Working with Color: How Color Quantization Can Aid Researchers of Problematic Information
August 06, 2024 Β· Declared Dead Β· π CSCW Companion
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Nina Lutz, Jordyn W. Padzensky, Joseph S. Schafer
arXiv ID
2408.03424
Category
cs.CY: Computers & Society
Cross-listed
cs.HC
Citations
8
Venue
CSCW Companion
Last Checked
5 months ago
Abstract
Analyzing large sets of visual media remains a challenging task, particularly in mixed-method studies dealing with problematic information and human subjects. Using AI tools in such analyses risks reifying and exacerbating biases, as well as untenable computational and cost limitations. As such, we turn to adopting geometric computer graphics and vision methods towards analyzing a large set of images from a problematic information campaign, in conjunction with human-in-the-loop qualitative analysis. We illustrate an effective case of this approach with the implementation of color quantization towards analyzing online hate image at the US-Mexico border, along with a historicist trace of the history of color quantization and skin tone scales, to inform our usage and reclamation of these methodologies from their racist origins. To that end, we scaffold motivations and the need for more researchers to consider the advantages and risks of reclaiming such methodologies in their own work, situated in our case study.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Computers & Society
π
π
The Cartographer
R.I.P.
π»
Ghosted
Artificial Intelligence: the global landscape of ethics guidelines
R.I.P.
π»
Ghosted
The role of artificial intelligence in achieving the Sustainable Development Goals
R.I.P.
π»
Ghosted
Green AI
R.I.P.
π»
Ghosted
Principles alone cannot guarantee ethical AI
R.I.P.
π»
Ghosted
Tackling Climate Change with Machine Learning
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