- From: Jim Allan <jimallan@tsbvi.edu>
- Date: Fri, 27 Jan 2012 14:40:45 -0600
- To: Jeanne Spellman <jeanne@w3.org>
- Cc: wed@csulb.edu, WAI-UA list <w3c-wai-ua@w3.org>
Going by Wayne's original document I would say the amount or quality AI involved simple guess versus complex heuristic.. I don;t thing we can say an existing implementation indicates ease, only that there was a good enough business case to make a feature. On Fri, Jan 27, 2012 at 12:45 PM, Jeanne Spellman <jeanne@w3.org> wrote: > Agreed, this is a useful analysis and I have already grabbed part of it to > put into the proposal for the level definitions. > > My question is: deterministic vs. inferential is one part of ease, but it > certainly isn't all of it. What are the factors that define ease? We > already have existing implementations indicate ease, but what else? > > What else makes a feature hard to implement? > > jeanne > > > On 1/27/2012 1:10 PM, Jim Allan wrote: >> >> Wayne, >> thanks for doing the thinking and writing on this. A good place to >> start. I agree with Chaals it strikes a good balance for ease vs >> impact. That's where we as a group can decide to push the level up or >> down. >> >> Jim >> >> On Thu, Jan 26, 2012 at 7:40 PM, Wayne Dick<wayneedick@gmail.com> wrote: >>> >>> Hi All, >>> >>> I wrote this to help us narrow feasibility to a reasonable range, so >>> we could use it in choosing Level A through AAA. We don't want to let >>> developer's off reasonable tasks, but we can't require excessive >>> development. >>> >>> http://www.csulb.edu/~wed/Feasibility.html >>> >>> Wayne >>> >> >> >> > -- Jim Allan, Accessibility Coordinator & Webmaster Texas School for the Blind and Visually Impaired 1100 W. 45th St., Austin, Texas 78756 voice 512.206.9315 fax: 512.206.9264 http://www.tsbvi.edu/ "We shape our tools and thereafter our tools shape us." McLuhan, 1964
Received on Friday, 27 January 2012 20:41:10 UTC