Community Empowerment through Location-Based AR: The ThΓ‘mien Ohlone AR Tour
April 11, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Kai Lukoff, Xinqi Zhang
arXiv ID
2504.09010
Category
cs.HC: Human-Computer Interaction
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Community empowerment is the process of enabling communities to increase control over their narratives, resources, and futures. In HCI and design, this social challenge centers on helping marginalized groups gain agency through technology and design interventions. For Indigenous communities in particular, empowerment means not only representation but sovereignty in how their stories are told and by whom. Location-based augmented reality (AR) offers a novel opportunity to address this challenge. By overlaying digital content onto physical places, AR can spatially anchor community narratives in the real world, allowing communities to re-tell the story of a place on their own terms. Such site-specific AR experiences have already been used to reveal hidden histories, re-imagine colonial monuments, and celebrate minority cultures. The affordances of XR - particularly ARΕ spatial interaction and immersive storytelling - make it a promising tool for cultural continuity and community activism. In this position paper, we focus on how these XR affordances can empower communities, using the ThΓ‘mien Ohlone AR Tour as a case study. We outline why traditional digital interventions fall short of true empowerment, how AR's immersive qualities uniquely support Indigenous self-determination, insights from co-designing the Ohlone AR Tour, and future directions to scale such efforts responsibly.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted