Discover more about We Count’s efforts, activities and viewpoints.
A Clusive Success Story
Clusive is a free, flexible, adaptive and customizable learning environment. It is a web application for students and teachers that addresses access and learning barriers present in digital and open learning materials.
Ensuring Equitable Outcomes from Automated Hiring Processes: An Update
For this article, Antranig is considering this problem in the context of corporate apologies for technological practice and initiatives such as data feminism that seek to transfer power from privileged groups to those at the margins of society.
The Future of Work and Disability
The Future of Work and Disability project formed a study group to understand and examine intersecting topics of AI, automation, standards and employment as they relate to persons with disabilities.
The Accessibility Ecosystem Proposal
To say that the route to almost all essential services is through digital systems is stating the obvious. Despite this reality, more than twenty-five years of regulations requiring accessible digital technology, a plethora of guidelines and resources to support accessibility, and a thriving industry checking and repairing inaccessible websites, people who require alternative ways to access digital systems face ever-multiplying barriers.
Exploring Bias in Hiring Tools
This video presentation examines how AI technology is utilized in recruitment and selection, its implications for candidates with disabilities, and the question of accessibility and diversity.
Disability Bias in AI-Powered Hiring Tools Co-Design
In May, we completed our second set of co-design sessions with the Equitable Digital Systems (EDS) project. EDS is a project that explores how to make digital systems more inclusive for persons with disabilities in the workplace.
Introduction to Data Science Tools Resources in the We Count Research Library
Learning data science comes with a steep learning curve, and inaccessible tutorials, resources and tools create barriers. To support a more inclusive environment in the field of data science, We Count has created a resource library.
Ensuring Equitable Outcomes from Automated Hiring Processes
These automated hiring and matching algorithms, implemented by major corporations such as LinkedIn, Amazon and others can be positioned in the wider context of automated processes, that use machine learning/AI algorithms, and support the infrastructure of society. These systems inevitably result in inequitable outcomes.
Pluralistic Data Infrastructure
The pluralistic data infrastructure supports communities in taking collective ownership of data that relates to them and curating its relationships with data from other sources.
W3C Portable Personal Data Preferences Community Group
The IDRC has submitted a proposal to the W3C to establish a Community Group to discuss and develop portable personal data preferences.