One of the turning points of my life was watching a talk by Francisco Varela on connectivity. The key, he said, was to find a sweet spot - not too dense, otherwise the signals would overwhelm the network, and not too sparse, or the signal would never propagate. He was talking about immune networks, but it was clear to me that the principle applied more generally.
When we have an epidemic, the problem is that the signal - in this case, a virus - is spreading too rapidly. The basic reproduction number (R0) is used to measure the transmission potential of a disease. This number is based on the connectivity of the network - which is why we're applying social distancing. The same problems causing an epidemic, says this article, are the problems that cause misinformation. "The spread of misinformation is enabled by the structures of social networks. These structures reduce friction in sharing. They speed up flows of information and incentivise users to post things that will earn likes, replies and shares."
This is a structural problem. As Umair Haque said three years ago, "Social media has great economics: Facebook and Twitter and so on maximize incomes and earn fortunes. But it's eudaimonics are profoundly unsuccessful: it makes people unhappy, unfulfilled, and more distant - and it's a vector for misinformation and mistrust that's eating away at the fabric of democracy." We need to value the local more - maybe not so much as suggested by Jenny Mackness, but in that direction.
We do this by making it harder to be too big. In an economy, it should be much harder (not easier, as it is to day) to generate more income if you already have a lot of income. In a social network, it should be more expensive to amass large numbers of users, by making it harder to finance through mass-driven economics like advertising. In media, each additional person you reach with a message should cost more, not less. And, as we already know, in a pandemic, we make it much harder for the disease to find large numbers of people such as are found at sporting events and concerts. When you hear me talk about decentralized and distributed technology for learning networks, this is why.
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