Introducing Anthropic Interviewer \ Anthropic

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:
Career adaptation. Trucking dispatcher: “I'm always trying to figure out things that humans offer to the industry that can't be automated and really hone in on that aspect like the personalized human interactions. However, that is not something that I think will be necessary in the long run. I'm still trying to figure out what skills would be good to work on that AI can't ‘take over.’”
Societal perspectives. Office assistant: “It's a tool to me like a computer was, or a type writer was in the day—computers didn't get rid of mathematicians, they just made them able to do more and that is where I see AI going in the best possible future.”
Writing independence. Salesperson: “I hear from colleagues that they can tell when email correspondence is AI generated and they have a slightly negative regard for the sender. They feel slighted that the sender is ‘too lazy’ to send them a personal note and push it onto AI to do it.”
Educational integration. Special education teacher: “I am hoping that AI will be a more collaborative partner that will help me better manage my time and help me expand creatively so I can offer my students a wide variety of activities and assignments that I may not have been able to come up with on my own.”
Example quotations from professionals in the general workforce, organized by topic. This research aims to both unpack the optimism and navigate the underlying anxieties to better understand how AI is actually reshaping work across different professional contexts.
Control boundaries. Gamebook writer: “During these storytelling sessions, I would say that there's only the illusion of collaboration for the most part… there’s rarely a point where I’ve really felt like the AI is driving the creative decision-making.”
Workflow automation. Social media manager: “I’m less stressed, honestly. It has created a ton of efficiency for me so I can focus on my favorite aspects of the job (filming and editing)”.
Writer displacement. Creative fiction writer: “A novel written by AI might have a great plot and be technically brilliant. But it won’t have the deeper nuances that only a human can weave throughout the story.”
Music production. Music producer: “Sometimes, when it comes time to add lyrics, I’ll ask ChatGPT or Claude for lists of interesting word pairings. Just getting a long list to try out over the instrumental often leads to finding a hook or at least a seed for a song idea.”
Example quotations from creatives, organized by topic.
Security concerns. Medical scientist: “Our confidence in AI just isn’t high enough at the moment to trust it with our data. We’re also a commercial entity so there’s a bit of concern over confidentially with data that we might share with an AI system.”
Research assistance. Molecular biologist: “If AI could integrate and normalize all this data in a single repository, it could be a very exciting thing for biological discovery. You could see how expression dynamics change across cell models, tissue types, disease states, and more.”
Content verification. Economist: “What I would really like from an AI would be the ability to accurately grab information, summarise it and use it to write the core of a funding application. AI generally writes well; the problem now is that I just can’t rely on it not hallucinating, or to put it bluntly, lying.”
Code development. Food scientist: “Honestly I wouldn’t have known how to help my student with her code if something was off without AI tools.”
Example quotations from scientists, organized by topic.
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 par