Connectionists: Call for Papers: Explainable Artificial Intelligence and Neuroscience: Cross-disciplinary Perspectives

[Huajin Tang]

Explainable Artificial Intelligence and Neuroscience: Cross-disciplinary
Perspectives





 *CALL FOR PAPERS*

In this Frontiers Research Topic, we bring together neuroscientists and AI
researchers to consider the problem of explainable AI. Though deep learning
is the main pillar of current AI techniques and is ubiquitous in basic
science and real-world applications, it is also flagged by AI researchers
for its black-box problem: it is easy to fool, and it also cannot explain
how it makes a prediction or decision. Therefore, the significance of
creating transparent, explainable AI, should not be underestimated. In
particular, we are interested in leveraging insights from neurobiology that
might be useful for novel approaches in AI, and techniques for analyzing
artificial neural networks that might be applied, in turn, to neuroscience.

*Participating Journals*

Manuscripts can be submitted to this Research Topic via the following
journals:

Frontiers in Artificial Intelligence; Frontiers in Neurorobotics; Frontiers
in Big Data.

*Papers Submission *

Papers submission will be handled through our research topic page:

https://www.frontiersin.org/research-topics/11553/explainable-artificial-intelligence

Submission Deadline： 31 May 2020



*Topic Editors*

*James Leland Olds, *George Mason University, United States

*Jeffrey L Krichmar, *University of California, Irvine， United States

*Huajin Tang, *Zhejiang University, Hangzhou, China

*Juan V. Sanchez-Andres, *University of JaumeI, Castelló de La Plana, Spain

-- 
Professor
College of Computer Science and Technology
Zhejiang Univeristy, Hangzhou 310027, China
E-mail: htang at zju.edu.cn
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