character-cultural-value-checker

To detect paradigm drift, you quantify the cultural-value alignment by generating multi-dimensional profiles using 8 cultural axes and 9 paradigms. The process calculates distance metrics and paradigm drift risks to identify worldview shifts between the character and the LLM.

AI character cultural-value alignment measures how closely a character's setting matches a target LLM's baseline values. Culture analysis works by evaluating the character prompt against 8 cultural axes and 9 paradigms to produce a multi-dimensional profile and quantitative risk scores.

Yes, you can evaluate conversation logs and historical figures for LLM bias. The character profiling accepts full character prompts, summaries, dialogue logs, and historical descriptions as input to generate multi-dimensional cultural profiles and calculate AI-suitability scores.

You calculate cultural drift risk (CDR) and paradigm drift risk (PDR) by applying a standardized evaluation flow to the character input. This generates distance metrics alongside risk scores, providing a detailed diagnostic output of potential worldview transformations.

The best way to predict worldview drift is to run the character prompt through a multi-dimension culture analysis before deployment. This generates an AI-suitability score and specific risk metrics, allowing you to anticipate and mitigate potential paradigm shifts in the target LLM.

While the evaluation accepts short character summaries, detailed diagnostic output requires sufficient context to accurately apply the 8-axis and 9-paradigm scoring. Extremely brief inputs may limit the precision of the distance metrics and paradigm drift risk calculations.