Abstract

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

Original languageEnglish
Article number629336
JournalFrontiers in Environmental Science
Volume9
Number of pages5
ISSN2296-665X
DOIs
Publication statusPublished - 23 Mar 2021
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 1172 Environmental sciences
  • artificial inteligence
  • modeling
  • environmental poicy
  • decision making
  • stackeholder engagement

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