Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities
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 optimall...
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2020-11-01
|
Series: | Frontiers in Big Data |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fdata.2020.577974/full |
id |
doaj-ef48524cad574e7ea1e69fef04edeb1f |
---|---|
record_format |
Article |
spelling |
doaj-ef48524cad574e7ea1e69fef04edeb1f2020-12-17T11:37:37ZengFrontiers Media S.A.Frontiers in Big Data2624-909X2020-11-01310.3389/fdata.2020.577974577974Interdisciplinary Research in Artificial Intelligence: Challenges and OpportunitiesRemy Kusters0Dusan Misevic1Hugues Berry2Antoine Cully3Yann Le Cunff4Loic Dandoy5Natalia Díaz-Rodríguez6Natalia Díaz-Rodríguez7Marion Ficher8Jonathan Grizou9Alice Othmani10Themis Palpanas11Matthieu Komorowski12Patrick Loiseau13Clément Moulin Frier14Santino Nanini15Daniele Quercia16Michele Sebag17Françoise Soulié Fogelman18Sofiane Taleb19Liubov Tupikina20Liubov Tupikina21Vaibhav Sahu22Jill-Jênn Vie23Fatima Wehbi24INSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, FranceINSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, FranceInria, Villeurbanne, FranceImperial College London, London, United KingdomUniversity of Rennes, Rennes, FranceINSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, FranceInria Flowers, Paris and Bordeaux, FranceENSTA Paris, Institut Polytechnique Paris, Paris, FranceINSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, FranceINSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, FranceUniversité Paris-Est, LISSI, Vitry sur Seine, FranceUniversité de Paris, France and French University Institute (IUF), Paris, FranceImperial College London, London, United KingdomUniversité Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, Grenoble, FranceInria Flowers, Paris and Bordeaux, FranceINSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, France0Nokia Bell Labs, Cambridge, United Kingdom1TAU, LRI-CNRS–INRIA, Universite Paris-Saclay, France2Hub France Intelligence Artificielle, Paris, FranceINSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, FranceINSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, France3Nokia Bell Labs, Paris, FranceINSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, France4Inria, Lille, FranceINSERM U1284, Université de Paris, Center for Research and Interdisciplinarity (CRI), Paris, FranceThe 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.https://www.frontiersin.org/articles/10.3389/fdata.2020.577974/fullartificial intelligenceinterdisciplinary scienceeducationethicsauditabilityinterpretability |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Remy Kusters Dusan Misevic Hugues Berry Antoine Cully Yann Le Cunff Loic Dandoy Natalia Díaz-Rodríguez Natalia Díaz-Rodríguez Marion Ficher Jonathan Grizou Alice Othmani Themis Palpanas Matthieu Komorowski Patrick Loiseau Clément Moulin Frier Santino Nanini Daniele Quercia Michele Sebag Françoise Soulié Fogelman Sofiane Taleb Liubov Tupikina Liubov Tupikina Vaibhav Sahu Jill-Jênn Vie Fatima Wehbi |
spellingShingle |
Remy Kusters Dusan Misevic Hugues Berry Antoine Cully Yann Le Cunff Loic Dandoy Natalia Díaz-Rodríguez Natalia Díaz-Rodríguez Marion Ficher Jonathan Grizou Alice Othmani Themis Palpanas Matthieu Komorowski Patrick Loiseau Clément Moulin Frier Santino Nanini Daniele Quercia Michele Sebag Françoise Soulié Fogelman Sofiane Taleb Liubov Tupikina Liubov Tupikina Vaibhav Sahu Jill-Jênn Vie Fatima Wehbi Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities Frontiers in Big Data artificial intelligence interdisciplinary science education ethics auditability interpretability |
author_facet |
Remy Kusters Dusan Misevic Hugues Berry Antoine Cully Yann Le Cunff Loic Dandoy Natalia Díaz-Rodríguez Natalia Díaz-Rodríguez Marion Ficher Jonathan Grizou Alice Othmani Themis Palpanas Matthieu Komorowski Patrick Loiseau Clément Moulin Frier Santino Nanini Daniele Quercia Michele Sebag Françoise Soulié Fogelman Sofiane Taleb Liubov Tupikina Liubov Tupikina Vaibhav Sahu Jill-Jênn Vie Fatima Wehbi |
author_sort |
Remy Kusters |
title |
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities |
title_short |
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities |
title_full |
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities |
title_fullStr |
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities |
title_full_unstemmed |
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities |
title_sort |
interdisciplinary research in artificial intelligence: challenges and opportunities |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Big Data |
issn |
2624-909X |
publishDate |
2020-11-01 |
description |
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. |
topic |
artificial intelligence interdisciplinary science education ethics auditability interpretability |
url |
https://www.frontiersin.org/articles/10.3389/fdata.2020.577974/full |
work_keys_str_mv |
AT remykusters interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT dusanmisevic interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT huguesberry interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT antoinecully interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT yannlecunff interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT loicdandoy interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT nataliadiazrodriguez interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT nataliadiazrodriguez interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT marionficher interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT jonathangrizou interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT aliceothmani interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT themispalpanas interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT matthieukomorowski interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT patrickloiseau interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT clementmoulinfrier interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT santinonanini interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT danielequercia interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT michelesebag interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT francoisesouliefogelman interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT sofianetaleb interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT liubovtupikina interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT liubovtupikina interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT vaibhavsahu interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT jilljennvie interdisciplinaryresearchinartificialintelligencechallengesandopportunities AT fatimawehbi interdisciplinaryresearchinartificialintelligencechallengesandopportunities |
_version_ |
1724380019167330304 |