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.- Anthology ID:
- 2022.woah-1.3
- Volume:
- Proceedings of the Sixth Workshop on Online Abuse and Harms (WOAH)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, Washington (Hybrid)
- Venue:
- WOAH
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 24–28
- Language:
- URL:
- https://aclanthology.org/2022.woah-1.3
- DOI:
- 10.18653/v1/2022.woah-1.3
- Cite (ACL):
- Siddhartha Datta, Konrad Kollnig, and Nigel Shadbolt. 2022. GreaseVision: Rewriting the Rules of the Interface. In Proceedings of the Sixth Workshop on Online Abuse and Harms (WOAH), pages 24–28, Seattle, Washington (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- GreaseVision: Rewriting the Rules of the Interface (Datta et al., WOAH 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.woah-1.3.pdf