Artificial Intelligence (AI) for Business Librarians

AI Literacy

What is AI Literacy?   AI literacy as a set of competencies that allows users to critically evaluate AI technology, communicate and work with AI in an effective manner.  When we talk about AI Literacy from an information science standpoint, we can think of it as analogous to media literacy or digital literacy, and a subset of Information Literacy.

AI literacy is just beginning to be formed.  But at this stage we know that it will encompass asking technical questions such as "how does AI work?" "How does AI compare as a tool to other types of searches?" and "How can I best use AI to reach my goals?" (Klein, 2023).  AI literacy will also include understanding ethical and social justice implications of current AI models, as well as practical skills in teaching and using AI. (Klein, 2023).   

Reference:

Klein, A. (May, 2023). AI literacy, explained. Education Week.  https://www.edweek.org/technology/ai-literacy-explained/2023/05

Being able to critically evaluate AI and its uses and responses is a process that involves many aspects of information literacy.

On the next pages this guide explores the following aspects of critical evaluation:

1. Evaluating AI results for credibility and accuracy
2. Evaluation the AI process for transparency, how much source data does a particular AI tool or result provide in order to apply Information Literacy standards and tests to the results
3. Evaluating the AI tool for fairness and bias
4. Understanding the ethical and practical implications of the AI tool in terms of privacy, bias, plagiarism, copyright and ownership issues.

AI Literacy can be an extension of Information Literacy practices already being used.  

"The Framework provides librarians and disciplinary faculty with a customizable way to provide information literacy instruction that meets the needs of students and enables them to become participants in the information that they are producing (not just consuming). Because of the Framework’s flexible nature, librarians can incorporate new technology, like ChatGPT, more easily into their instruction." (James, A.B. & Hampton Filgo, E, 2023)

Below are knowledge practices from the ACRL Framework mapped onto AI literacy queries.

1. Authority is Constructed and Contextual

• Are responses generated by AI transparent enough to evaluate the source material to determine authority?
• Does the response give information on the source author(s) subject expertise, social position, or special experience?
• Does the response give transparency on the tools and research methods used to provide response material, for the purposes of helping to determine authority?

2. Information Creation as a Process

• Are responses generated by AI transparent enough to allow the user to evaluate how the source material was created?
• Does the response give information on the source format?
• Do users understand the AI's own creation process to transform datasets and source material into generated responses?

3. Information has Value

• Are responses generated by an AI influenced by its value as a commercial product?
• Do the responses reflect any biases or omissions causes by its training datasets?
• How are AI products using the information inputted into them as queries?
• Are the responses returned by AI consistent with copyright and owner's rights over source materials?

4. Research As Inquiry

• Are responses generated by an AI on a specific inquiry enough to help the researchers understand the whole field of inquiry to identify gaps or scope of investigation?
• Will additional sources be needed?
• Are responses inclusive enough to allow for analysis by the researcher?

5. Scholarship as Conversation

• Do responses by the AI give enough information to correctly and fully cite each contributor to ideas or claims?
• Does the response give the researcher perspective on how a particular perspective fits into the scholarly conversation?
• Does the use of AI invite the researcher to consider themselves as part of the scholarly conversation?

6. Searching as Strategic Exploration

• Does the researcher have the tools needed to understand how to engineer a query prompt to get relevant results?
• Is the researcher using an AI tool with access to the resources needed to provide relevant answers?
• Does the AI response point the researcher to further sources?