Responsible AI Toolkit
87 vendors curated. Independent ranking, no paid placement.
AI Trust Services (KPMG)
KPMG's trusted AI framework for governance, risk, and compliance.
Aporia
Monitor, test, and safeguard LLMs in production with observability and guardrails.
Robust Intelligence
AI security platform detecting adversarial vulnerabilities and model failures.
Azure AI Content Safety
Content moderation API detecting harmful AI outputs in real-time.
NannyML
Post-deployment ML monitoring for data drift, performance degradation, and model behavior.
Neuronpedia
Interpretability platform for understanding neural network behavior and safety.
Pangea
API-first security guardrails for AI applications and compliance.
Weights & Biases
ML experiment tracking and model monitoring for governance and compliance.
8 Principles of Responsible ML
Framework for building responsible ML systems with governance principles.
A checklist for auditing AI systems
Structured checklist framework for systematic AI system auditing and compliance assessment.
A Living and Curated Collection of Explainable AI Methods
Curated reference collection of XAI methods for model transparency and interpretability.
ABOUT ML Reference Document
Framework for documenting ML system transparency, accountability, and governance requirements.
Advanced AI evaluations at AISI: May update
Advanced AI evaluation framework for systematic risk assessment and compliance testing.
AI Alliance affiliated project
Framework for responsible prompt engineering and LLM governance.
AI Badness: An open catalog of generative AI badness
Open catalog documenting generative AI failure modes and risks.
AI FactSheets 360 (IBM)
Open-source toolkit for AI transparency, bias detection, and responsible model development.
AI Safety Camp
Community-driven AI safety education and governance resources.
AI Snake Oil
Exposes AI hype and provides practical guidance for responsible AI deployment.
AI Verify Foundation
Open-source AI governance testing toolkit for compliance and responsible AI
AI Vulnerability Database
Open database and tools for identifying and managing AI vulnerabilities and risks.
AIAAIC
AI incident tracking and governance resource hub for organizations.
Algorithmic Impact Assessment tool
Government-backed framework for assessing algorithmic systems' impact and risks.
Atlas of AI Risks
Structured risk taxonomy and mapping for AI system governance.
Auditing Guidelines for Artificial Intelligence
Guidelines for auditing AI systems and governance controls.
BRAID programme
UK-based AI governance framework for responsible AI implementation and compliance.
COMPAS Recidivism Risk Score Data and Analysis
Public dataset exposing bias in criminal risk assessment AI systems.
Data Use Policy
Framework for organizations to define and implement responsible data use policies.
Debugging Machine Learning Models
Debug ML models to understand failures and improve transparency.
Deon (DrivenData)
Checklist-driven framework for building ethical AI systems with governance.
Distill
Interactive visualizations for understanding and debugging machine learning models.
EU AI Act Expert Explainer (Ada Lovelace Institute)
Open-source guide demystifying EU AI Act requirements and compliance obligations.
Extracting Training Data from ChatGPT
Research tool demonstrating training data extraction risks in LLMs.
FairLearn
Open-source toolkit for detecting and mitigating AI model bias and fairness issues.
Fairness and Machine Learning: Limitations and Opportunities
Free textbook and resource guide on fairness limitations in machine learning systems.
FATML Principles and Best Practices
Community-driven principles and practices for fair, transparent, accountable ML.
ForHumanity Body of Knowledge
Open knowledge base for AI governance, risk, and compliance frameworks.
Foundation Model Development Cheatsheet
Quick reference guide for foundation model developers on compliance and responsible practices.
FRIA Guide (ECNL & Danish Institute)
Practical guide for conducting fundamental rights impact assessments on AI systems.
Getting a Window into your Black Box Model
Reason codes for NFL models: interpretability for black-box AI systems.
Guide to FRIAs (Danish Institute for Human Rights)
Structured guidance for conducting fundamental rights impact assessments under EU AI Act.
Have I Been Trained?
Check if your training data was used to train AI models without consent.
IML
Open-source ML interpretability library for understanding model decisions.
