Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?

Detalhes bibliográficos
Autor(a) principal: Manzione, Rodrigo Lilla [UNESP]
Data de Publicação: 2021
Outros Autores: Matulovic, Mariana [UNESP]
Tipo de documento: Capítulo de livro
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/978-3-030-59320-9_93
http://hdl.handle.net/11449/206132
Resumo: In this modern and dynamic society, threatened by climate change, poverty, hungry and economical systems collapse, artificial intelligence (AI) emerged as a promise field to solve many actual problems. Although AI does not give absolute answers. The outputs of AI methods are subjective and in many situations depend on human-based decisions. It has a strong impact on decision-making processes and geoscientists are highly exposed to this question. Specifically, on groundwater, issues involving water quality and water quantity deserve special attention for monetary resources applications, urban supply, ecosystemical services should be balanced in order to avoid biased solutions. This paper aims to present some AI methods and discuss where it they can lead geoscientists with and without an ethical posture. A study case using monitoring water levels data is presented.
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spelling Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?Algorithmic responsibilityData analysisGeoethicsGeosciencesIn this modern and dynamic society, threatened by climate change, poverty, hungry and economical systems collapse, artificial intelligence (AI) emerged as a promise field to solve many actual problems. Although AI does not give absolute answers. The outputs of AI methods are subjective and in many situations depend on human-based decisions. It has a strong impact on decision-making processes and geoscientists are highly exposed to this question. Specifically, on groundwater, issues involving water quality and water quantity deserve special attention for monetary resources applications, urban supply, ecosystemical services should be balanced in order to avoid biased solutions. This paper aims to present some AI methods and discuss where it they can lead geoscientists with and without an ethical posture. A study case using monitoring water levels data is presented.Biosystems Engineering Department School of Sciences and Engineering (DEB/FCE) São Paulo State University (UNESP)Biosystems Engineering Department School of Sciences and Engineering (DEB/FCE) São Paulo State University (UNESP)Universidade Estadual Paulista (Unesp)Manzione, Rodrigo Lilla [UNESP]Matulovic, Mariana [UNESP]2021-06-25T10:27:04Z2021-06-25T10:27:04Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookPart441-445http://dx.doi.org/10.1007/978-3-030-59320-9_93Advances in Science, Technology and Innovation, p. 441-445.2522-87222522-8714http://hdl.handle.net/11449/20613210.1007/978-3-030-59320-9_932-s2.0-85103542565Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAdvances in Science, Technology and Innovationinfo:eu-repo/semantics/openAccess2021-10-22T21:09:44Zoai:repositorio.unesp.br:11449/206132Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-22T21:09:44Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?
title Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?
spellingShingle Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?
Manzione, Rodrigo Lilla [UNESP]
Algorithmic responsibility
Data analysis
Geoethics
Geosciences
title_short Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?
title_full Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?
title_fullStr Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?
title_full_unstemmed Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?
title_sort Decision-Making in Groundwater Management: Where Artificial Intelligence Can Really Lead Geoscientists?
author Manzione, Rodrigo Lilla [UNESP]
author_facet Manzione, Rodrigo Lilla [UNESP]
Matulovic, Mariana [UNESP]
author_role author
author2 Matulovic, Mariana [UNESP]
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Manzione, Rodrigo Lilla [UNESP]
Matulovic, Mariana [UNESP]
dc.subject.por.fl_str_mv Algorithmic responsibility
Data analysis
Geoethics
Geosciences
topic Algorithmic responsibility
Data analysis
Geoethics
Geosciences
description In this modern and dynamic society, threatened by climate change, poverty, hungry and economical systems collapse, artificial intelligence (AI) emerged as a promise field to solve many actual problems. Although AI does not give absolute answers. The outputs of AI methods are subjective and in many situations depend on human-based decisions. It has a strong impact on decision-making processes and geoscientists are highly exposed to this question. Specifically, on groundwater, issues involving water quality and water quantity deserve special attention for monetary resources applications, urban supply, ecosystemical services should be balanced in order to avoid biased solutions. This paper aims to present some AI methods and discuss where it they can lead geoscientists with and without an ethical posture. A study case using monitoring water levels data is presented.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-25T10:27:04Z
2021-06-25T10:27:04Z
2021-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/978-3-030-59320-9_93
Advances in Science, Technology and Innovation, p. 441-445.
2522-8722
2522-8714
http://hdl.handle.net/11449/206132
10.1007/978-3-030-59320-9_93
2-s2.0-85103542565
url http://dx.doi.org/10.1007/978-3-030-59320-9_93
http://hdl.handle.net/11449/206132
identifier_str_mv Advances in Science, Technology and Innovation, p. 441-445.
2522-8722
2522-8714
10.1007/978-3-030-59320-9_93
2-s2.0-85103542565
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Advances in Science, Technology and Innovation
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 441-445
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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