by Stephen Downes
Jul 18, 2016
This is a summary of a study from Facebook, and it's important to keep in mind that Facebook is lobbying for a limited Facebook-only version of the internet in poorer countries. This is why it makes sense to say, for example, that "75% of the unconnected had never heard of the word 'internet.'" It's like they won't know what they're missing if they get only Facebook. That said, it is unacceptable that 4 billion don't have access to internet. And it's not because the internet isn't relevant ('reason 3') for these people, nor is it because they are not ready ('reason 4') for the internet. It has everything to do with a global model of resource distribution where the necessities of life and the means of producing them - not only internet, but food, energy, housing, and the rest - are provided only to those who can pay for them. Facebook's wealth, and the system that produced it, is the reason 4 billion people are offline.
Kevin Kelly has a long history of being wrong about the future and his streak will continue with this article. The world he depicts here is not some sort Star Trek Federation economy or socialist ideal - it's an end-state for a capitalist dream, where all ownership has been consolidated in corporations and individual people have nothing of their own. It's a world where, if you don't pay, you don't have anything, which means that (as today) social control and individual labour will be secured by corporations through the threat of cutting access to food, housing, entertainment, and more. Security, continuity, affinity - these are important to people, and physical objects are tangible instances of them.
"It's at the intersection of machine learning and graph technology where the next evolution lies and where new disruptive companies are emerging," according to this article. These are neural network technologies, and they work by analyzing connections, not contents. But there's a difference between 'machine learning' and 'graph technologies'. "machine learning takes large quantities of data to make predictions about future events. While graph technology is more concerned with the relationship between different data points... Some ML methods use ‘graphs’ to represent the learnings while others don't.”"
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