What comes after Web 2.0?

Typically, Web 2.0 is used by computer programmers to refer to a combination of a) improved communication between people via social-networking technologies, b) improved communication between separate software applications-read “mashups”-via open Web standards for describing and accessing data, and c) improved Web interfaces that mimic the real-time responsiveness of desktop applications within a browser window. To see how these ideas may evolve, and what may emerge after Web 2.0, one need only look to groups such as MIT’s Computer Science and Artificial Intelligence Laboratory, the World Wide Web Consortium, Amazon.com, and Google. All of these organizations are working for a smarter Web, and some of their prototype implementations are available on the Web for anyone to try. Many of these projects emphasize leveraging the human intelligence already embedded in the Web in the form of data, metadata, and links between data nodes. Others aim to recruit live humans and apply their intelligence to tasks computers can’t handle. The first category of projects is related to the Semantic Web, a vision for a smarter Web laid out in the late 1990s by World Wide Web creator Tim Berners-Lee. The vision calls for enriching every piece of data on the Web with metadata conveying its meaning. In theory, this added context would help Web-based software applications use the data more appropriately. A second category of post-Web 2.0 projects focuses not on helping machines understand the meaning and the uses of existing Web content, but on recruiting real people to add their intelligence to information before it’s used. The best known example is Amazon Mechanical Turk, a kind of high-tech temp agency introduced by the online retailer in 2005. The service allows people with tasks and questions that computers can’t handle – for example, spotting inappropriate images in a collection of photos—to hire other Web users to help. Another project that attempts to persuade humans to add meaning to raw data is the Google Image Labeler. It entices users to label digital photographs according to their content by making the task into a simple game in which contestants must both collaborate and compete. Like Amazon Mechanical Turk, the Image Labeler has a community of fans who enjoy it as a game. And there’s nothing wrong with making potentially dull tasks entertaining, if that’s what it takes to motivate “workers.”