Responsible AI at PIMPmyBOSS: what it does, and what it does not do
PIMPmyBOSS does not hide automated judgement behind the word AI. In v1, scores are based on deterministic, explainable rules. Generative AI and learning components are planned for later, with constrained roles.
The active engine does not use a generative model to decide a profile, index or ranking. Scoring functions are versioned and run server-side. The RAG chatbot and effective learning are v2 horizons, not capabilities presented as already active.
The core calculation can be explained without asking users to trust a black box.
Typology distributes 100% of the profile across five reference centres according to weighted proximity; compatibility uses ten mirror pairs and an RMS distance; relationship quality and lived score remain separate.
These calculations are not delegated to a generative model and do not live in the browser. Engine versions and parameters make a result reproducible.
RAG is planned to help explain results, not reinvent the scores.
The v2 roadmap includes a conversational results chatbot built on a RAG system. Its expected role is to contextualise and explain results already produced by the scoring layers, not freely decide who is a good manager.
The capability will not be presented as active until it is developed, tested and documented.
Real-world data may evolve the engine, but never live on one person.
Archetype centres and selected weights may be recalibrated once data volume and quality make that defensible. Learning will happen in batches, offline, regularised towards the prior, separately validated and released as a new version.
A micro-validation of right, partial or wrong never instantly changes a centre, weight or historical result.
Technology must not turn a perception into a verdict.
PIMPmyBOSS separates style from relationship quality, rejects public manager rankings, protects evaluation granularity and preserves human supervision for complex cases.
The product also states its limits: a perception is lived data to contextualise, not an absolute truth about a person.
Frequently asked questions
Important answers should remain understandable without animation, internal jargon or dependence on a personal result.
Does AI decide my style?
Not in the sense of a generative or autonomous model. The v1 engine applies a deterministic proximity calculation using versioned centres and parameters.
Can a chatbot change my score?
No. The RAG chatbot planned for v2 is a results explanation and contextualisation tool. Scoring remains a separate layer.
Do user feedback signals immediately train the engine?
No. Micro-validations evaluate insight relevance. Any parameter change must happen offline, be validated and versioned.
Is PIMPmyBOSS trying to predict relationship success?
No. The current compatibility index normalises proximity across ten pairs; it is not a probability of success.