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.

Overview Tools Metrics About the catalogue

lime

Github

A repository to quickly generate synthetic data and associated trojaned deep learning models

About the tool

You can click on the links to see the associated tools

Tool type(s):

Toolkit/software

Objective(s):

Robustness

Impacted stakeholders:

Regulators

Purpose(s):

Event/anomaly detection
Forecasting/prediction
Goal-driven optimisation
Interaction support/chatbots
Personalisation/recommenders
Reasoning with knowledge structures/planning
Recognition/object detection
Content generation

Lifecycle stage(s):

Operate & monitor
Deploy
Verify & validate
Build & interpret model
Collect & process data
Plan & design

Type of approach:

Technical

Maturity:

Implemented in multiple projects

Usage rights:

Open source/Permissive

License:

BSD 2-Clause "Simplified" License

Target groups:

Professionals

Target users:

Data scientist
Developer
Project manager
System operators
System integrators
Policy makers

Validity:

Always up to date

Enforcement:

Reporting frameworks
Trust/Quality mark

Benefits:

Improved ability to scale
Increased quality results
Reduction in risk of failure

Geographical scope:

All countries

People involved:

Operations employees

Required skills:

Domain expertise

Technology platforms:

Platform neutral

Programming languages:

Python
TeX
CSS
HTML
JavaScript

Tags:

ai responsible
ai risks
trustworthy ai
validation of ai model
ai assessment
ai governance
ai auditing

Github stars:

10949

Github forks:

1777

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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.