Virtual Takeovers in the Metaverse: Interrogating Power in Our Past and Future(s) with Multi-Layered Narratives
April 23, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Heather Snyder Quinn, Jessa Dickinson
arXiv ID
2404.15108
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Mariah is an augmented reality (AR) mobile application that exposes power structures (e.g., capitalism, patriarchy, white supremacy) through storytelling and celebrates acts of resistance against them. People can use Mariah to "legally trespass" the metaverse as a form of protest. Mariah provides historical context to the user's physical surroundings by superimposing images and playing stories about people who have experienced, and resisted, injustice. We share two implementations of Mariah that raise questions about free speech and property rights in the metaverse: (1) a protest against museums accepting "dirty money" from the opioid epidemic; and (2) a commemoration of sites where people have resisted power structures. Mariah is a case study for how experimenting with a technology in non-sanctioned ways (i.e., "hacking") can expose ways that it might interact with, and potentially amplify, existing power structures.
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