Abstract

The increasing role of algorithms shaping our use of communication technology—particularly on social media—comes with a growth of empirical research attempting to assess how literate users are regarding these algorithms. This rapidly emerging field is marked by great diversity in terms of how it theorizes and measures our understanding of algorithms, due, in part, to the opaque “black box” nature of the algorithms themselves. In this review article, we summarize the state of knowledge on algorithmic literacy, including its definitions, development, measurement, and current theorizing on human–algorithm interaction. Drawing on this existing work, we propose an agenda including four different directions that future research could focus on: (1) balancing users’ expectations of algorithmic literacy with developers’ responsibility for algorithmic transparency, (2) methods for engaging users in increasing their literacy, (3) further developing the affective and behavioral facets of literacy, and (4) addressing the new algorithmic divide.

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