Clio stands for Claude insights and observations, and it's a tool that helps us understand the different use cases for which people are using Claude, showing high-level aggregate clusters of usage.

Clio allows us to analyze real-world usage of our models, helping us design more thoughtful evaluations that match real-world use cases.

Clio enables us to evaluate the relevance of our models in real-world scenarios, ensuring they provide accurate and unbiased information.

Clio has shown that people use Claude in subjective settings, such as seeking relationship or health advice, which raises important questions about the values AI should represent in these contexts.

Clio enhances our top-down safety approach by allowing us to identify blind spots in user traffic that may not have been anticipated when establishing policies.

Clio helps us understand the risks associated with AI models by revealing how they are being used in various applications, including scientific research and cybersecurity.

During the development of Clio, we recognized the importance of understanding how users interact with AI during elections, including both factual and subjective inquiries.

The way Clio works is by processing real-world conversations with a language model to extract high-level summaries and group related answers, allowing us to understand user intent without reading raw conversations.

We are excited to explore how Clio can help us understand the subjective use cases of AI and ensure models represent diverse viewpoints.