AI AND ACCESSIBILITY

Artificial Intelligence (AI) or artificial narrow intelligence (ANI), artificial general intelligence (AGI), artificial super intelligence (ASI) is a critical issue for people with disabilities and it will only grow in its impact. The World Institute on Disability (WID) is aware that AI has already brought many remarkable tools to disability access and inclusion; what has already been achieved illuminates the promise that AI can facilitate more accessible content for people with disabilities.

For example, software is now learning how to recognize and respond to images, sounds, and linguistic expressions, which have opened up new opportunities for people with many disabilities. When the data sets used are designed for full inclusion, tools like those outlined below will positively change the landscape for people with disabilities:

  • For individuals who are deaf or have hearing loss, auto-captioning with AI.
  • For people who are unable to drive, autonomous cars built with Universal Design principles.
  • For people who are blind or have low vision, facial recognition and image recognition to support interaction with the environment.
  • For people with cognitive disabilities, language use to facilitate comprehension.
  • For job seekers with disabilities, with an unemployment rate of more than twice their non-disabled peers, outcomes can change with the development of accessible and intelligent AI solutions which will support job seekers and employees in developing their professional skills, improve workplace culture and expand inclusive hiring.

The concerns of WID, many corporations and public and private sector organizations focus on the critical need for AI standards for privacy, ethics and bias so that full inclusion of persons with disabilities in the evolution of AI occurs. Many of us foresee compounded risks of AI use unless there is commitment to and prioritization of privacy, ethics and bias.  For example:

  • Models learning from biased data may reproduce and continue historical biases;
  • Training data may under represent outlier populations, which often include people with disabilities, and therefore thwart or deny full inclusion;
  • Building inclusive data sets will prove essential for developing effective solutions, but also hold challenges such as requiring people to waive privacy rights;
  • Data collection, machine learning training protocols and programming may not include representation from individuals with disabilities or professionals in the field with the appropriate knowledge to plan for full inclusion; and,
  • Safety, security, bias and accessibility may be a lower priority than speed.

So, while AI is a great opportunity, it is also a great threat to full inclusion for people with disabilities.  Most researchers, accessibility experts, and disability rights organizations agree that building inclusive data sets is one of the greatest challenges for researchers and that AI accessibility should be a base level requirement for AI standards.

WID also recommends that persons with expertise in disability culture and accessibility be engaged early in the AI standards development, as well as those with expertise in recognizing and addressing implicit bias and those who can set guidance for developing inclusive data sets.  Inclusion of those with appropriate expertise will go far to achieve full inclusion of persons with disabilities in future data sets.

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