Type of Presentation
Poster Session
Conference Strand
Ethics in Information
Target Audience
Higher Education
Second Target Audience
K-12
Relevance
Artificial Intelligence is changing faster than any of us can keep up. It's not only students asking about the appropriateness of its use, how to cite it, when to cite it, and other rules dealing with the information and products being created with AI. Faculty, too, are asking these questions, and many are turning to their librarians expecting answers. This poster will explore the ethical use of AI in creating information products (such as papers, OER materials, images, etc) and provide tips for teaching librarians how to address and approach some of these issues with their faculty and within their instruction sections.
Proposal
Exploring the Ethical Use of AI in Information Product Creation: A Guide for Librarians
The rapid advancement of artificial intelligence (AI) has revolutionized the way information products are created, raising ethical considerations that demand the attention of educators, researchers, and librarians. This poster presentation aims to delve into the ethical aspects of AI-generated information products, such as papers, Open Educational Resources (OER) materials, images, etc., and to provide practical tips for teaching librarians on how to navigate and address citation rules associated with these products.
Objectives:
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Understanding AI in Information Product Creation: Explore the key principles behind AI algorithms and their role in generating information products. Discuss the ethical implications of AI in content creation, emphasizing transparency, accountability, and bias.
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Ethical Considerations: Highlight the ethical challenges associated with AI-generated content, including issues related to authorship, intellectual property, and potential biases. Examine how librarians can play a crucial role in guiding users through these considerations.
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Guidelines for Ethical Use: Provide a set of guidelines for librarians to educate users on the ethical use of AI-generated information products. Address topics such as proper attribution, transparency in methodology, and the importance of critical evaluation of AI-generated content.
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Citation Rules and Best Practices: Discuss the evolving landscape of citation rules for AI-generated content and propose best practices for librarians when teaching users how to cite such materials. Explore potential citation styles and standards that can be adapted to accommodate AI-generated content.
In conclusion, this poster presentation aims to empower librarians with the knowledge and tools needed to navigate the ethical landscape of AI-generated information products. By understanding the principles, addressing ethical considerations, and providing practical guidelines for citation, librarians can play a pivotal role in promoting responsible and transparent practices in the use of AI-generated content within the academic and research communities.
Short Description
Dive into the ethical dimensions of AI in information product creation with this poster presentation. Explore the challenges, guidelines, and best practices for librarians, ensuring responsible use and citation of AI-generated content. Discover real-world examples to help empower librarians to navigate this evolving landscape and add to their toolkit for teaching faculty and students.
Keywords
AI, Artificial Intelligence, Ethical Use, Product Creation
Publication Type and Release Option
Presentation (Open Access)
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Cannon-Rech, Dawn N., "Exploring the Ethical Use of AI in Information Product Creation: A Guide for Librarians" (2024). Georgia International Conference on Information Literacy. 16.
https://digitalcommons.georgiasouthern.edu/gaintlit/2024/2024/16
Exploring the Ethical Use of AI in Information Product Creation: A Guide for Librarians
Exploring the Ethical Use of AI in Information Product Creation: A Guide for Librarians
The rapid advancement of artificial intelligence (AI) has revolutionized the way information products are created, raising ethical considerations that demand the attention of educators, researchers, and librarians. This poster presentation aims to delve into the ethical aspects of AI-generated information products, such as papers, Open Educational Resources (OER) materials, images, etc., and to provide practical tips for teaching librarians on how to navigate and address citation rules associated with these products.
Objectives:
-
Understanding AI in Information Product Creation: Explore the key principles behind AI algorithms and their role in generating information products. Discuss the ethical implications of AI in content creation, emphasizing transparency, accountability, and bias.
-
Ethical Considerations: Highlight the ethical challenges associated with AI-generated content, including issues related to authorship, intellectual property, and potential biases. Examine how librarians can play a crucial role in guiding users through these considerations.
-
Guidelines for Ethical Use: Provide a set of guidelines for librarians to educate users on the ethical use of AI-generated information products. Address topics such as proper attribution, transparency in methodology, and the importance of critical evaluation of AI-generated content.
-
Citation Rules and Best Practices: Discuss the evolving landscape of citation rules for AI-generated content and propose best practices for librarians when teaching users how to cite such materials. Explore potential citation styles and standards that can be adapted to accommodate AI-generated content.
In conclusion, this poster presentation aims to empower librarians with the knowledge and tools needed to navigate the ethical landscape of AI-generated information products. By understanding the principles, addressing ethical considerations, and providing practical guidelines for citation, librarians can play a pivotal role in promoting responsible and transparent practices in the use of AI-generated content within the academic and research communities.