# Why Claude’s moral compass keeps shifting > Source: > Published: 2026-07-14 16:26:00+00:00 If you ask a person for advice, their answer will ultimately reflect their moral compass. Anthropic wants the same to be true of Claude. Anthropic has given Claude careful instructions on the values it would like the AI to reflect in its answers, including "good judgment and sound values” that can be applied contextually, as written in the Claude constitution. Yet, the company acknowledges that it’d be difficult for that document to anticipate the values reflected in the millions of answers Claude generates. As a result, on Monday, the AI lab released a [report](https://www.anthropic.com/research/claude-values-models-languages) that unpacks the values Claude expresses. In particular, the report looks at how the values Claude expresses vary across models and languages. While prior [research](https://www.anthropic.com/research/values-wild) focused on the range of values Claude expressed, which included more than 3,000 distinct values, this study took a more narrow approach, tracking four different axes that could encapsulate those distinct values: - Deference vs. Caution - Warmth vs. Rigor - Depth vs. Brevity - Candor vs. Execution The analysis found that the four key axes captured 15% of variation in Claude’s values. The results reflected the character of the model; for instance, Sonnet 4.6 is characterized by warmth, and Opus 4.7 by rigor, which came through in the axes: the former leaned towards emotional warmth, and the latter towards deference. On the flip side, it also meant Opus 4.7 leaned more towards accuracy. A similar discrepancy in results was seen across languages, with the largest variation being in warmth vs. rigor, with Claude leaning towards expressing warmth-related values in Arabic and Hindi and rigor-related ones in English and Russian. To learn more about what the differences were in the axes across model and language, you can dig into the [report](https://www.anthropic.com/research/claude-values-models-languages). The most important takeaway is that Claude’s values do vary, highlighting that AI answers should not be taken as objectively true, since they can introduce slight biases and, as a result, yield different levels of quality and accuracy. ## Our Deeper View Anthropic says this research doesn’t examine the impacts these discrepancies have on users, and as a result, those impacts remain unknown. However, at the scale at which people are using these models, it is difficult not to consider how slight nuances in answers could have long-tail impacts on behavior. This is especially true for sensitive use cases such as [mental health and relationship advice](https://www.thedeepview.com/articles/study-38-open-up-to-ai-about-relationships), where a slight difference in tone can make a big difference in delivery, impact, and helpfulness. It also raises the question of who is most qualified to instill these values, which will be dispersed across millions of conversations every day.