Introduction
Anthropic has launched Anthropic Interviewer, a groundbreaking research tool powered by Claude that automatically conducts detailed interviews at unprecedented scale to understand how people use artificial intelligence and how it affects their work and lives. This innovative approach represents a new step in understanding the wants and needs of AI users, as well as gathering data for analyzing AI's societal and economic impacts.
To test Anthropic Interviewer, the company conducted 1,250 interviews with professionals across three groups: the general workforce (N=1,000), scientists (N=125), and creatives (N=125). The research reveals fascinating insights about how different professionals are navigating the AI revolution, from optimistic productivity gains to concerns about job displacement and professional identity.
What is Anthropic Interviewer?
A New Research Methodology
Anthropic Interviewer is an interview tool powered by Claude that runs detailed interviews automatically at unprecedented scale, feeding its results back to human researchers for analysis. This represents a significant advancement in qualitative research methodology:
Key Features:
- Automated Interviewing: Uses AI to conduct detailed, conversational interviews
- Unprecedented Scale: Can interview hundreds or thousands of participants
- Privacy Protection: Designed to investigate patterns of AI use while protecting user privacy
- Human Analysis: Results are fed back to human researchers for interpretation
- Comprehensive Insights: Captures both what happens in conversations with Claude and what comes afterwards
The Research Gap It Addresses
Anthropic previously developed tools to analyze changing patterns of AI use across the economy, but these tools only allowed them to understand what was happening within conversations with Claude. Anthropic Interviewer addresses critical questions that couldn't be answered through conversation analysis alone:
Unanswered Questions:
- How are people actually using Claude's outputs?
- How do they feel about working with AI?
- What do they imagine the role of AI to be in their future?
- How is AI transforming professional identity and work practices?
Research Methodology
Study Design
The initial test of Anthropic Interviewer involved a comprehensive study of professional AI usage:
Participant Groups:
- General Workforce: 1,000 professionals from various industries
- Scientists: 125 researchers and academics
- Creatives: 125 professionals in creative fields
Research Approach:
- Participants were engaged through crowdworker platforms
- Interviews were conducted using Anthropic Interviewer
- All interview data was collected with participant consent
- Data is being publicly released for researchers to explore
Participant Experience
After the interviews, participants were surveyed on their interview experience:
Satisfaction Metrics:
- 97.6% of participants rated their satisfaction as 5 or higher (on a 1-7 scale)
- 49.6% gave the highest rating (7)
- 96.96% felt the conversation captured their thoughts well (5-7 rating)
- 99.12% said they would recommend this interview format to others
These remarkably positive ratings suggest that AI-conducted interviews can be effective and well-received by participants.
Key Research Findings
Overall Sentiment: Cautious Optimism
Across all three samples studied—the general workforce, scientists, and creatives—participants expressed predominantly positive sentiments about AI's impact on their professional activities. However, certain topics introduced pause, particularly around questions of personal control, job displacement, and autonomy.
Positive Themes:
- Productivity gains and efficiency improvements
- Workflow automation and time savings
- Enhanced creative capabilities
- Educational integration benefits
- Societal perspectives on AI as a tool
Concerns and Challenges:
- Career adaptation and skill development
- Writing independence and authenticity
- Control boundaries in creative work
- Writer displacement and creative identity
- Trust issues in scientific research
Findings by Professional Group
General Workforce: Preserving Professional Identity
Professionals in the general workforce revealed a clear pattern in how they're adapting to AI:
Key Insights:
- Preserve Identity-Defining Tasks: People want to preserve tasks that define their professional identity while delegating routine work to AI
- Future Vision: They envision futures where routine tasks are automated and their role shifts to overseeing AI systems
- Career Adaptation: Many are actively trying to figure out what skills to develop that AI can't "take over"
- Societal Perspectives: Many view AI as a tool similar to computers or typewriters—enhancing rather than replacing human capabilities
Example Quotations:
- 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."
- 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."
Creatives: Productivity Despite Stigma
Creative professionals are navigating a complex landscape of opportunity and concern:
Key Insights:
- Productivity Gains: Creatives are using AI to increase their productivity despite peer judgement and anxiety about the future
- Stigma Navigation: They are navigating both the immediate stigma of AI use in creative communities and deeper concerns about economic displacement
- Creative Identity: Concerns about the erosion of human creative identity
- Workflow Benefits: Many report being "less stressed" and having more time for favorite aspects of their work
Example Quotations:
- 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)."
