Black Boxes and the Role of Modeling in Environmental Policy Making

Modeling 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 lac...

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Bibliographic Details
Published in:Frontiers in environmental science 2021-03, Vol.9
Main Authors: Maeda, Eduardo Eiji, Haapasaari, Päivi, Helle, Inari, Lehikoinen, Annukka, Voinov, Alexey, Kuikka, Sakari
Format: Article
Language:English
Subjects:
Algorithms
artificial inteligence
Artificial intelligence
Climate change
Communication
Computer applications
Decision making
Environment models
Environmental impact
environmental poicy
Environmental policy
Environmental science
Machine learning
Mathematical models
Model accuracy
modeling
Policy making
Reliability
Science
Scientists
stackeholder engagement
Stakeholders
Trust
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Summary:Modeling 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
ISSN:2296-665X
2296-665X
DOI:10.3389/fenvs.2021.629336