An AI-powered speech recognition app that adapts to users' unique speech patterns, facilitating communication for individuals with speech impairments.

UNICEF’s Accessible Digital Textbooks for All initiative aims to make textbooks accessible for students with disabilities by following Universal Design for Learning (UDL) guidelines and offering flexible delivery formats.

Efficacy of a Computer-Based Learning Program in Children With Developmental Dyscalculia. What Influences Individual Responsiveness?

The Early Literacy Interventions Tool uses ChatGPT to answer questions and design learning plans

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.

Warden AI provides independent, tech-led AI bias auditing, designed for both HR Tech platforms and enterprises deploying AI solutions in HR. As the adoption of AI in recruitment and HR processes grows, concerns around fairness have intensified. With the advent of regulations such as NYC Local Law 144 and the EU AI Act, organisations are under increasing pressure to demonstrate compliance and fairness.

FairNow is an AI governance software tool that simplifies and centralises AI risk management at scale. To build and maintain trust with customers, organisations must conduct thorough risk assessments on their AI models, ensuring compliance, fairness, and security. Risk assessments also ensure organisations know where to prioritise their AI governance efforts, beginning with high-risk models and use cases.

A fast, scalable, and open-source framework for evaluating automated red teaming methods and LLM attacks/defenses. HarmBench has out-of-the-box support for transformers-compatible LLMs, numerous closed-source APIs, and several multimodal models.

Community jury is concept where multiple stakeholders impacted by a same technology are given the possibility to learn about a project, discuss with one another and provide feedback.

This DIN DKE SPEC defines guidelines for the labelling of training data for QA systems and specifies the characteristics of labels.

This standard specifies an architecture and technical requirements for face recognition systems.

This document introduces the effects of population demographics on biometric functions.

This document addresses bias in relation to AI systems, especially with regards to AI-aided decision-making.

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.

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

A PyTorch implementation of Speech Transformer, an End-to-End ASR with Transformer network on Mandarin Chinese.

Approaches to disability-centered data, models, systems oversight

Ethical Problem Solving (EPS) is a framework to promote the development of safe and ethical artificial intelligence. EPS is divided into an evaluation stage (performed via Algorithmic Impact Assessment tools) and a recommendation stage (the WHY-SHOULD-HOW method).

A collections of public and free annotated datasets of relationships between entities/nominals (Portuguese and English).

Our work enables developers and policymakers to anticipate, measure, and address discrimination as language model capabilities and applications continue to expand.