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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Recall

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Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation: Recall = TP / (TP + FN) Where TP is the number of true positives and FN is the number of false negatives.

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A survey of cross-validation procedures for model selection

Uploaded on Oct 21, 2022

Used to estimate the risk of an estimator or to perform model selection, cross-validation is a widespread strategy because of its simplicity and its apparent universality. Many...

Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals

Uploaded on Nov 1, 2022

We show that many machine learning goals, such as improved fairness metrics, can be expressed as constraints on the model’s predictions, which we call rate constraints. W...

Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network

Uploaded on Nov 1, 2023
Recent studies in image classification have demonstrated a variety of techniques for improving the performance of Convolutional Neural Networks (CNNs). However, attempts to combine...

I3CL:Intra- and Inter-Instance Collaborative Learning for Arbitrary-shaped Scene Text Detection

Uploaded on Nov 1, 2023
One fundamental challenge of vehicle re-identification (re-id) is to learn robust and discriminative visual representation, given the significant intra-class vehicle variations acr...

May the Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation

Uploaded on Nov 1, 2023
Driving 3D characters to dance following a piece of music is highly challenging due to the spatial constraints applied to poses by choreography norms. In addition, the generated da...

REGTR: End-to-end Point Cloud Correspondences with Transformers

Uploaded on Nov 1, 2023
Methods based on convolutional neural networks have improved the performance of biomedical image segmentation. However, most of these methods cannot efficiently segment objects of ...

ResNet strikes back: An improved training procedure in timm

Uploaded on Nov 1, 2023
Graph and hypergraph representation learning has attracted increasing attention from various research fields. Despite the decent performance and fruitful applications of Graph Neur...

ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision

Uploaded on Nov 1, 2023
A key function of auditory cognition is the association of characteristic sounds with their corresponding semantics over time. Humans attempting to discriminate between fine-graine...

Human-Computer Trust Scale (HCTS)

Uploaded on Apr 10, 2024

The Human-Computer Trust scale (HCTS) is a simple, nine-item attitude Likert scale that gives a global view of subjective assessments of trust in technology.

The HCTS resu...


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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.