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Brain imaging and artificial intelligence

Maoz, Uri and Linstead, Erik (2019) Brain imaging and artificial intelligence. In: Casting Light on the Dark Side of Brain Imaging. Academic Press , London, pp. 99-103. ISBN 9780128161791. http://resolver.caltech.edu/CaltechAUTHORS:20190320-125915181

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Abstract

Humans are OK with other humans making critical financial, moral, and other decisions for them. In contrast, they tend to trust decisions based on artificial intelligence (AI) much less. This is arguably strange because such AI systems have some clear advantages over human decision-making; the latter suffers from known inconsistencies and biases and lacks a clear understanding of its neural underpinnings. Might future brain-imaging let us understand the human brain well enough to mimic it artificially? This chapter discusses on artificial neural networks (ANNs), a modern AI approach, and on why it is so difficult to understand how large ANNs make decisions (or classify) based on their free parameters. It is also suggested that, if humans have such a hard time understanding ANNs, they are likely to have even greater problems understanding the complex biological neural networks recorded in future, large-scale brain imaging.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/B978-0-12-816179-1.00017-7DOIArticle
Additional Information:© 2019 Elsevier Inc. Available online 22 February 2019.
Subject Keywords:Artificial intelligence (AI); artificial neural networks; deep learning; machine learning; limitations of brain imaging
Record Number:CaltechAUTHORS:20190320-125915181
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190320-125915181
Official Citation:Uri Maoz, Erik Linstead, 17 - Brain imaging and artificial intelligence, Editor(s): Amir Raz, Robert T. Thibault, Casting Light on the Dark Side of Brain Imaging, Academic Press, 2019, Pages 99-103, ISBN 9780128161791, https://doi.org/10.1016/B978-0-12-816179-1.00017-7. (http://www.sciencedirect.com/science/article/pii/B9780128161791000177)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:93997
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:20 Mar 2019 20:43
Last Modified:20 Mar 2019 20:43

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