Information Literacy in the Age of Machines that Learn: Desiderata for Machines that Teach
Libri: International Journal of Libraries and Information Studies
machine learning, context literacy, information search process, guided inquiry
Information Literacy | Library and Information Science | Social and Behavioral Sciences
With the use of machine learning and other advances, modern information search systems make it easy for searchers to access information to meet their most frequent information needs. Building from Kuhlthau’s concepts of exploration and differentiating, this article argues that along with the benefits of greater accessibility, these advances impede the development of information literacy, conceptualized as processes for planning, accessing, judging and communicating information. It is argued that information literacy emerges during interaction with search systems and modern system designs hide or render unworkable the contextual information needed for the judgment processes of information literacy. In response to these concerns, the article contributes desiderata for new designs that facilitate the discovery, navigation and use of context information.
Smith, Catherine L. and Matteson, Miriam L. (2018). Information Literacy in the Age of Machines that Learn: Desiderata for Machines that Teach. Libri: International Journal of Libraries and Information Studies 68(2), 71-84. doi: doi.org/10.1515/libri-2017-0025 Retrieved from https://digitalcommons.kent.edu/slispubs/102