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GC Insights: Identifying conditions that sculpted bedforms – human insights to building an effective AI (artificial intelligence)

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posted on 2021-12-02, 14:15 authored by John HillierJohn Hillier, Chris Unsworth, Luke De Clerk, Sergey SavelievSergey Saveliev
Insights from a geoscience communication activity, verified using preliminary investigations with an artificial neural network, illustrate that observation of humans' abilities can help design an effective artificial intelligence or “AI”. Even given only one set of “training” examples, survey participants could visually recognize which flow conditions created bedforms (e.g. sand dunes and riverbed ripples) from their shapes, but an interpreter's geoscience expertise does not help. Together, these observations were interpreted as indicating that a machine learning algorithm might be trained successfully from limited data, particularly if it is “helped” by pre-processing bedforms into a simple shape familiar from childhood play.

Funding

British Society of Geomorphology

History

School

  • Science
  • Social Sciences and Humanities

Department

  • Geography and Environment
  • Physics

Published in

Geoscience Communication

Volume

5

Issue

1

Pages

11 - 15

Publisher

Copernicus GmbH

Version

  • VoR (Version of Record)

Rights holder

© The authors

Publisher statement

This is an Open Access Article. It is published by Copernicus GmbH under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

Acceptance date

2021-12-01

Publication date

2022-01-06

Copyright date

2022

ISSN

2569-7102

eISSN

2569-7110

Language

  • en

Depositor

Dr John Hillier. Deposit date: 1 December 2021

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