Why, What and How to Help Each Citizen to Understand Artificial Intelligence?

Artificial intelligence for all Computational thinking MOOC Open educational resources (OERs)

Journal

Kunstliche intelligenz
ISSN: 1610-1987
Titre abrégé: Kunstliche Intell (Oldenbourg)
Pays: Germany
ID NLM: 101766441

Informations de publication

Date de publication:
2021
Historique:
received: 17 07 2020
accepted: 29 04 2021
pubmed: 18 5 2021
medline: 18 5 2021
entrez: 17 5 2021
Statut: ppublish

Résumé

A critical understanding of digital technologies is an empowering competence for citizens of all ages. In this paper we introduce an open educational approach of artificial intelligence (AI) for everyone. Through a hybrid and participative MOOC we aim to develop a critical and creative perspective about the way AI is integrated in the different domains of our lives. We have built and now operate a MOOC in AI for all the citizens from 15 years old. The MOOC aims to help understanding AI foundations and applications, intended for a large public beyond the school domain, with more than 20,000 participants engaged in the MOOC after nine months. This study addresses the pedagogical methods for designing and evaluating the MOOC in AI. Through this study we raise four questions regarding citizen education in AI: Why (i.e., to which aim) sharing such citizen formation? What is the disciplinary knowledge to be shared? What are the competencies to develop? How can it be shared The online version contains supplementary material available at 10.1007/s13218-021-00725-7.

Identifiants

pubmed: 33994668
doi: 10.1007/s13218-021-00725-7
pii: 725
pmc: PMC8103663
doi:

Types de publication

Journal Article

Langues

eng

Pagination

191-199

Informations de copyright

© Gesellschaft für Informatik e.V. and Springer-Verlag GmbH Germany, part of Springer Nature 2021.

Déclaration de conflit d'intérêts

Conflict of interestNot applicable for the non-commercial “common good” reported here: this free access resources set is also not, up to our best knowledge, in concurrence with any other equivalent commercial product.

Auteurs

Frédéric Alexandre (F)

Inria, Mnemosyne Team, Talence, France.

Jade Becker (J)

Magic-Makers, Paris, France.

Marie-Hélène Comte (MH)

Learning Lab, Science Outreach Department, Inria, Talence, France.

Aurélie Lagarrigue (A)

Learning Lab, Science Outreach Department, Inria, Talence, France.

Romain Liblau (R)

Magic-Makers, Paris, France.

Margarida Romero (M)

Laboratoire LINE, Université Côte d'Azur, Nice, France.

Thierry Viéville (T)

Inria, Mnemosyne Team, Talence, France.
Laboratoire LINE, Université Côte d'Azur, Nice, France.

Classifications MeSH