing decision-making, fostering trust and collaboration between humans and machines, improving operational efficiency, and optimizing business value.UNINOVA-Instituto de Desenvolvimento de Novas TecnologiasCTS - Centro de Tecnologia e SistemasRUNAgostinho, CarlosDikopoulou, ZoumpoliaLavasa, EleniPerakis, KonstantinosPitsios, StamatisBranco, RuiReji, SangeethaHetterich, JonasBiliri, EvmorfiaLampathaki, FenaretiRodríguez Del Rey, SilviaGkolemis, Vasileios2024-03-05T00:16:09Z2023-12-112023-12-11T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article21application/pdfhttp://hdl.handle.net/10362/164433eng2624-8212PURE: 84377962https://doi.org/10.3389/frai.2023.1264372info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:52:12Zoai:run.unl.pt:10362/164433Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T04:00:10.353222Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Explainability as the key ingredient for AI adoption in Industry 5.0 settings
title Explainability as the key ingredient for AI adoption in Industry 5.0 settings
spellingShingle Explainability as the key ingredient for AI adoption in Industry 5.0 settings
Agostinho, Carlos
business value
decision-making
explainable AI
Fuzzy Cognitive Maps
manufacturing industry
XMANAI platform
Artificial Intelligence
SDG 9 - Industry, Innovation, and Infrastructure
title_short Explainability as the key ingredient for AI adoption in Industry 5.0 settings
title_full Explainability as the key ingredient for AI adoption in Industry 5.0 settings
title_fullStr Explainability as the key ingredient for AI adoption in Industry 5.0 settings
title_full_unstemmed Explainability as the key ingredient for AI adoption in Industry 5.0 settings
title_sort Explainability as the key ingredient for AI adoption in Industry 5.0 settings
author Agostinho, Carlos
author_facet Agostinho, Carlos
Dikopoulou, Zoumpolia
Lavasa, Eleni
Perakis, Konstantinos
Pitsios, Stamatis
Branco, Rui
Reji, Sangeetha
Hetterich, Jonas
Biliri, Evmorfia
Lampathaki, Fenareti
Rodríguez Del Rey, Silvia
Gkolemis, Vasileios
author_role author
author2 Dikopoulou, Zoumpolia
Lavasa, Eleni
Perakis, Konstantinos
Pitsios, Stamatis
Branco, Rui
Reji, Sangeetha
Hetterich, Jonas
Biliri, Evmorfia
Lampathaki, Fenareti
Rodríguez Del Rey, Silvia
Gkolemis, Vasileios
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias
CTS - Centro de Tecnologia e Sistemas
RUN
dc.contributor.author.fl_str_mv Agostinho, Carlos
Dikopoulou, Zoumpolia
Lavasa, Eleni
Perakis, Konstantinos
Pitsios, Stamatis
Branco, Rui
Reji, Sangeetha
Hetterich, Jonas
Biliri, Evmorfia
Lampathaki, Fenareti
Rodríguez Del Rey, Silvia
Gkolemis, Vasileios
dc.subject.por.fl_str_mv business value
decision-making
explainable AI
Fuzzy Cognitive Maps
manufacturing industry
XMANAI platform
Artificial Intelligence
SDG 9 - Industry, Innovation, and Infrastructure
topic business value
decision-making
explainable AI
Fuzzy Cognitive Maps
manufacturing industry
XMANAI platform
Artificial Intelligence
SDG 9 - Industry, Innovation, and Infrastructure
description Funding Information: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The research leading to this work has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement no: 957362. Publisher Copyright: Copyright © 2023 Agostinho, Dikopoulou, Lavasa, Perakis, Pitsios, Branco, Reji, Hetterich, Biliri, Lampathaki, Rodríguez Del Rey and Gkolemis.
publishDate 2023
dc.date.none.fl_str_mv 2023-12-11
2023-12-11T00:00:00Z
2024-03-05T00:16:09Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/164433
url http://hdl.handle.net/10362/164433
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2624-8212
PURE: 84377962
https://doi.org/10.3389/frai.2023.1264372
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 21
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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