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AI Tools

What is AI Literacy?

AI Literacy is a set of competencies that enables individuals to critically evaluate AI technologies; communicate and collaborate effectively with AI; and use AI as a tool online, at home, and in the workplace.  …..  It’s important to understand and evaluate AI in areas like privacy/surveillance; misinformation; ethical decision-making, diversity, and bias when using AI technologies.  

Source:  Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings
of the 2020 CHI conference on human factors in computing systems
(pp. 1–16).



AI Literacy Includes a Knowledge of These Issues

AI output can include inaccuracies & hallucinations  

  • inaccuracies (completely wrong information)

  • completely fake people, events, and articles (hallucinations) 

  • A  mix of truth and fiction

AI output can include bias, resulting in discrimination - 

  • omission of facts and data 

  • algorithms  (Amazon hiring - see 

Potential for ethical issues such as plagiarism & copyright Infringement 

Potential for security & privacy issues 

Adapted from: Artificial Intelligence and Information Literacy. University of Maryland. Teaching and Learning Transformation Center.  Accessed March 7, 2024. 

Lateral Reading & Fact Checking

  1. Break down the AI Output.   Isolate specific, searchable claims. 

  2. Open a new tab and look for supporting pieces of information, verify sources (course readings, Omni, library databases, Google, Google Scholar, Wikipedia)

  3. Critically evaluate your AI prompt/question

  4. Re-prompt AI if needed  

  5. Keep checking!


Adapted from: Artificial Intelligence and Information Literacy. University of Maryland.
Teaching and Learning Transformation Center.
Accessed March 7, 2024. 

Algorithmic Literacy

Algorithm literacy can be defined as being aware of the use of algorithms in online applications, platforms, and services, knowing how algorithms work, being able to critically evaluate algorithmic decision-making as well as having the skills to cope with or even influence algorithmic operations. 

Source: Dogruel, L., Masur, P., & Joeckel, S. (2022). Development and validation of an algorithm literacy scale for internet users. Communication Methods and Measures, 16(2), 115–133.

AI Tool Evaluation


  • Can you find information about the data that the tool was trained on?   

  • What are the recommended ways to use it?

  • Can you find examples of positive applications, but also examples of its limitations?

  • Can it draw upon up-to-date information or does it have a cut-off-date? 


The ROBOT Test

Use this tool when reading about AI tools to help consider the legitimacy of the technology: 

Reliability  - check credentials of author, is there a bias? Is it a reliable source?  Is it only partial information?

Objective - goal of AI and information being shared about it - to convince, inform or raise money? 

Bias - sources of bias? Ethical issues? Are these issues acknowledged by creators or users? 

Owner - who is the owner of the tool? Who has access?  

Type - Which subtype of AI is it?  Information system it relies on?  Human intervention?