Interdisciplinary research in artificial intelligence: challenges and opportunities
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
The use of artificial intelligence (AI) in a variety of research fields is speeding up multiple digital revolutions, from shifting paradigms in healthcare, precision medicine and wearable sensing, to public services and education offered to the masses around the world, to future cities made optimally efficient by autonomous driving. When a revolution happens, the consequences are not obvious straight away, and to date, there is no uniformly adapted framework to guide AI research to ensure a sustainable societal transition. To answer this need, here we analyze three key challenges to interdisciplinary AI research, and deliver three broad conclusions: 1) future development of AI should not only impact other scientific domains but should also take inspiration and benefit from other fields of science, 2) AI research must be accompanied by decision explainability, dataset bias transparency as well as development of evaluation methodologies and creation of regulatory agencies to ensure responsibility, and 3) AI education should receive more attention, efforts and innovation from the educational and scientific communities. Our analysis is of interest not only to AI practitioners but also to other researchers and the general public as it offers ways to guide the emerging collaborations and interactions toward the most fruitful outcomes.
Date Issued
2020-11-23
Date Acceptance
2020-10-28
Citation
Frontiers in Big Data, 2020, 3, pp.1-7
ISSN
2624-909X
Publisher
Frontiers Media
Start Page
1
End Page
7
Journal / Book Title
Frontiers in Big Data
Volume
3
Copyright Statement
© 2020 Kusters, Misevic, Berry, Cully, Cunff, Dandoy, Díaz-Rodríguez, Ficher, Grizou, Othmani, Palpanas, Komorowski, Loiseau, Frier, Nanini, Quercia, Sebag, Fogelman, Taleb, Tupikina, Sahu, Vie and Wehbi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
License URL
Identifier
https://www.frontiersin.org/articles/10.3389/fdata.2020.577974/full
Publication Status
Published
Date Publish Online
2020-11-23