AUTHOR=Kusters Remy , Misevic Dusan , Berry Hugues , Cully Antoine , Le Cunff Yann , Dandoy Loic , Díaz-Rodríguez Natalia , Ficher Marion , Grizou Jonathan , Othmani Alice , Palpanas Themis , Komorowski Matthieu , Loiseau Patrick , Moulin Frier Clément , Nanini Santino , Quercia Daniele , Sebag Michele , Soulié Fogelman Françoise , Taleb Sofiane , Tupikina Liubov , Sahu Vaibhav , Vie Jill-Jênn , Wehbi Fatima TITLE=Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities JOURNAL=Frontiers in Big Data VOLUME=3 YEAR=2020 URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2020.577974 DOI=10.3389/fdata.2020.577974 ISSN=2624-909X 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.