Rooted in the Collective: A Culturally Situated Artificial Intelligence (AI) Education Workshop For Urban Farmers

This paper describes our experiences related to a culturally situated Artificial Intelligence (AI) education workshop for urban farmers. The farmers explored the concept of AI and its implications in the context of their own farm. They engaged in hands-on activities, including using traditional sensemaking practices in conjunction with sensor technology to collect contextual data. They then used a tangible educational tool: a corkboard with push pins and images to build tactile AI models based on their farm data. Throughout this process, they discussed their hopes and desires regarding AI in farming, and their concerns about AI technologies. The perspectives of the urban farmers reveal their preference for AI systems that are contextual, integrate community values, Indigenous knowledge, and environmental concerns, and are rooted in community ownership of data. Our report provides a starting point for conducting future workshops that involve 'critical participatory design' of AI technologies to promote AI literacies rooted in the community.

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Publication Details

Published
2025-02-12
DOI
https://doi.org/10.1145/3641554.3701898
Citations
2
Primary Topic
Service-Learning and Community Engagement
Type
article
Field-Weighted Citation Impact
17.85
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article

Rooted in the Collective: A Culturally Situated Artificial Intelligence (AI) Education Workshop For Urban Farmers

Sai Swaminathan, Rhema Linder, Srinayana Patil, Sukanya Kannan Moudgalya et al.
2 citations
Service-Learning and Community Engagement
17.85
article

Rooted in the Collective: A Culturally Situated Artificial Intelligence (AI) Education Workshop For Urban Farmers

Sai Swaminathan, Rhema Linder, Srinayana Patil, Sukanya Kannan Moudgalya, Carmen Palileo
article en
2 citations

Abstract

This paper describes our experiences related to a culturally situated Artificial Intelligence (AI) education workshop for urban farmers. The farmers explored the concept of AI and its implications in the context of their own farm. They engaged in hands-on activities, including using traditional sensemaking practices in conjunction with sensor technology to collect contextual data. They then used a tangible educational tool: a corkboard with push pins and images to build tactile AI models based on their farm data. Throughout this process, they discussed their hopes and desires regarding AI in farming, and their concerns about AI technologies. The perspectives of the urban farmers reveal their preference for AI systems that are contextual, integrate community values, Indigenous knowledge, and environmental concerns, and are rooted in community ownership of data. Our report provides a starting point for conducting future workshops that involve 'critical participatory design' of AI technologies to promote AI literacies rooted in the community.

Knoxville College (US), University of Tennessee at Knoxville (US)
Openalex Percentile: Top 2%
Service-Learning and Community Engagement
17.85
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