Which feature of the Einstein Trust Layer is specifically designed to detect inappropriate or harmful AI-generated content?

The feature designed to detect inappropriate or harmful AI-generated content within the Einstein Trust Layer is Toxicity Detection. This functionality plays a crucial role in ensuring that the content generated by AI models adheres to community standards and does not propagate harmful language or misinformation.

Toxicity Detection works by analyzing the text for various indicators of harmfulness, such as hate speech, harassment, and other toxic behaviors. By incorporating this feature, organizations can mitigate risks associated with the deployment of AI-generated content in their applications, ultimately promoting a safer and more favorable user experience.

The other options, while related to data management or privacy, do not specifically focus on the detection of inappropriate content. Dynamic Grounding is primarily concerned with enhancing AI understanding by grounding responses in real-world context. Data Masking relates to protecting sensitive information by obscuring data, and Auditing focuses on examining the usage and performance of AI, rather than the content it produces.