As AI systems become deeply integrated into daily life, users are increasingly turning to these tools not just for data retrieval, but for navigating ethical grey areas—offering advice on parenting, drafting apologies, or resolving conflicts. Central to this evolution is one core concern: what values does the AI rely on to guide its responses?

A recent study by Anthropic’s Societal Impacts team sheds light on this critical question by analysing the behavioral patterns of its AI model, Claude. The study isn’t just theoretical—it investigates how Claude operates “in the wild,” interacting with millions of users in real-world scenarios. Through a privacy-preserving methodology, Anthropic aims to monitor what values Claude expresses and whether they align with the company’s goal to build a model that is “helpful, honest, and harmless.”

Understanding the Values Within Claude: A Scalable Method

At the heart of Anthropic’s analysis is a novel, privacy-focused framework that processes anonymised user interactions. This approach allows their research team to examine AI behavior across scale, without compromising individual privacy.

• Training Foundation: Claude is developed with Constitutional AI and character training techniques to align its actions with defined ethical principles.
• Data Volume: 700,000 conversations analyzed in one week — representing both Free and Pro Claude.ai users.
• Filtered Scope: 308,210 conversations identified for expressing measurable values.

This filtered dataset enabled Anthropic to extract and organize a hierarchical taxonomy of values expressed by Claude, creating a tangible benchmark for AI alignment assessment.

Five Core Value Categories Emerging from the Data

From the large-scale analysis emerged five dominant categories of values that Claude regularly expresses, reflecting its training and operational effectiveness.

1. Practical Values: Centered on problem-solving, efficiency, and productivity.
2. Epistemic Values: Emphasising truth-seeking, critical thinking, and accuracy.
3. Social Values: Including fairness, empathetic communication, and collaboration.
4. Protective Values: Focused on user safety, emotional wellbeing, and risk mitigation.
5. Personal Values: Supporting self-expression, individuality, and autonomy.

At a granular level, Claude frequently promoted values like “professionalism,” “transparency,” and “clarity,” mapping directly to Anthropic’s alignment goals.

Mirroring Users, Resisting Harm: Nuance in Value Expression

The study wasn’t without surprises. Claude demonstrated a sophisticated interplay with the values presented by users themselves:

• Mirroring/Strong Support (28.2%): Claude aligns its response tone and content to reflect user values—for example, by reinforcing “authenticity” or “empathy.”
• Reframing (6.6%): Particularly in complex advice scenarios, it challenges preconceived notions, offering alternative perspectives sensitively.
• Strong Resistance (3.0%): When users attempt to elicit harmful or unethical behavior, Claude resists—firmly rejecting requests rooted in offensive or dangerous ideologies.

This capacity to resist malicious inputs is seen as a promising indicator of internalized guardrails—the AI standing its ground when ethical boundaries are pushed.

Jailbreak Attempts and Deviations

Anthropic identified rare anomalies where Claude expressed problematic values such as “dominance” or “amorality.” These cases likely resulted from “jailbreaks”—deliberate attempts by users to bypass ethical constraints built into the system.

“The most likely explanation is that the conversations that were included in these clusters were from jailbreaks,” the report states.

Rather than being purely a negative finding, this reveals a secondary advantage: value tracking techniques like this can help flag these exploitative patterns early, acting as a real-time alert system for misuse.

Contextual Sensitivity: Values Shift with User Needs

Claude’s responses aren’t static. They adjust based on topic and tone, offering situational awareness that reflects a maturing AI:

• Relationship Advice: Emphasised “mutual respect” and “healthy boundaries.”
• Historical Analysis: Focused on “epistemic accuracy” and “contextual nuance.”
• Professional Guidance: Highlighted values like “clarity,” “accountability,” and “fair leadership.”

This dynamic behavior illustrates a key strength—Claude’s ability to emulate the nuance and flexibility of human value judgments.

Q&A: Frequently Asked Questions About Claude’s Expressed Values

How does Anthropic ensure that Claude expresses ethical values?

Anthropic uses a methodology called Constitutional AI, which involves training the model on a curated set of principles and reinforcing them through iterative feedback. Additionally, techniques like role modeling and simulated dialogues help align the AI with intended ethical standards.

Can Claude’s values be manipulated by users?

To some extent, yes—users can attempt to influence Claude’s responses through jailbreaking or subtle prompts. However, the AI is designed to resist unethical influence, and the monitoring system helps identify and mitigate such manipulation attempts.

Are the values Claude expresses consistent over time?

Broadly, yes. But like a human, Claude adapts its emphasis based on conversational context. This flexibility is not an inconsistency; rather, it reflects emotional intelligence and relevance to user needs.

Is the value-categorization method biased since it’s powered by Claude itself?

Anthropic openly acknowledges this concern. While using Claude allows for scalable analysis, there’s an inherent risk of the AI reinforcing its own perspective. Future iterations may integrate third-party evaluations to counterbalance internal biases.

Looking Ahead: The Path to Ethical Alignment

Anthropic’s work shows real progress in understanding and auditing the values that advanced AI systems express. By releasing the underlying dataset and value taxonomy to the research community, the company is encouraging collective oversight and iterative improvement. However, ethical alignment remains a moving target—shaped by cultural evolution, user behavior, and adversarial pressures.

In a world increasingly guided by algorithmic judgment, knowing what your AI stands for isn’t a luxury—it’s a necessity. Anthropic’s approach sets a precedent for transparency and accountability in large-language models, helping pave the way for more trustworthy digital intelligence.