Alex Iskold at Read/Write Web describes and analyzes the Implicit Web:
"What if there was a way to capture our choices automatically? What would that mean? Firstly, as Fred Wilson put it, we would be able to spy on ourselves. That is actually not as strange as it sounds. Just as we often refer to our respective browsing history, it would be great to automatically refer to the things we liked. Secondly, if our web-wide preferences were accessible to different web sites and web services, then they would be able to do a better job of personalizing our online experience. From recommendations to look n’ feel, a Web where our implicit preferences are automatically considered, would feel a lot more personal.
The Implicit Web is powered by clicks. When we click on things, we vote. When we spend time on a page, we vote. And when we copy and paste, we vote some more. Our gestures and actions reveal our intent and reactions. While it is impossible for an algorithm to always capture our intent with 100% certainty, a lot of software has gotten pretty good at doing it.
Typically, software that powers recommendation engines or search engines takes clicks, time and actions as inputs and feeds them into a sophisticated optimization algorithm. Usually, the algorithm assigns weights to different input parameters and then outputs a verdict – e.g. how much the user liked or disliked something."
While significant opportunities exist for the consumer version of the Implicit Web, it will also be an important part of the how emerging enterprise web applications evolve to improve personal and collaboration productivity and customer service.