Scientists: Selective Trust and Partnership
Scientists expressed a clear desire for AI partnership but demonstrated selective trust:
Key Insights:
- Desire for Partnership: Scientists uniformly expressed a desire for AI that could generate hypotheses and design experiments
- Selective Use: At present, they confined their actual use to other tasks like writing manuscripts or debugging analysis code
- Trust Barriers: Scientists can't yet trust AI for core research activities
- Practical Applications: AI is being used for supporting tasks rather than core scientific work
Research Applications:
- Writing and editing manuscripts
- Debugging analysis code
Public Participation and Future Research
Public Pilot Launch
Anthropic has launched a public pilot interview to continue understanding how people envision AI's role in their lives:
Participation Details:
- Availability: Available to Claude.ai Free, Pro, and Max subscribers who signed up at least two weeks ago
- Duration: 10-15 minute interview
- Access: Available at claude.ai/interviewer
- Availability: The study will be open for a week
- Focus: Explores what experiences, values, and needs drive people's vision for AI's future role in their lives
Data Usage:
- Insights will be analyzed as part of Anthropic's Societal Impacts research
- Findings will be published
- Data will be used to improve models and services
- Anonymized responses may be included in published findings
Future Research Directions
According to Anthropic, Anthropic Interviewer enables several types of research:
Targeted Research:
- Conduct research that informs specific policies
- Understand AI's impact on specific industries or professions
Participatory Research:
- Involve different communities in conversations about AI
- Gather diverse perspectives on AI development
Regular Studies:
- Track evolving relationships between humans and AI over time
Research Limitations
Important Caveats
The research has several important limitations that affect the scope and generalizability of findings:
Selection Bias:
- Participants were engaged through crowdworker platforms
- Their experiences might differ significantly from the general workforce
- Responses may be biased toward more positive or experienced perspectives
Demand Characteristics:
- Participants knew they were being interviewed by an AI system about AI usage
- This could have changed their willingness to engage or the kinds of responses they gave
- May differ from responses in human-conducted interviews
Static Analysis:
- Captured a snapshot of current AI usage and attitudes
- Cannot track how relationships develop over time
- Cannot determine if initial enthusiasm changes with extended use
Emotional Analysis:
- Text-only interviews can't read tone of voice, facial expressions, or body language
- May miss emotional cues that affect the meaning of statements
Self-Report Discrepancies:
- Participants' descriptions of AI usage might differ from actual practices
- Could be due to social desirability bias, imperfect recall, or evolving workplace norms
- Interview data revealed key discrepancies when compared with real usage data
Global Generalizability:
- Sample primarily reflects Western-based workers
- Cultural attitudes toward AI, workplace dynamics, and professional identity likely vary significantly across global contexts
Non-Experimental Research:
- Cannot determine whether AI usage directly caused reported outcomes
- Cannot determine the extent to which other factors contributed
Implications for AI Development
Centering Humans in AI Development
The research demonstrates Anthropic's commitment to understanding human perspectives on AI:
User-Centered Development:
- Using people's feedback to develop better products
- Understanding interactions with AI as a great sociological question
- Creating feedback loops between user experience and AI development
Societal Impact Research:
- Gathering data for analyzing AI's societal and economic impacts
- Understanding how AI is transforming work and professional identity
- Informing policy and development decisions
Building AI Systems That Reflect Public Needs
The goal of Anthropic Interviewer is to build AI systems that reflect public perspectives and needs:
Feedback Integration:
- Connect what people experience with AI to how AI is developed
- Incorporate user perspectives into model development
- Address concerns and optimize for user needs
Transparency and Openness:
- Publicly releasing interview data for researchers to explore
- Sharing findings and insights with the broader community
- Engaging in open dialogue about AI's impact
Conclusion
Anthropic Interviewer represents a significant innovation in understanding how AI is transforming work and professional identity. The research with 1,250 professionals reveals a workforce actively negotiating its relationship with AI, generally preserving tasks central to their professional identity while delegating routine work for productivity gains.
Key Takeaways:
- Optimism with Concerns: Professionals are generally optimistic about AI's role in their work, but have concerns about job displacement, creative identity, and professional autonomy
- Professional-Specific Patterns: Different professional groups (general workforce, creatives, scientists) show distinct patterns in how they adopt and use AI
- Identity Preservation: People want to preserve tasks that define their professional identity while automating routine work
- Selective Trust: Scientists and other professionals are selective about which tasks they entrust to AI
- Research Innovation: AI-conducted interviews can be effective and well-received, enabling research at unprecedented scale
What's Next:
As Anthropic continues to use Anthropic Interviewer to understand how people envision AI's role in their lives, this research will inform both product development and broader understanding of AI's societal impact. The public pilot interview provides an opportunity for more people to share their perspectives, contributing to a more comprehensive understanding of human-AI relationships.
The launch of Anthropic Interviewer demonstrates that understanding human perspectives on AI is crucial for building AI systems that truly serve human needs. By combining AI-powered research tools with human analysis, Anthropic is creating new pathways for understanding and responding to the transformative impact of artificial intelligence on work, creativity, and society.
Sources
- Anthropic Research - Introducing Anthropic Interviewer
- Anthropic Official Website
- Claude Model Overview
- AI Impact Glossary Entry
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