Presentation Title

Toward Algorithmic Literacy: Tracing Agency Across Algorithm-Centered Online Research

Biographical Sketch

Daniel Hocutt is an English PhD candidate at Old Dominion University who works as a web manager and adjunct professor of English at the University of Richmond. His research interests include the rhetoric of algorithms, algorithmic literacy, technical communication, online composing, and rhetorical agency. He is on Twitter at @dhocutt and online at danielhocutt.com.

Type of Presentation

Individual presentation

Brief Description of Presentation

This presentation shares the results of a recent study completed by the presenter that seeks to trace and visualize agency as it emerges during online research activity. The study positions this tracing and visualizing activity as algorithmic literacy with the goal of critical understanding of algorithmic influence on agency shared among researchers and search technologies. The presentation offers a visual model for depicting ways technologies and researchers interact to generate and select online search results.

Abstract of Proposal

A Pew Research Center report, Code-Dependent: Pros and Cons of the Algorithm Age, calls for “education in algorithm literacy” (Rainie & Anderson, 2017, p. 74) across educational and corporate environments. This call more stridently echoes earlier calls from Davidson (2011) and Striphas (2011) for a focus on algorithmic literacy in education. Challenging the development of “algorithm literacy” are both the highly technical nature of programming and deploying algorithms in digital environments and the highly profitable proprietary nature of algorithmic processes. The result is that users generally face algorithms as “black box” (Latour, 2005) technologies whose activities are too complex, too technical, and too obscure to explore. At the same time, algorithmic processes are ubiquitous in human experience. From self-parking cars to self-driving trucks, smart digital assistants to smartphones, autocomplete suggestions to automatic film recommendations, algorithms make myriad decisions around, about, and on behalf of humans. This presentation responds to the call for education in algorithm literacy by proposing methods for identifying and tracing agency as it emerges during the algorithm-centered activity of online search. Using the lens of Bennett’s (2010) vital materiality and Latour’s (2005) actor-network theory, this presentation traces and visualizes agency emerging across a continuum of human, corporate, technological, and network activities. This tracing activity represents a technological aspect of Cargile Cook’s (2002) layered literacies and demonstrates one potential method for developing and teaching algorithm literacy. The presentation positions algorithm literacy within a frame of Gee’s (1987) meta-knowledge about algorithmic influence in search activities.

Start Date

2-24-2018 1:10 PM

End Date

2-24-2018 2:40 PM

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Feb 24th, 1:10 PM Feb 24th, 2:40 PM

Toward Algorithmic Literacy: Tracing Agency Across Algorithm-Centered Online Research

A Pew Research Center report, Code-Dependent: Pros and Cons of the Algorithm Age, calls for “education in algorithm literacy” (Rainie & Anderson, 2017, p. 74) across educational and corporate environments. This call more stridently echoes earlier calls from Davidson (2011) and Striphas (2011) for a focus on algorithmic literacy in education. Challenging the development of “algorithm literacy” are both the highly technical nature of programming and deploying algorithms in digital environments and the highly profitable proprietary nature of algorithmic processes. The result is that users generally face algorithms as “black box” (Latour, 2005) technologies whose activities are too complex, too technical, and too obscure to explore. At the same time, algorithmic processes are ubiquitous in human experience. From self-parking cars to self-driving trucks, smart digital assistants to smartphones, autocomplete suggestions to automatic film recommendations, algorithms make myriad decisions around, about, and on behalf of humans. This presentation responds to the call for education in algorithm literacy by proposing methods for identifying and tracing agency as it emerges during the algorithm-centered activity of online search. Using the lens of Bennett’s (2010) vital materiality and Latour’s (2005) actor-network theory, this presentation traces and visualizes agency emerging across a continuum of human, corporate, technological, and network activities. This tracing activity represents a technological aspect of Cargile Cook’s (2002) layered literacies and demonstrates one potential method for developing and teaching algorithm literacy. The presentation positions algorithm literacy within a frame of Gee’s (1987) meta-knowledge about algorithmic influence in search activities.