Toward an Embrace of Empathy: AI Literacy, The Digital Divide, Labor, and the Environment
Type of Presentation
Poster Session
Conference Strand
Ethics in Information
Target Audience
Higher Education
Second Target Audience
Higher Education
Location
Common Area
Relevance
This project relates to information literacy because it addresses aspects of social justice that are often neglected when addressing what it means to be "information literate." Specifically, it addresses how considerations of labor, environmental impacts, and the digital divide need to be addressed when teaching AI literacy.
Proposal
The widespread adoption and use of generative AI has elicited varying definitions of AI literacy. While some scholars opine that AI literacy is a subset of information literacy, others understand it as a unique field. Regardless of how AI literacy is defined, it is intrinsically intertwined with information literacy; AI literacy competencies cannot be achieved without a foundation in critical thinking, digital and media literacy skills, as well as knowledge of socio-cultural and historical contexts in which AI systems are developed, accessed, utilized and deployed. Accordingly, this poster presentation provides a foundational overview of new considerations for AI literacy: the digital divide, labor practices, and environmental considerations. Attention is given to the digital divide because AI is rapidly exasperating extant effects of the move from analog to digital materials, greatly disparaging those without AI training in the job market. Labor practices are mentioned because AI companies have, as reported in various news sources, outsourced AI dataset training to workers who are paid low wages. Finally, environmental considerations are addressed by discussion of how AI currently requires a substantial amount of fresh water to maintain its servers. By providing foundational social justice considerations for AI literacy, the authors hope to elicit a dialogue that furthers scholarship and research on the social justice aspects of AI literacy.
Short Description
This presentation provides a foundational overview of the intersection of social justice and AI literacy, specifically regarding the digital divide, labor practices, and environmental considerations. By exploring these considerations, the authors hope to inspire scholarly paradigms and discourse on the intersection of AI literacy, information literacy, and social justice.
Keywords
Ai Literacy, Information Literacy, Social Justice
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
Reagan, Kevin J.; Swaringen, Jessica L.; and Coates, Kay, "Toward an Embrace of Empathy: AI Literacy, The Digital Divide, Labor, and the Environment" (2025). Georgia International Conference on Information Literacy. 17.
https://digitalcommons.georgiasouthern.edu/gaintlit/2025/2025/17
Toward an Embrace of Empathy: AI Literacy, The Digital Divide, Labor, and the Environment
Common Area
The widespread adoption and use of generative AI has elicited varying definitions of AI literacy. While some scholars opine that AI literacy is a subset of information literacy, others understand it as a unique field. Regardless of how AI literacy is defined, it is intrinsically intertwined with information literacy; AI literacy competencies cannot be achieved without a foundation in critical thinking, digital and media literacy skills, as well as knowledge of socio-cultural and historical contexts in which AI systems are developed, accessed, utilized and deployed. Accordingly, this poster presentation provides a foundational overview of new considerations for AI literacy: the digital divide, labor practices, and environmental considerations. Attention is given to the digital divide because AI is rapidly exasperating extant effects of the move from analog to digital materials, greatly disparaging those without AI training in the job market. Labor practices are mentioned because AI companies have, as reported in various news sources, outsourced AI dataset training to workers who are paid low wages. Finally, environmental considerations are addressed by discussion of how AI currently requires a substantial amount of fresh water to maintain its servers. By providing foundational social justice considerations for AI literacy, the authors hope to elicit a dialogue that furthers scholarship and research on the social justice aspects of AI literacy.
