@inproceedings{datta-etal-2022-greasevision,
title = "{G}rease{V}ision: Rewriting the Rules of the Interface",
author = "Datta, Siddhartha and
Kollnig, Konrad and
Shadbolt, Nigel",
editor = "Bartolo, Max and
Kirk, Hannah and
Rodriguez, Pedro and
Margatina, Katerina and
Thrush, Tristan and
Jia, Robin and
Stenetorp, Pontus and
Williams, Adina and
Kiela, Douwe",
booktitle = "Proceedings of the First Workshop on Dynamic Adversarial Data Collection",
month = jul,
year = "2022",
address = "Seattle, WA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.dadc-1.2",
doi = "10.18653/v1/2022.dadc-1.2",
pages = "7--22",
abstract = "Digital harms can manifest across any interface. Key problems in addressing these harms include the high individuality of harms and the fast-changing nature of digital systems. We put forth GreaseVision, a collaborative human-in-the-loop learning framework that enables end-users to analyze their screenomes to annotate harms as well as render overlay interventions. We evaluate HITL intervention development with a set of completed tasks in a cognitive walkthrough, and test scalability with one-shot element removal and fine-tuning hate speech classification models. The contribution of the framework and tool allow individual end-users to study their usage history and create personalized interventions. Our contribution also enables researchers to study the distribution of multi-modal harms and interventions at scale.",
}
Markdown (Informal)
[GreaseVision: Rewriting the Rules of the Interface](https://aclanthology.org/2022.dadc-1.2) (Datta et al., DADC 2022)
ACL
- Siddhartha Datta, Konrad Kollnig, and Nigel Shadbolt. 2022. GreaseVision: Rewriting the Rules of the Interface. In Proceedings of the First Workshop on Dynamic Adversarial Data Collection, pages 7–22, Seattle, WA. Association for Computational Linguistics.