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.

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EducationalUnited KingdomUploaded on Dec 9, 2024
Newton’s Tree’s Federated AI Monitoring Service (FAMOS) is a dashboard for real-time monitoring of healthcare AI products. The dashboard is designed to enable users to observe and monitor the quality of data that goes into the AI, changes to the outputs of the AI, and developments in how healthcare staff use the product.

Related lifecycle stage(s)

Operate & monitorDeploy

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.

TechnicalEducationalProceduralSwedenSlovakiaCanadaFinlandUploaded on Nov 13, 2023
Use Saidot to empower AI teams to do high-quality AI governance efficiently and with quality

TechnicalEducationalProceduralFranceUploaded on Sep 26, 2023
Based on abstract interpretations, Saimple leverages state-of-the-art techniques described in ISO/IEC 24029 standards for the assessment and validation of AI model robustness

TechnicalEducationalProceduralUploaded on Jul 4, 2023<1 hour
The Data Carbon Scorecard provides a rapid assessment of the environmental impact of your proposed data project enabling you to quickly gauge the CO2 implications of your data project and determine the ‘best’ course of action for the environment. Through answering just 9 questions, the scorecard provides you with a traffic light display of data CO2 hotspots and an overall Data CO2 Score for the whole project within minutes. The scorecard can be used by any individual, team, or organization.

EducationalUploaded on Apr 27, 2023
AI serious game application for Mixed Reality to stimulate individual self-awareness in our relationship with AI, based on the following 3 pillars: (1) the computational self, (2) the experiential self, (3) the composite self.

Related lifecycle stage(s)

Verify & validate

EducationalUnited StatesUnited KingdomSaudi ArabiaJapanChinaIsraelEuropeEUUploaded on Apr 24, 2023<1 hour
Hybrid solution with online training, risk framework, chatbot and templates to secure AI Risks


TechnicalEducationalUploaded on Apr 12, 2023
An AI tool that allows you to understand complex civic issues by listening to the perceptions and concerns of millions of citizens in Latin America and the Caribbean in real time.

EducationalProceduralUploaded on Mar 30, 2023<1 day
The framework proposes a self-regulated approach that incorporates certain tools (or instruments) to facilitate ethical and responsible AI development, drawing on insights from the EU Regulation on Artificial Intelligence (AI Act)

EducationalProceduralUploaded on Mar 2, 2023
Naaia, the first AIMS on the market in Europe, is the governance and management solution for AI systems without compromising ethics or compliance (AI ACT)

Objective(s)


EducationalProceduralUploaded on Sep 15, 2022

Model cards are the tool for transparent AI documentation. Model cards are essential for discoverability, reproducibility, and sharing. You can find a model card as the README.md file in any model repo. Under the hood, model cards are simple Markdown files with additional metadata.


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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.