AI Alignment Handbook: Toxicity
In this video, as part of the Trustwise AI Alignment Series, the Toxicity metric is discussed, highlighting its importance in AI Alignment, and addressing the diverse and dynamic needs of businesses. The Toxicity metric evaluates whether a given text contains toxic, offensive content, and identifies the categories of toxicity seen. Examples of the Toxicity metric are seen, demonstrating that a variety of levels of toxicity and toxic styles can be identified.
Trustwise API is a powerful tool for developers, enabling them to easily integrate and leverage these metrics to improve the performance of LLM-powered AI applications across any cloud environment.
Don't forget to share your thoughts in the comments below, and check out the rest of our series for a comprehensive understanding of AI Alignment.
Chapters:
0:00 Introduction
0:09 Toxicity Detection in AI Alignment
0:28 Toxicity Detection Methodology
1:08 Examples
2:08 Trustwise API Capabilities
2:34 Technical Papers and Social Media
Technical Content:
AI Alignment: A Comprehensive Survey - https://arxiv.org/abs/2310.19852
RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models - https://arxiv.org/abs/2009.11462
Unveiling the Implicit Toxicity in Large Language Models - https://arxiv.org/abs/2311.17391
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