Salesforce AI Specialist Practice Exam

The correct answer is that generative AI audit data includes features related to both data masking and toxicity scores within the context of the Einstein Trust Layer.

The Einstein Trust Layer is designed to ensure that AI applications built on Salesforce uphold privacy and ethical standards. Data masking is an important feature that helps protect sensitive information by transforming or obscuring it in a way that maintains usability while safeguarding privacy. This practice is pivotal for maintaining compliance with data protection regulations while still allowing organizations to leverage the power of AI.

Toxicity scores contribute to this framework by assessing the content generated or processed by AI systems for harmful or negative implications. They serve to evaluate whether the generated content adheres to ethical guidelines and is free from bias or harmful language. By tracking these scores, organizations can take appropriate measures to mitigate risks associated with AI outputs, ensuring that the applications align with societal standards and company values.

Together, data masking and toxicity scores create a robust auditing mechanism that reflects the commitment of the Einstein Trust Layer to responsible AI use. This integrative approach promotes trust among stakeholders while facilitating the responsible deployment of AI technologies within Salesforce platforms.