Interpretable Machine Learning using Counterfactuals
Explainable AI through counterfactual examples for model transparency.
Interpreting Machine Learning Models with the iml Package
R package for interpreting and explaining machine learning model predictions.
Introduction to Responsible Machine Learning
Educational framework for building interpretable, fair, and accountable ML systems.
Llama 2 Responsible Use Guide
Meta's framework for responsible deployment and use of Llama 2 models.
MadryLab
Adversarial robustness research lab advancing AI security and trustworthiness.
MATS
AI safety research & governance framework for responsible AI development.
ML Safety Course
Educational resource for ML safety and responsible AI practices.
ML.ENERGY Leaderboard
Track ML model energy consumption and environmental impact.
Montreal AI Ethics Institute
AI ethics research institute providing governance frameworks and compliance guidance.
OECD.AI Policy Observatory
OECD intelligence on AI policy, governance, and regulation implementation.
OWASP AI Testing Guide
Open-source testing methodology for AI security, bias, and compliance risks.
Partial Dependence Plots in R
R package for interpreting model predictions through partial dependence visualization.
production website
Document and analyze AI incidents for governance and risk mitigation.
RAI Toolkit
Open-source toolkit for responsible AI development and bias assessment.
Real Toxicity Prompts - Allen Institute for AI
Dataset for testing language models against toxic outputs and unsafe behavior.
Resemble.AI Deepfake Incident Database
Deepfake incident tracking database for AI risk monitoring and governance.
Responsible AI Institute
Open-source framework for building and auditing responsible AI systems.
ResponsibleAI
Open-source toolkit for responsible AI development and model explainability.
Sample AI Incident Response Checklist
Structured checklist for responding to and documenting AI incidents.
TensorFlow Extended (TFX)
Production ML pipeline framework with model governance and monitoring capabilities.
Tracing the thoughts of a large language model
Interpretability research enabling auditable LLM decision tracing.
Trust-LLM-Benchmark Leaderboard
Benchmark suite evaluating LLM trustworthiness across safety, fairness, and robustness.
Understanding Responsibilities in AI Practices
Framework for defining AI accountability roles and organizational responsibilities.
University of British Columbia, Resources (Generative AI)
Open resource hub for responsible AI governance and compliance practices.
Verica Open Incident Database
Open database of AI incidents for learning from real-world failures.
Vocabulary of AI Risks
Structured vocabulary for identifying and categorizing AI risks in systems.
What-If Tool (Google)
Interactive tool for testing and understanding ML model behavior and fairness.
Aapti Institute
AI governance and responsible AI framework for organizations in emerging markets.
AI Disclosure Kit
Toolkit for documenting and disclosing AI systems to meet regulatory requirements.
AI Ethics Lab
AI ethics framework and governance tools for responsible AI deployment.
AI Safety Map
Visual landscape mapping tool for AI safety governance and compliance navigation.
AI Transparency Institute
Transparency and accountability tools for AI systems governance and compliance.
Apollo Research
AI safety research platform for interpretability and risk assessment.
Difinity
AI governance platform helping enterprises compare and select compliant tools.
FAR AI
Formal verification for AI systems to prove safety properties and compliance.
GEM
Benchmark suite for evaluating AI model risks and bias across governance frameworks.
HiddenLayer
Adversarial attack detection and ML model security for compliance-required risk management.
Lasso Security
Runtime security and guardrails for LLM applications in production.
OSD Bias Bounty
Crowdsourced bias detection for AI systems through structured bounty programs.
Prompt Security
Detects and prevents prompt injection attacks and data leakage in AI applications.
Redwood Research
AI safety research lab building tools for measuring and improving model alignment.
SolasAI
Detect algorithmic bias and ensure fairness compliance in AI decisions.
SynthID-Text
Watermark AI-generated text for transparency and provenance verification.
The Ethical AI Database
Centralized database for AI governance policies, risk frameworks, and compliance auditing.
VerifyWise
AI governance platform enabling safe, compliant business AI deployment