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AI artifact developed to detect and rewrite toxic workplace communication

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new AI artifact using a Design Science Research approach to address toxic communication in digital workplaces. This artifact employs fine-tuned transformer models, DistilBERT and DistilRoBERTa, for accurate toxicity detection. It also integrates mT0-XL-Detox-ORPO, a generative model capable of rewriting toxic messages into non-offensive paraphrases while preserving their original meaning. The system aims to foster respectful discourse and maintain conversation continuity, offering a constructive alternative to traditional moderation tools that merely delete or block harmful content. AI

IMPACT This research offers a novel approach to content moderation, potentially improving workplace communication and trust by preserving meaning while neutralizing toxicity.

RANK_REASON The item is an academic paper detailing a new AI artifact and its technical evaluation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI artifact developed to detect and rewrite toxic workplace communication

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The item is an academic paper detailing a new AI artifact and its technical evaluation. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Hossein Arshadi Soufiani, Henry M. Kim, Hjalmar Turesson, Syed Mohammad Arham Noman, Anav Setia ·

    Detoxifying Toxic Communication: A Design Science Approach to Responsible AI

    arXiv:2609.00361v1 Announce Type: cross Abstract: 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 c…

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