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Article: Black Boxes and the Role of Modeling in Environmental Policy Making

TitleBlack Boxes and the Role of Modeling in Environmental Policy Making
Authors
Keywordsartificial inteligence
decision making
environmental poicy
modeling
stackeholder engagement
Issue Date2021
Citation
Frontiers in Environmental Science, 2021, v. 9, article no. 629336 How to Cite?
AbstractModeling is essential for modern science, and science-based policies are directly affected by the reliability of model outputs. Artificial intelligence has improved the accuracy and capability of model simulations, but often at the expense of a rational understanding of the systems involved. The lack of transparency in black box models, artificial intelligence based ones among them, can potentially affect the trust in science driven policy making. Here, we suggest that a broader discussion is needed to address the implications of black box approaches on the reliability of scientific advice used for policy making. We argue that participatory methods can bridge the gap between increasingly complex scientific methods and the people affected by their interpretations
Persistent Identifierhttp://hdl.handle.net/10722/309282
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorMaeda, Eduardo Eiji-
dc.contributor.authorHaapasaari, Päivi-
dc.contributor.authorHelle, Inari-
dc.contributor.authorLehikoinen, Annukka-
dc.contributor.authorVoinov, Alexey-
dc.contributor.authorKuikka, Sakari-
dc.date.accessioned2021-12-15T03:59:54Z-
dc.date.available2021-12-15T03:59:54Z-
dc.date.issued2021-
dc.identifier.citationFrontiers in Environmental Science, 2021, v. 9, article no. 629336-
dc.identifier.urihttp://hdl.handle.net/10722/309282-
dc.description.abstractModeling is essential for modern science, and science-based policies are directly affected by the reliability of model outputs. Artificial intelligence has improved the accuracy and capability of model simulations, but often at the expense of a rational understanding of the systems involved. The lack of transparency in black box models, artificial intelligence based ones among them, can potentially affect the trust in science driven policy making. Here, we suggest that a broader discussion is needed to address the implications of black box approaches on the reliability of scientific advice used for policy making. We argue that participatory methods can bridge the gap between increasingly complex scientific methods and the people affected by their interpretations-
dc.languageeng-
dc.relation.ispartofFrontiers in Environmental Science-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectartificial inteligence-
dc.subjectdecision making-
dc.subjectenvironmental poicy-
dc.subjectmodeling-
dc.subjectstackeholder engagement-
dc.titleBlack Boxes and the Role of Modeling in Environmental Policy Making-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3389/fenvs.2021.629336-
dc.identifier.scopuseid_2-s2.0-85103850362-
dc.identifier.volume9-
dc.identifier.spagearticle no. 629336-
dc.identifier.epagearticle no. 629336-
dc.identifier.eissn2296-665X-
dc.identifier.isiWOS:000636991700001-

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