Ed: MIT alumni. Artificial intelligence heuristics for tracking, inference, application. Cool. Go MIT.
A lot of clicks to track down this conversation thread. Too many distractions from the main thread.
The Alive Web
I find this concept very interesting, and important as we move from our current navigation/UI to new forms. New Scientist'scoverage:
SITES that evolve as if they were living organisms are making their way onto the internet.
This ability to adapt without human intervention allows sites to stay up to date with changes in their users' tastes and can result in designs that are more user-friendly than anything a human designer is likely to come up with. Evolving sites might also allow web designers to home in on the features that work best for users.
- Posted by John Battelle
Living web sites that grow, develop and evolve to suit the taste of the people that read them are now finding their way on to the internet...
For two decades, computer scientists have played around with evolutionary software that can gradually evolve and mutate to carry out a task efficiently, or hone the design of a wing, robot or whatever, without the need for a programmer to get involved.
A grouping of some of the sites with human controlled design properties or genetic design evolution Now these techniques are being used to allow web sites to keep themselves up to date and to adapt to the latest fads and fashion, reports New Scientist.
Not only are they quicker to evolve than possible with human intervention, they offer the chance to come up with new ways to organise material in the web that work best for users.
Matthew Hockenberry and Ernesto Arroyo of Creative Synthesis, a non-profit organisation in Cambridge, Massachusetts, have created evolutionary software that alters colours, fonts and hyperlinks of pages in response to what seems to grab the attention of the people who click on the site. Seewww.creativesynthesis.net for more.
The experiment measures a number of usability goals and attention metrics (such as mousetracking). Users were given the opportunity to utilize an analytic tool for mouse tracking. AI processes are used to offer possible interpretation of the results, such as identifying mouse tracks indicative of reading. A discussion interface created conversations focused on pattern identification of user behavior and comparisons between domain content. Users also noted the impact of customizations to the design outside the pre-seeded experimental options (such as color changes, etc.). Followup versions of the pilot included low level support for random variable mutation (organic canvas) similar to the outline described previously.
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