Empirical Analysis of Multi-Task Learning for Reducing Model Bias in Toxic Comment Detection

Understand

With the recent rise of toxicity in online conversations on social media platforms, using modern machine learning algorithms for toxic comment detection has become a central focus of many online applications.

• Researchers and companies have developed a variety of models to identify toxicity in online conversations, reviews, or comments with mixed successes.
• However, many existing approaches have learned to incorrectly associate non-toxic comments that have certain trigger-words (e.g.
• gay, lesbian, black, muslim) as a potential source of toxicity.