RE: Scope of AI/ML and accessibility work

To Jason

Agree with comments and scope, the only thing I think has been overlooked is the need to specifically reference the term generative AI. Machine learning has been around for a long time, the part of it that has drawn the attention of the world to this work in recent times has been generative AI and based on my research, there's less familiarity outside of academic circles about machine learning as a term but a lot of familiarity in the public with the term of generative AI, so I think important that where applicable this is referenced as taking a straw poll of my 13 staff and a few dozen people in the meetup groups in the accessibility community here, few are aware of machine learning but all were familiar with generative AI and that's how the discussion is framed so just want to make sure our work isn't overlooked in our messaging not specifically including this term.

Other than that, a great summary of the work, scope and approach.

Scott.




Dr Scott Hollier
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From: Jason J.G. White <jason@jasonjgw.com>
Sent: Wednesday, July 31, 2024 10:07 PM
To: RQTF <public-rqtf@w3.org>
Subject: Scope of AI/ML and accessibility work

Based on Task Force discussions, it is my understanding that our document on AI/ML and accessibility is intended to address the application of machine learning models to enhancing the accessibility of Web content, as well as the accessibility of Web content which may be created by this technology (e.g., AI-generated text, audio or video).
This scope includes applications of machine learning used in

  *   Content creation and distribution (e.g., machine learning invoked by the author or Web site operator, including any third parties they engage). Authoring tools, code generation applications, and accessibility evaluation tools are all included in this category.
  *   Interaction with Web content by the end user, including machine learning technologies invoked by the user (possibly in an assistive technology or as part of a user agent). Machine learning applications that the user engages to enhance the accessibility of content are included. In addition, machine learning models invoked by the user as part of a Web application lie within our scope. For example, a text or image generation application built on machine learning technology that is available to the user as part of a Web application would be relevant to our work.
The purposes of our document include the identification of issues of accessibility to be considered in the development of these applications, and identification of currently applicable W3C standards, as well as other suggested practices or approaches that we choose to discuss.
The use of machine learning to make decisions about the rights, privileges or responsibilities of individuals (including people with disabilities), and the questions of discrimination that these applications pose, lie outside the scope of our work, even if such applications happen to be available via the Web. For example, an application designed to assess recidivism risk in the criminal justice context raises important policy questions, but it is outside our scope.
Comments are welcome, as Janina plans to integrate these considerations into forthcoming draft text.