Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Type

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Fairness

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Origin

Scope

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Approach Technical
Objective Fairness

TechnicalUnited StatesUploaded on Mar 24, 2025
An open-source Python library designed for developers to calculate fairness metrics and assess bias in machine learning models. This library provides a comprehensive set of tools to ensure transparency, accountability, and ethical AI development.

TechnicalUploaded on Aug 2, 2024
Responsible AI (RAI) Repairing Assistant

TechnicalProceduralSpainUploaded on May 21, 2024
LangBiTe is a framework for testing biases in large language models. It includes a library of prompts to test sexism / misogyny, racism, xenophobia, ageism, political bias, lgtbiq+phobia and religious discrimination. Any contributor may add new ethical concerns to assess.

TechnicalInternationalUploaded on Apr 23, 2024
Based on an extensive criteria catalogue, the Digital Trust Label is awarded to trustworthy digital services after an audit

TechnicalUploaded on Apr 22, 2024
A clear, concise, simple yet powerful and efficient API for deep learning.

TechnicalUploaded on Apr 22, 2024
The open big data serving engine. https://vespa.ai

Objective(s)


TechnicalUnited KingdomUploaded on Apr 22, 2024
JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.

TechnicalUnited StatesUploaded on Apr 22, 2024
Wild Me's first product, Wildbook supports researchers by allowing collaboration across the globe and automation of photo ID matching

TechnicalUnited StatesUploaded on Apr 22, 2024
XLNet: Generalized Autoregressive Pretraining for Language Understanding

Objective(s)


TechnicalUnited StatesUploaded on Apr 22, 2024
YoloV3 Implemented in Tensorflow 2.0

TechnicalEducationalSwitzerlandUploaded on Apr 22, 2024<1 day
A global communityof 500+ researchers from 57+ countries, with foundational free course in a Human Rights-based approach to AI development that explores concrete builds of systems centering human rights values. Community is further enriched by reading & discussion groups, and written community outputs.

TechnicalProceduralUnited StatesJapanUploaded on Apr 19, 2024
Diagnose bias in LLMs (Large Language Models) from various points of views, allowing users to choose the most appropriate LLM.

Related lifecycle stage(s)

Plan & design

TechnicalProceduralIsraelUploaded on Apr 11, 2024
Citrusx offers a multifaceted solution to connect all stakeholders in the company through an SDK, user-friendly UI, and automated reporting system.

TechnicalCanadaUploaded on Apr 2, 2024
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

TechnicalPhilippinesUploaded on Apr 2, 2024
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

TechnicalUploaded on Apr 2, 2024
Deep learning library featuring a higher-level API for TensorFlow.

TechnicalFranceUploaded on Apr 2, 2024
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

Objective(s)


TechnicalGermanyUploaded on Apr 2, 2024
🧙 A web app to generate template code for machine learning

TechnicalFranceUploaded on Apr 2, 2024
Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀

TechnicalProceduralGermanyUploaded on Feb 19, 2024>1 year
Casebase is a software for AI management along the entire life cycle.

catalogue Logos

Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.