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Artificial Intelligence + ACRL Frameworks

This libguide explores the integration of generative AI with the Framework for Information Literacy. It examines authority, information creation, value, research inquiry, and scholarship as conversation in relation to generative AI.

Scholarship as Conversation

Communities of scholars, researchers, or professionals engage in sustained discourse with new insights and discoveries occurring over time as a result of varied perspectives and interpretations.

—Framework for Information Literacy for Higher Education, Page 20

Scholarship as conversation: Comparison

How does each system encourage scholarly communication?​

How does each system encourage scholarly communication?​

Scholarly

A review of literature and bibliography situates the discussion within the community of scholars.​

Generative AI

The corpus is consulted to help generate terms that are regularly deployed when answering a prompt.​

How does each system encourage feedback?​

How does each system encourage feedback?​

Scholarly

Feedback is solicited by either a board of editors or by undergoing the peer review process. This feedback is incorporated into the final output.​

Generative AI

The corpus is trusted to provide accurate and complete information on the topic. A user may also rate their interaction with the LLM.​

How does each system respond to erroneous output?​

Scholarly

A journal may issue a retraction or correction to articles if issues with veracity have been reported to the publication.​

Generative AI

Since Generative AI is a closed system, improvements are not disclosed. Chat history may not be subject to correction.​