algorithmic bias

Assignment

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.

Assignment

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.

Assignment

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.

Assignment

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.

Assignment

This workshop delivers an action-oriented introduction to personal data privacy designed for new college students.

Assignment

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.