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Digital Literacy FLC (Spring 2021)

Resources from the spring 2021 Digital Literacy Faculty Learning Community at Rowan University.

Information and Power (Theme)

Our next FLC meeting theme will be structured around information and information systems; power; and issues of diversity, equity, and inclusion. While often in society at large, information and technology are perceived of as neutral, biases and assumptions are embedded throughout information systems (just as they are woven throughout all structures of power and privilege). Acts of resistance and grassroots efforts can help to shed light on issues of power and privilege and can bring to the surface assumptions or biases that are often otherwise rendered invisible. This month’s FLC theme is broad, so we have selected two core resources that provide examples of some ways that systems of power and privilege are reflected in information and technology. These are intended to open discussion. As you review the two core resources, please think about examples in your teaching practices and/or your research that relate to the theme of information and power.

Opening Discussion Questions:

  • What concepts or ideas from today’s core resources stood out to you? Did you see certain connections between either of these resources and your discipline and/or your teaching? 

  • How do/might we explore with students the role that algorithmic bias plays in everyday life and/or in academia (particularly given the fact that these biases, much like social privilege, are often rendered invisible)? 

  • [Time permitting] What other challenges or questions are you engaging with in relation to intersections between DEI, information and information systems, power and digital literacy in your classes? 

Core Resources:

Key Concepts: 

  • Algorithmic bias: “systematic and repeatable errors in a computer system that create unfair outcomes, such as privileging one arbitrary group of users over others” - Wikipedia
  • Information systems: “an academic study of systems with a specific reference to information and the complementary networks of hardware and software that people and organizations use to collect, filter, process, create and also distribute data. An emphasis is placed on an information system having a definitive boundary, users, processors, storage, inputs, outputs and the aforementioned communication networks” - Wikipedia 

Emergent Themes

The myth of neutrality

  • The various ways that bias is ingrained in information systems, including in headlines, auto-suggestions in search systems, search results, and the algorithms that generate search results
  • Interrogating the presumed objectivity of information systems in the classroom and acknowledging how the “black box” of algorithms are actually influenced by certain assumptions and biases that are often difficult to uncover
  • The misconception that information systems are neutral as a way for companies and organizations to justify decision-making and to absolve themselves of responsibility
  • The potential dangers of corporate monopolies dictating information systems and search

Teaching

  • Teaching about algorithmic bias as a way to encourage inquiry and information seeking beyond a simple Google search
  • Educational uses of digital platforms,the ways in which these contribute to algorithmic bias and filter bubbles, and the digital privacy concerns that such tools present
  • The common self-perception that one is too savvy to be misled by biased search results or search systems, when in reality these biases are often rendered invisible and thus easy to overlook. This can be countered in part through providing evidence of algorithmic bias, its consequences, and the difficulties of often seeing that bias.
  • The issues of information access, convenience, and habit: Students go to Google to find resources that match their claims, opinions, and perspectives. How do we provide access to conversations or resources that are outside of students’ usual approaches to searching and researching? How do we incorporate information from sources/voices that tend to be marginalized or minoritized? How do we encourage students to look beyond the “usual suspects” and to engage with texts that center voices/experiences that are not typically considered the norm?

Teaching Ideas and Activities

  • Have students search for organizations/groups/brands/social media influencers which/whom they follow or about which they have some depth of knowledge. Analyze what the initial search results reveal. Compare those results with the perceptions of peers who have little or no awareness of those groups or entities. Consider questions such as: 
  • Can you get an ‘unbiased’ view of any person or brand through a standard Google search? How would you know? 
  • What do you do when you discover that online content about a person or brand is false or misleading?
  • Have students use the same search terms to search for information on a topic. Compare the differences in their search results and discuss the possible reasons for these differences (e.g., personalization of search results, search history, location, search engine).  
  • Examine how tech companies like Google, Facebook, and Twitter manage their reputations and represent themselves (for example, through branding and messaging). Rhetorical analysis can be useful for guiding this process.

Further Reading