- From: Shawn Henry <shawn@w3.org>
- Date: Wed, 10 Oct 2018 15:25:29 -0500
- To: Sharron Rush <srush@knowbility.org>, Sylvie Duchateau <contact@sylvie-duchateau.fr>
- Cc: wai-eo-editors <wai-eo-editors@w3.org>
Thanks for the review and comments, Sylvie. Comments on first to are below preceded with "Shawn's thoughts:" You wrote: 1. Regarding case studies, the only examples are Apple and Google. Even if I understand the arguments, it may happen that some people will say: you only mention big companies who have the means to provide those services. Unfortunately, I cannot think of other good examples. May be it could help to have an introduction sentence explaining why the two giants were chosen for the case study. Shawn's thoughts: Good point about the potential misunderstanding that only big companies have means to address accessibility. We should keep on the lookout for ways to address that -- for example, specifically look for case studies, quotes, or other examples of small organizations. (Sharron, do you want to record that somewhere? possibly a GitHub issue that we leave open just to help us remember it?) The reason the two giants were chosen was basically because that is all the info we could gather. I don't think there is a smooth way to say that. Sharron says: There are actually several case studies, including Barclay's Bank, Winn-Dixie grocery store, and the NPR radio show "This American Life." However, in the innovation section those are the two. I therefore added this leading sentence: "Tech giants Apple and Google are recognized as leading innovators. Their development practices demonstrate the value of accessible design thinking." Let me know if that is OK. Shawn's thoughts: I think including "Tech giants" emphases the issue that was Sylvie's concern even more. Also, we shouldn't say "are recognized as leading innovators", given the vendor-neutrality issues. So I think just go back to how you had it before. "Apple development practice is another demonstration of how accessibility can drive innovation." 2. In the case study on Google, I would be cautious with the last bullet: "auto-captioning for the deaf using machine learning is now being turned to broader applications". Many deaf and hard of hearing people complain that auto-captioning is a catastrophe. Sometimes it displays the contrary of what the person said. In a video, auto captioning transcribed the noise of the white cane of a blind person as applause. So I am not sure that auto-captioning is a good argument. Sharron says: I added this to the last bullet: "auto-captioning for the deaf using machine learning was problematic at first and as it has been steadily improving, is now being turned to broader applications" Shawn's thoughts: Unfortunately I don't think that takes care of the issue. auto-captioning is still far from an acceptable solution. Some brainstorms on how to address it: * delete the whole bullet. * "auto-captioning using machine learning that can be used as a first step to generating effective captions for people who are deaf is now being turned to broader applications" Best, ~Shawn
Received on Wednesday, 10 October 2018 20:25:38 UTC