An Inclusive Design Research Centre project
We Count

Challenges

To achieve We Count’s goal of an inclusive and balanced data ecosystem for persons with disabilities, We Count is issuing an ongoing call for challenges.

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A We Count Challenge is a data ecosystem inclusion problem that creates barriers to participation or other risks from things like:

  • Exclusion from data sets — ensures that decisions and knowledge based on data won’t take people with disabilities into account
  • Ableism and bias in data systems — causes AI and machine learning tools to incorrectly respond to individuals who present differently
  • Inaccessible data science and visualization tools — limits the ability for individuals to create from data, learn about data science or be employed in the field
  • Data abuse and misuse — a concern for all that is heightened for those who are already subject to bias and discrimination

We Count is providing opportunities for stakeholders to raise and address data ecosystem challenges, especially those that impact people with disabilities. Here are examples of challenges already submitted by We Count collaborators:

  • Creating data sets that help identify barriers to employment, such as access to accessible washrooms at workplaces
  • Effectively sharing information on elevator operation status for all elevators
  • Collecting data on screen reader interoperability to improve accessibility
  • Developing strategies for voice recognition systems to support use by individuals with dysarthric speech or other “difficult to recognize” speech patterns, like accents

To tackle these challenges, We Count is assembling diverse, knowledgeable teams for challenge workshops.

What is the data ecosystem?

A data ecosystem is the complete cycle of “pieces” of information as well as individuals and organizations within the data science/services system. This cycle includes:

  • Individuals who generate data or information
  • Systems to collect and analyze the data
  • Individuals who build or use the systems
  • Collecting, analyzing, visualizing and generating insights from data and the decisions made from this process
  • Training, hiring and working within data science fields

As data becomes the main source for truth and value, persons with disabilities are becoming increasingly marginalized as their needs are not considered within the data ecosystem.