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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.

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.

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.

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.

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.

The IDRC has submitted a proposal to the W3C to establish a Community Group to discuss and develop portable personal data preferences.

A COVID-19 data monitor prototype test that was created to show how data gaps can be addressed, providing a way to find accessibility information that is not included in these data sets.

The Future of Work: Equitable Digital Systems project is an initiative at the Inclusive Design Research Centre, OCAD U examining the accessibility of the digital tools and systems we rely upon for work.

The development team has created a new workflow supported by the Personal Data Storage, or Preferences server, where the user makes save/retrieve requests for their preferences while on a static site.