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Web search engines have become indispensable tools for finding information online effectively. As the range of information, context and users of Internet searches has grown, the relationship between the search query, search interest and user has become more tenuous. Not all users are seeking the same information, even if they use the same query term. Thus, the quality of search results has, at least potentially, been decreasing. Search engines have begun to respond to this problem by trying to personalise search in order to deliver more relevant results to the users. A query is now evaluated in the context of a user's search history and other data compiled into a personal profile and associated with statistical groups. This, at least, is the promise stated by the search engines themselves. This paper tries to assess the current reality of the personalisation of search results. We analyse the mechanisms of personalisation in the case of Google web search by empirically testing three commonly held assumptions about what personalisation does. To do this, we developed new digital methods which are explained here. The findings suggest that Google personal search does not fully provide the much-touted benefits for its search users. More likely, it seems to serve the interest of advertisers in providing more relevant audiences to them.

You know how our social graphs are creeping into every aspect of our web lives, from search results to coupons? Well, get ready for something a lot more personal, a lot more targeted and, perhaps, a lot more creepy. Much as social graphs are maps of our social media connections that follow us across the web, interest graphs are maps of our interests. Some companies want them to follow us across the web, too, meaning that wherever we go, there we are. There'll be no more need to search through news sites for the stories we want, or shopping sites for the products we want, because the site will know as soon as we hit its system who we are and what we like. Whether you're fascinated or appalled by the idea of interest graphs, here's a taste of how they might work.

"There are many explanations for today's uncertain economy. But Nobel economist Joseph Stiglitz of Columbia University has advanced an analysis that's starting to resonate. In a recent article, Stiglitz says that our problem is "rooted in the kinds of jobs we have, the kind we need, and the kind we're losing, and rooted as well in the kind of workers we want, and the kind we don't know what to do with." To advance our economy, Stiglitz believes that wrenching, fundamental change is required - no less dramatic than the shifts experienced by an earlier generation during the Great Depression. While Stiglitz and I work in different worlds, I see evidence in all types of organizations that we need to better prepare, train, and inspire successful self-directed learners to meet today's challenges. As I see it, there are two big questions to consider. First, what are the critical 21st century skills that the workforce of tomorrow needs to develop and master today? Secondly, how can we improve our learning methods to enable the self-directed learner to thrive in this new environment?"

What do Color, Quora, Hunch, Blippy, and StockTwits have in common? They are examples of companies that generate value for their users by leveraging the concept of the Interest Graph. The list also features some of the most promising startups right now, having raised close to $100 million in venture funding. Pure coincidence?

Beware online "filter bubbles": Eli Pariser on TED.com As web companies strive to tailor their services (including news and search results) to our personal tastes, there's a dangerous unintended consequence: We get trapped in a "filter bubble" and don't get exposed to information that could challenge or broaden our worldview. Eli Pariser argues powerfully that this will ultimately prove to be bad for us and bad for democracy.