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Billions of people use social media everyday, all over the world. Once you start using networks like Twitter, Facebook and YouTube often enough, you start to notice that people share similar (and often rather annoying) online media habits, and can be categorised into common personality types.

Social media is having an increasingly pervasive influence on both personal and professional life. But there is still widespread ignorance about the risks associated with using it. The Snowden revelations gave us the first insight into how our personal data is being "harvested" by both companies and governments, and not all of it for benign purposes. This (preliminary) declaration of digital human rights is something that perhaps we should all give serious consideration to supporting.

The new rules generally expand the definition of personal data - so it can include information such as location data, online identifiers (such as IP addresses) and other metadata. So again, this means businesses really need to conduct an audit to identify all the types of personal data they hold. Ignorance is not compliance.

A recent MIT study found that in one organization the employees with the most extensive personal digital networks were 7% more productive than their colleagues - so Wikis and Web 2.0 tools may indeed improve productivity. In the same organization, however, the employees with the most cohesive face-to-face networks were 30% more productive.

The baton passing technique is a fast method for sharing, identifying high-impact lessons and gaining personal commitment to action. Baton passing can either be 'fast' - when based on clear lesson-themes - or 'slow' and more detailed when connected to a specific business process involving complex issues

"When given the choice of whom to work with, people will pick one person over another for any number of reasons: the prestige of being associated with a star performer, for example, or the hope that spending time with a strategically placed superior will further their careers. But in most cases, people choose their work partners according to two criteria. One is competence at the job (Does Joe know what he's doing?). The other is likability (Is Joe enjoyable to work with?). Obviously, both things matter. Less obvious is how much they matter-and exactly how they matter."

"Smart Wikis™ combine Artificial Intelligence and knowledge concepts with your existing IT to provide integrated collaborative working environments that anticipate each user's personal information needs and surround that user with seamless and non-obtrusive forms of assistance."

Fictional story written in the first person by an autonomous bomb disposal robot. Raises fascinating questions about social robotics ethics.

AI being used for driverless cars, energy saving and personal assistants (bots)

KIN has long stressed the importance of learning from failure. In this short, funny and revealing post, David D'Souza publicly shares his experience of what not to do in a TV interview. His post uses humour, it's punchy (note the bullet points) and is in the first-person. I doubt I'll ever be on TV, but everyone could immediately relate to and learn from this. Now that's real learning from failure - the antithesis of a dry 'lessons learned' report.

KM Maturity models are popular as a way of self-measuring progress, but personally I think they are inappropriate and can lead you into a wrong understanding of KM, and that there are much better alternatives.

Article on senior managers' 'Personal Knowledge Infrastructure'. Davide Nicolini, Prof of Organizational Studies at Warwick Business School and Director of KIN

the Diigo team aims to evolve Diigo into the best personal knowledge management system (PKM) on the market, providing unsurpassed capabilities for the collection, compilation, organization, digestion, presentation and collaboration of knowledge and information.

Humans are biased, and the biases we encode into machines are then scaled and automated. This is not inherently bad (or good), but it raises the question: how do we operate in a world increasingly consumed with "personal analytics" that can predict race, religion, gender, age, sexual orientation, health status and much more.

The Getting Things Done method rests on the principle that a person needs to move tasks out of the mind by recording them externally. That way, the mind is freed from the job of remembering everything that needs to be done, and can concentrate on actually performing those tasks.

The average piece of user-generated content (UGC) is awful. It's actually way worse than you think. It can be rife with misspellings, vulgarity or flat-out wrong information. But by identifying the best and worst UGC, machine-learning models can filter out the bad and bubble up the good without needing a real person to tag each piece of content.

Suggestic, an application and Internet-based platform, is looking to fuse medical advances with a growing trend of personalized healthcare - making interventions specific to the individual patient. The company launched a beta version of its technology earlier this month and has a few thousand people signed up in their waiting list to try out the service.