A highly recommended and very long post from Edge on Danny Hillis and his view on the future evolution of the web with interesting comments from leading thinkers like Stewart Brand (GBN), Jaron Lanier, Douglas Rushkoff, Marc Hauser, Bruce Sterling (Wired, WorldChanging), Esther Dyson, Freeman Dyson and Howard Gardner. It touches many, many emergent web trends.
Semantic Web or Web 3.0 is about the World Wide Database instead of WWW. It is about structured, more machine readable data and information on the web. It is about advanced and accellerating eLearning, the next phase of the web after the current entertainment and community phase within Web 2.0. Focusing in factual and procedural knowledge. There are many interesting and current case studies integrating some aspects or technologies of the semantic web. Examples: FreeBase, Hakia, Radar Networks, MetaWeb, Joost and RealTravel. While I am not 100% sure about this at this moment, I do believe Google Base can be included in this space as well. It combines structured data with bottom-up, collective tagging systems.
What does this all mean ?
- Machine learning -> more outsourcing of (factual) tasks to bots and agents -> people will devote more time towards local low-end services, higher-level (symbolic) thinking and other human-specific skills/talents like soft skills (intuitive creativity, communicative/emotional/social skills).
- Better search engine results/experiences -> higher productivity and more innovation
- More self-aware/correcting nature of online articles/posts dynamically integrating feedback loops on predictions in their texts. This allows for more easily deciphering the true nature of experts making future claims in their fields. This is a boost for reputational systems. Think more structured Wikipedia self regulation.
- Better data remixes/mash-ups -> higher productivity and more innovation
- Less impact of SEO (spam) tactics due to rise of structured and verified (!) data (formats) like PICS, Content Labels and microformats. The content of (commercial) websites will be indexed more authentically bringing back a better search engine experience for end users
- Deepens the impact, breadth and relevance of Mixed and Augmented Reality (AR) applications
Most importantly in my view is that a Knowledge Web has to take into account the mental, evolutionary state of the recipient as to be truly effective. Communication and learning is a two-way street. How does the Knowledge Web know about this mental state ? Through personalization ? Behavorial, contextual, profiled, social networked history ? Through emotional sensing ? MIT and DARPA (Pentagon) are working on these (recipient) items as well (Emotional Computing and Cognitive Augmentation).
"As useful as the Web is, it still falls far short of Alexander's tutor or even Vennavar Bush's Memex. For one thing, the Web knows very little about you (except maybe your credit card number). It has no model of how you learn, or what you do and do not know—or, for that matter, what it does and does not know. The information in the Web is disorganized, inconsistent, and often incorrect. Yet for all its faults, the Web is good enough to give us a hint of what is possible.
It is changing the way we learn. For example, one topic in the knowledge web might be Kepler's third law (that the square of a planet's orbital period is proportional to the cube of its distance from the sun). This concept would be connected to examples and demonstrations of the law, experiments showing that it is true, graphical and mathematical descriptions, stories about the history of its discovery, and explanations of the law in terms of other concepts. For instance, there might be a mathematical explanation of the law in terms of angular momentum, using calculus. Such an explanation might be perfect for a calculus-loving student who is familiar with angular momentum. Another student might prefer a picture or an interactive simulation. The database would contain information, presumably learned from experience, about which explanations would work well for which student. It would contain representations of many successful paths to understanding Kepler's law.
In retrospect the key idea in the "Aristotle" essay was this: if humans could contribute their knowledge to a database that could be read by computers, then the computers could present that knowledge to humans in the time, place and format that would be most useful to them. The missing link to make the idea work was a universal database containing all human knowledge, represented in a form that could be accessed, filtered and interpreted by computers.
One might reasonably ask: Why isn't that database the Wikipedia or even the World Wide Web? The answer is that these depositories of knowledge are designed to be read directly by humans, not interpreted by computers. They confound the presentation of information with the information itself. The crucial difference of the knowledge web is that the information is represented in the database, while the presentation is generated dynamically. Like Neal Stephenson's storybook, the information is filtered, selected and presented according to the specific needs of the viewer.
Most search engines are about algorithms and statistics without structure, while databases have been solely about structure until now, Esther Dyson said."In the middle there is something that represents things as they are," she said. "Something that captures the relationships between things." That addition has long been a vision of researchers in artificial intelligence. "It's like a system for building the synapses for the global brain," said Tim O'Reilly."