Defining a critical data literacy for recommender systems: A media-grounded approach

The digital processing of massive data is becoming a central component of our technological infrastructures. While being able to use these tools efficiently is an issue that cannot be ignored, it appears crucial to provide citizens with the means to control their technical environment. Recommender s...

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Bibliographic Details
Published inThe journal of media literacy education Vol. 12; no. 3; pp. 17 - 29
Main Authors Claes, Arnaud, Philippette, Thibault
Format Journal Article
LanguageEnglish
Published National Association for Media Literacy Education 14.12.2020
Subjects
Critical Literacy
Data Analysis
Educational Philosophy
Information Literacy
Information Technology
Media Literacy
News Reporting
Teaching Methods
Technological Literacy
Users (Information)
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Summary:The digital processing of massive data is becoming a central component of our technological infrastructures. While being able to use these tools efficiently is an issue that cannot be ignored, it appears crucial to provide citizens with the means to control their technical environment. Recommender systems and personalization technologies are currently being blamed for the destabilization of users' informational ecosystems and a growing polarization of opinions. However, a critical review of the current literature on the subject indicates that these recommender systems may also be beneficial to the user in specific circumstances. Building on current critical data literacies approaches, key concepts from the philosophy of technology and a media literacy perspective, this paper suggests a framework defining the competences needed to help users assess these technologies and critically include them in their digital ecosystem.
ISSN:2167-8715
2167-8715
DOI:10.23860/JMLE-2020-12-3-3