When Google Speaks: Situating Personalizing Algorithms as Speakers in Online Rhetorical Situations
Type of Presentation
Individual paper/presentation
Target Audience
Higher Education
Location
Session Six Breakouts
Proposal
Popular search engines like Google rely on algorithms informed by data gathering techniques to curate results lists that align with a user’s existing behaviors and beliefs, which can make identifying and combating disinformation difficult. Current scholarship grapples with the presence of personalizing algorithms in academic, social, and personal contexts --ultimately concluding that capital interest on the side of the search engine serves as a driving force for personalizing search results. Consequently, to better position the role personalizing algorithms play in writing and research, algorithms are understood as a nonhuman audience with their own sets of needs and expectations. This presentation will extend upon this conceptualization by situating personalizing algorithms as speakers in an online rhetorical situation. By approaching personalizing algorithms as a speaker, this presentation will investigate methods for identifying and discussing the capital interests that undergird the curation of search results, as well as how this view can enrich methods for recognizing and countering disinformation that may appear in a user’s search results. To supplement this approach, this presentation will analyze the Terms of Service (TOS) for the popular search engines Google, Bing, and DuckDuckGo to assess how these search engines first “listen” to the user through data tracking techniques and how they “speak” to users through the search results provided. Upon analysis, this presentation will conclude by proposing best practices for using this conceptualization in the academic classroom as a means to spotlight the biases embedded within search results and to curb the spread of disinformation.
Presentation Description
This presentation will position the personalizing algorithms used on popular search engines like Google as nonhuman speakers in online rhetorical situations, extending upon current scholarship conceptualizing personalizing algorithms as audience. By understanding the algorithm as “speaker” and the user as “audience,” this presentation will propose a new way to critically assess capital interests undergirding information personalization, as well as discuss how this approach can be used in the academic classroom to push back against the presence of disinformation.
Keywords
Algorithms, disinformation, data gathering, digital literacy, Terms of Service (TOS)
Publication Type and Release Option
Presentation (Open Access)
Recommended Citation
Hope, Lacy, "When Google Speaks: Situating Personalizing Algorithms as Speakers in Online Rhetorical Situations" (2021). Georgia International Conference on Information Literacy. 32.
https://digitalcommons.georgiasouthern.edu/gaintlit/2021/2021/32
When Google Speaks: Situating Personalizing Algorithms as Speakers in Online Rhetorical Situations
Session Six Breakouts
Popular search engines like Google rely on algorithms informed by data gathering techniques to curate results lists that align with a user’s existing behaviors and beliefs, which can make identifying and combating disinformation difficult. Current scholarship grapples with the presence of personalizing algorithms in academic, social, and personal contexts --ultimately concluding that capital interest on the side of the search engine serves as a driving force for personalizing search results. Consequently, to better position the role personalizing algorithms play in writing and research, algorithms are understood as a nonhuman audience with their own sets of needs and expectations. This presentation will extend upon this conceptualization by situating personalizing algorithms as speakers in an online rhetorical situation. By approaching personalizing algorithms as a speaker, this presentation will investigate methods for identifying and discussing the capital interests that undergird the curation of search results, as well as how this view can enrich methods for recognizing and countering disinformation that may appear in a user’s search results. To supplement this approach, this presentation will analyze the Terms of Service (TOS) for the popular search engines Google, Bing, and DuckDuckGo to assess how these search engines first “listen” to the user through data tracking techniques and how they “speak” to users through the search results provided. Upon analysis, this presentation will conclude by proposing best practices for using this conceptualization in the academic classroom as a means to spotlight the biases embedded within search results and to curb the spread of disinformation.
