Introducing Anthropic Interviewer: What 1,250 professionals told us about working with AI

We’re launching a new tool, Anthropic Interviewer, to help understand people’s perspectives on AI. In this research post, we introduce the tool, describe a test of it on a sample of professionals, and discuss our early findings. We also discuss future work in this direction that we can now explore with the development of this tool and through partnerships with creatives, scientists, and teachers.

Millions of people now use AI every day. As a company developing AI systems, we want to know how and why they’re doing so, and how it affects them. In part, this is because we want to use people’s feedback to develop better products—but it’s also because understanding people’s interactions with AI is one of the great sociological questions of our time.

We recently designed a tool to investigate patterns of AI use while protecting our users’ privacy. It enabled us to analyze changing patterns of AI use across the economy . But the tool only allowed us to understand what was happening within conversations with Claude. What about what comes afterwards? How are people actually using Claude’s outputs? How do they feel about it? What do they imagine the role of AI to be in their future? If we want a comprehensive picture of AI’s changing role in people’s lives, and to center humans in the development of models, we need to ask people directly .

Such a project would require us to run many hundreds of interviews. Here, we enlisted AI to help us do so. We built an interview tool called Anthropic Interviewer. Powered by Claude, Anthropic Interviewer runs detailed interviews automatically at unprecedented scale, feeding its results back to human researchers for analysis. This is a new step in understanding the wants and needs of our users, as well as gathering data for the analysis of AI’s societal and economic impacts.

To test Anthropic Interviewer, we had it run 1,250 interviews with professionals—the general workforce (N=1,000), scientists (N=125), and creatives (N=125)—about their views on AI. We’re publicly releasing all interview data from this initial test (with participant consent) for researchers to explore; we provide our own analysis below. Briefly, here are some examples of what we found:

This initial test explored how workers integrate AI into their professional practice and how they feel about its role in their future. We ran interviews to produce qualitative data, and supplemented them with quantitative data from surveys where participants answered questions on their behavioral and occupational backgrounds. We also had a separate AI analysis tool read the interview transcripts and cluster together emergent, overarching themes from the unstructured data—for example, on the percentage of participants who mentioned a specific topic or expressed a specific view in their interview.