Interpretable Toxicity Detection: A Concept-Based Approach

This research explores interpretable AI methods for identifying toxic content, a critical area for responsible AI deployment. Focusing on concept-based interpretability suggests a novel approach potentially improving transparency and understanding in toxicity detection models.

• •Focuses on improving the interpretability of toxicity detection models.
• •Employs a concept-based approach, offering a potentially novel perspective.
• •Addresses the ethical considerations surrounding AI and harmful content.