algorithmic literacy

Submitted by Shelby Hallman on March 26th, 2024
Share this on: 
Short Description: 

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.

Workshop Instructors: Shelby Hallman, Physical Sciences and Engineering Librarian; Ashley Peterson, Research & Instruction Librarian, Media and Data Literacy; Alexandra Solodkaya, Rothman Family Food Studies Librarian

Credits: This workshop was derived from LMU's Rise Against the Machines: Understanding Algorithmic Bias workshop. 

Attachments: 
AttachmentSize
UCLA_SRW_Fall23 Algorithmic Bias Workshop Slide Deck.pdfdisplayed 1108 times3.75 MB
Algo_Bias_UCLA_Fall_23_Lesson Plan.pdfdisplayed 985 times83.65 KB
Relevant links: 
Breaking the Code: Fall 2023 Slide Deck
Learning Outcomes: 
  • Students will be introduced to algorithmic bias concepts, focusing on machine learning and AI.
  • Students will understand the causes and implications of bias within algorithm development and use. 
  • Students will discuss strategies to cope with or critically engage with algorithms.
Discipline: 
Computer ScienceLibrary and Information Science

Individual or Group:

Ability Level:

Tags:

Course Context (e.g. how it was implemented or integrated): 

This workshop was held virtually, via Zoom. 

Assessment or Criteria for Success
Assessment Short Description: 
Formative assessment was conducted via the in-session activities and participation. Summative assessment was conducted via an end of session survey form.
Suggested Citation: 
Hallman, Shelby. "Breaking the Code: Understanding Algorithmic Bias." CORA (Community of Online Research Assignments), 2024. https://projectcora.org/assignment/breaking-code-understanding-algorithmic-bias.
Copyright icon to go along with copyright rules.
All assignments contributed to this site are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike United States License

Teaching Resource

RE:Search - Unpacking the Algorithms That Shape Our UX

Home for the IMLS Grant RE-72-17-0103-17 - “RE:Search” - Unpacking the Algorithms That Shape Our UX.

Submitted by Shelby Hallman on June 9th, 2022
Share this on: 
Short Description: 

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.

Attachments: 
AttachmentSize
Presentation_Rise Against the Machines_Algorithmic Bias Workshopdisplayed 1381 times3.65 MB
Lesson Plan_ Rise Against the Machines_ Understanding Algorithmic Bias Workshop.pdfdisplayed 950 times149.88 KB
Algorithm_Intervention_Spectrum_Activity.pdfdisplayed 691 times116.41 KB
Relevant links: 
Rise Against the Machines: Understanding Algorithmic Bias Workshop SlidesRise Against the Machines: Understanding Algorithmic Bias LibGuideActivity: Survival of the Best Fit GameSpring 2023 Workshop Slides
Learning Outcomes: 

•Students will be introduced to the machine bias inherent in algorithmic decision making, with a focus on information systems.

•Students will discuss the effects of algorithm bias in order to articulate how some individuals or groups of individuals may be misrepresented or systematically marginalized in search engine results.

•Students will develop an attitude of informed skepticism in order to critically evaluate search results. 

Discipline: 
Computer ScienceLibrary and Information Science

Information Literacy concepts:

Individual or Group:

Ability Level:

Tags:

Course Context (e.g. how it was implemented or integrated): 

Stand-alone workshop; co-curricular workshop. 

Assessment or Criteria for Success
Assessment Short Description: 
Formative assessment was conducted via the in-session activities. Summative assessment was conducted via an end of session survey form.
Collaborators: 
Susan Archambault
Elisa Acosta
Suggested Citation: 
Hallman, Shelby. "Rise Against the Machines: Understanding Algorithmic Bias." CORA (Community of Online Research Assignments), 2022. https://projectcora.org/assignment/rise-against-machines-understanding-algorithmic-bias.
Copyright icon to go along with copyright rules.
All assignments contributed to this site are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike United States License
Submitted by Alexandria Chisholm on October 14th, 2021
Share this on: 
Short Description: 

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.

Attachments: 
AttachmentSize
#ForYouWorkshopLessonPlan_Chisholm.pdfdisplayed 1828 times163.64 KB
AttentionAutonomyPlan_#ForYouWorkshop.pdfdisplayed 1189 times83.03 KB
Relevant links: 
#ForYou: Algorithms & the Attention Economy Workshop LibGuide#ForYou: Algorithms & the Attention Economy Workshop Slides
Learning Outcomes: 

By the end of the #ForYou: Algorithms & the Attention Economy workshop, students will be able to:

  1. describe recommender system algorithms in order to examine how they shape individuals' online experiences through personalization
  2. analyze their online behaviors and subsequent ad profiles in order to reflect on how they influence how individuals encounter, perceive, & evaluate information, leading to echo chambers & political polarization
  3. assess how their data is used to personalize their online experience in order to build algorithmic awareness & make informed, intentional choices about their information consumption
Discipline: 
Multidisciplinary

Information Literacy concepts:

Individual or Group:

Ability Level:

Tags:

Suggested Citation: 
Chisholm, Alexandria. "#ForYou: Algorithms & the Attention Economy." CORA (Community of Online Research Assignments), 2021. https://projectcora.org/assignment/foryou-algorithms-attention-economy.
Copyright icon to go along with copyright rules.
All assignments contributed to this site are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike United States License