Automated Content Moderation Using Transparent Solutions and Linguistic Expertise

Automated Content Moderation Using Transparent Solutions and Linguistic Expertise

Veronika Solopova

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Doctoral Consortium. Pages 7097-7098. https://doi.org/10.24963/ijcai.2023/823

Since the dawn of Transformer-based models, the trade-off between transparency and accuracy has been a topical issue in the NLP community. Working towards ethical and transparent automated content moderation (ACM), my goal is to find where it is still relevant to implement linguistic expertise. I show that transparent statistical models based on linguistic knowledge can still be competitive, while linguistic features have many other useful applications.
Keywords:
Natural Language Processing: NLP: Interpretability and analysis of models for NLP
AI Ethics, Trust, Fairness: ETF: Explainability and interpretability
Natural Language Processing: NLP: Applications