Which aspect of AI governance includes informing users about AI interactions?

The correct answer is centered around the concept of transparency and interpretability, which are essential aspects of AI governance. This aspect involves making AI systems understandable to users, which includes clear communication about how AI operates, the data it processes, and the decisions it makes. By informing users about these interactions, organizations foster trust and enable users to make informed decisions regarding their engagement with AI systems.

Transparency ensures that users are aware of how their data is utilized and the rationale behind AI-generated outcomes, which is crucial for maintaining ethical standards and accountability in AI applications. Interpretability refers to the ability to explain how and why decisions are made by AI systems in a way that is accessible to users, allowing them to comprehend and trust the technology better.

While accountability, privacy protection, and data minimization are also important elements of AI governance, they do not specifically focus on the user’s understanding of AI interactions. Accountability pertains to the responsibility of organizations in managing AI systems and their outcomes, privacy protection emphasizes safeguarding users' personal information, and data minimization involves limiting data collection to what is necessary. Each plays a role in a comprehensive governance framework, but transparency and interpretability directly address informing users about their interactions with AI.