AI Might Summarize, but it Can't Think: AI-assisted lit reviews
Practical strategies for teaching AI-assisted lit reviews while keeping human analysis and critical thinking central.
Practical strategies for teaching AI-assisted lit reviews while keeping human analysis and critical thinking central.
Algorithms are everywhere, and they have increasing power over what we consume (Amazon, Netflix, TikTok), who we date (“the apps”), and how we understand the world (Google, ChatGPT). So, what are algorithms, and how did they become so powerful? Who are the humans that create them, and why does it matter?
In this workshop, we will explore how algorithms can perpetuate bias and discrimination, and discuss some preventive strategies. It is open to learners of all backgrounds and experience.
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.
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-market-actors ]
This workshop delivers an action-oriented introduction to personal data privacy designed for new college students.
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.