This learning session, led by a librarian, is for first-year community college students in an academic library setting. The intention of this session is to scaffold onto existing research writing skills acquired in previous education, as well as use of popular video sharing platforms to obtain information, like TikTok. Informative videos produced by everyday people are a growing form of intellectual connection between all audiences and scholarly sources based on relatability, as well as visibility of marginalized issues larger news organizations do not address. When the information messenger is familiar yet dynamic in their presentation and provides information that the public is not informed on, viewers are more inclined to listen than if it were just a research paper or a scholarly representative of a research community. There are, however, citation issues and basic research principles missing in several of these videos, based solely on most video sharing platform’s intention to obtain engagement, not to responsibly inform/educate its users. As researchers, it is crucial to discern engagement-intended, incendiary content with informative, well-researched content that our neighbors are making, even if their intentions are good.

Algorithms are not neutral but this does not mean they are not useful tools for research. In this workshop on algorithmic bias, student learn how algorithms can perpetuate bias and discrimination and how to critically evaluate their search results.

This algorithmic literacy workshop puts a new spin on media literacy by moving beyond fake news to examine the algorithms that shape our online experiences and how we encounter information in our everyday lives.

We use Google every day, but we do really understand why we get certain results? This event will explain what an algorithm is, how search engines use them, and how bias exists in our search results. Attendees will have a chance to reflect on the ways biased results can echo larger biases for representation in society.  Access this site at your convenience at: https://jmu.libwizard.com/f/algorithms-bias

Co-creators: Malia Willey and Alyssa Young.

This assignment was created for a credit bearing course for first year students. It's designed to help students take what they've learned about algorithmic bias from the course lectures and readings and apply it to their own search practices. They also critically analyze search results for advertisements and compare DuckDuckGo to Google. [You could also look at this assignment as an adaptation of Jacob Berg's wonderful, "Googling Google," assignment at https://www.projectcora.org/assignment/googling-google-search-engines-ma... ]

This workshop delivers an action-oriented introduction to personal data privacy designed for new college students. The session is designed to reveal the systems in place to collect and analyze online behavioral data, and to unveil the real-world consequences of online profiling in contexts like sentiment shaping, consumer preferences, employment, healthcare, personal finance, and law enforcement. In lieu of a prescriptive approach, students analyze case studies to observe how online behaviors impact real-world opportunities and reflect on the benefits and risks of technology use to develop purposeful online behaviors and habits that align with their individual values. Developing knowledge practices regarding privacy and the commodification of personal information and embodying the core library values of privacy and intellectual freedom, the workshop promotes a proactive rather than reactive approach and presents a spectrum of privacy preferences across a range of contexts in order to respect students’ autonomy and agency in personal technology use.

This 30-minute activity was a quick introduction to algorithmic bias and the importance of critically evaluating search engine results. Algorithms increasingly shape modern life and can perpetuate bias and discrimination. In pairs, students analyzed the results from Google Image searches and Google Autocomplete suggestions. This activity was based on “Algorithms of Oppression: How Search Engines Reinforce Racism,” by Safiya Umoja Noble. This lesson plan was Part 1 of an hour-long workshop that also included a 30 minute Google Scholar activity. Please see Jennifer Masanaga's Google Scholar activity for Part 2: https://www.projectcora.org/assignment/exploring-google-scholar-summer-b...