SOURCE-LINKED INTELLIGENCE
Detoxifying Toxic Communication: A Design Science Approach to Responsible AI
Toxic language in digital workplaces such as pejoratives, sarcasm, condescension, and subtle incivility can erode trust, morale, and collaboration. Existing moderation tools primarily delete or block harmful messages, disrupting communication and offering no constructive resolution. This study adopts a Design Science Research approach to create a responsible AI artifact that detects and detoxifies toxic communication. The artifact integrates fine-tuned transformer-based classifiers (DistilBERT, DistilRoBERTa) with a generative detoxification model (mT0-XL-Detox-ORPO) that rewrites toxic text i
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T20:54:33.000Z
First collected: 2026-09-21T06:21:59.299Z. This is not the publication date.