There's really two different capabilities being discussed here. One (the Northwestern example) is the actual generation of prose from an underlying data asset. There are certain well structured domains of information (baseball games, earnings announcements, etc) where this will most likely work quite well. The second capability is automating the analysis of new content. NewsScope falls into that category. It takes raw news (written by humans) and extracts key terms, entities and events to make that content more easily consumable by machines. If you're interested you can use the same Thomson Reuters tools that are under NewsScope on your own content. My site uses them to analyze news from feeds, throw most of it away and put the rest in the right places. Thomson makes this capability available to anybody for free at a project called OpenCalais (see http://viewer.opencalais.com/ to play with it). Another group has built it into a complete publishing platform called OpenPublish.

Great point. I was over-focusing on the economic / hassle factor. You're correct that a potentially even greater impact is the fragmentation of our society based on profiles and stereotypes. I travel to Israel regularly where profiling (say - at a club or the airport) is a 100% accepted practice. Why - it works. The downside - a 2 tier society.

It's important to remember that the goal here is not to bring down planes or buildings - it's to create turmoil and terror. Simple actions like this cause millions to billions of dollars of cost to our economy for the investment of a can of lighter fluid and a firecracker. Because of one case of semi-successful action by one clown millions of us will now be subject to ineffective additional screening, more TSA invasions of privacy and general police state tactics, more delays. I don't have the answer - but I know the ROI from a terrorist perspective is outstanding.

If you're in the world of investigative journalism I'd encourage you to take a look at a new class of semantic data generation tools. New capabilities like Calais (www.opencalais.com) from Thomson Reuters allow you to ingest unstructured text (news articles, press releases, FOIA documents, whatever) and automatically extract semantic metadata like people, companies, management changes, natural disasters and hundreds of others. You can take the output of these tools and load them directly into databases to query. You could take news stories and build a social network of family relationships then play news events against the network. We're already seeing some initial uses in the area of investigative journalism and would love to see more. Jump in and give it a try.

Ummh, I think that's the point. The concept - first advocated by Tim Berners Lee - has been around for a long time. The technology to make it real has not. This is a big step in that direction. It's not the whole answer - but services like this will help overcome one of the key constraining factors: ubiquitous metadata tagging of content.