Measuring real-world impact
How does AI affect people’s wellbeing, reasoning, and relationships? Our researchers study how people interact with Claude at scale, and interview them directly about their experience. We publish what we learn, and work to support outside researchers studying these questions.
Improving our models and products
Our research identifies ways Claude can serve people better. We act on what we learn by integrating these findings into changes to Claude’s behavior, new evaluations, and product improvements.
What 81,000 people want from AI
We invited Claude.ai users to share how they use AI, what they dream it could make possible, and what they fear it might do. Nearly 81,000 people participated—the largest and most multilingual qualitative study of its kind. Here's what we found.
Read moreEnabling independent research on how people use Claude
We ran a pilot giving external researchers access to aggregate, real-world Claude usage data. In this post, we share high-level results and what we learned running this pilot.
Read moreMeasuring AI agent autonomy in practice
We analyzed millions of human-agent interactions across both Claude Code and our public API using our privacy-preserving tool, to ask: How much autonomy do people grant agents? How does that change as people gain experience? Which domains are agents operating in? And are the actions taken by agents risky?
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ARTICLES
What do you want from AI?
Enabling independent research on how people use Claude
Claude’s values across models and languages
Results from the first Anthropic Public Record
How people ask Claude for personal guidance
Anthropic Education Report: The AI Fluency Index
Measuring AI agent autonomy in practice
Introducing Anthropic Interviewer: What 1,250 professionals told us about working with AI
How AI is transforming work at Anthropic
Measuring political bias in Claude
Anthropic Education Report: How educators use Claude
Anthropic Economic Index: AI’s impact on software development
Values in the wild: Discovering and analyzing values in real-world language model interactions
Anthropic Education Report: How university students use Claude
Anthropic Economic Index: Insights from Claude 3.7 Sonnet
Clio: A system for privacy-preserving insights into real-world AI use
Evaluating feature steering: A case study in mitigating social biases
Measuring the persuasiveness of language models
Evaluating and mitigating discrimination in language model decisions
Collective Constitutional AI: Aligning a language model with public input
Towards measuring the representation of subjective global opinions in language models
The capacity for moral self-correction in large language models
Red teaming language models to reduce harms: methods, scaling behaviors, and lessons learned
Predictability and Surprise in Large Generative Models
Explore work from other teams
Alignment
47 posts
Works to understand the risks of AI models and develop ways to ensure future ones remain helpful, honest, and harmless.
Economics
25 posts
Studies and monitors the impact of AI systems on individuals, firms, and economies.
Engineering
27 posts
Builds the infrastructure and systems that make Claude reliable and trustworthy.
Frontier Red Team
33 posts
Stress-tests AI systems to understand the full extent of their current capabilities and anticipate what comes next.
Interpretability
35 posts
Studies how large language models work internally as a foundation for AI safety.
Science
18 posts
Explores how AI can increase the pace of scientific progress through both research and collaborations.
Societal Impacts
24 posts
Studies how AI affects people, both individually and collectively.
Alignment
47 posts
Works to understand the risks of AI models and develop ways to ensure future ones remain helpful, honest, and harmless.
Economics
25 posts
Studies and monitors the impact of AI systems on individuals, firms, and economies.
Engineering
27 posts
Builds the infrastructure and systems that make Claude reliable and trustworthy.
Frontier Red Team
33 posts
Stress-tests AI systems to understand the full extent of their current capabilities and anticipate what comes next.
Interpretability
35 posts
Studies how large language models work internally as a foundation for AI safety.
Science
18 posts
Explores how AI can increase the pace of scientific progress through both research and collaborations.
Societal Impacts
24 posts
Studies how AI affects people, both individually and collectively.