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 language | English |
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Article number | 629336 |
Journal | Frontiers in Environmental Science |
Volume | 9 |
Number of pages | 5 |
ISSN | 2296-665X |
DOIs | |
Publication status | Published - 23 Mar 2021 |
MoE publication type | A1 Journal article-refereed |
Fields of Science
- 1172 Environmental sciences
- artificial inteligence
- modeling
- environmental poicy
- decision making
- stackeholder engagement