microsoft/responsible-ai-toolbox
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions. observed · 2026-08-28
Health v2 · maintenance only
67/100
- Activity 98
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2249
- days_rel: n/a
- days_push: 14
- n_releases_24m: 0
Adoption not part of the score
1824 stars · 492 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Microsoft suite of Python libraries and Jupyter widgets providing dashboards for model assessment, error analysis, interpretability, fairness evaluation, and causal decision-making. It helps developers and stakeholders understand, debug, and responsibly monitor AI systems.
Use cases
- analyze why my machine learning model makes errors on certain cohorts
- visualize feature importance and model explanations in a Jupyter notebook
- assess fairness of my model across demographic groups
- debug underperforming ML model subpopulations
- generate a responsible AI dashboard for model assessment
- explore counterfactuals and causal insights for model decisions
- evaluate model error rates by data cohort
When to choose
- you train ML models in Python and need interpretability, error analysis, or fairness assessment
- you want interactive dashboards inside Jupyter notebooks
- you need a holistic responsible-AI evaluation suite for tabular models
When to avoid
- you need LLM/GenAI evaluation rather than classical ML model assessment
- you want a production monitoring service rather than notebook-based analysis
- your models are not accessible from Python
Facets
library · maturity active
data-visualization machine-learning ui-components machine-learning data-science data-visualization developer-tools python responsible-ai fairness explainability error-analysis interpretability jupyter-widgets model-assessment jupyter web
1 source
- readme: https://github.com/microsoft/responsible-ai-toolbox · fetched 2026-08-28 · 1b6f7170b783
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| microsoft/responsible-ai-toolbox | main | 67 |
For agents
markdown · JSON · MCP: product_card(name="microsoft/responsible-ai-toolbox")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem