Abstract
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.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Claes, A., & Philippette, T. (2020). Defining a critical data literacy for recommender systems: A media-grounded approach. Journal of Media Literacy Education, 12(3), 17-29. https://doi.org/10.23860/JMLE-2020-12-3-3
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