A small selection of dozens of bookmarks from the past month. The one you should really be reading on all of this is Sarah Kendzior.
The Republican machine. The election was rigged. Everything mattered. Something is deeply broken. We all have plenty to fear. Is this how democracy ends? Is progress history? Trump’s looming mass criminalization. “These people.” The lessons of Berlusconi. Take danger at face value.
Google, democracy and the truth about internet search. It’s like the fascists saw John Perry Barlow’s Declaration of the Independence of Cyberspace and thought “Lebensraum!”
The Department for Education agreed to share pupil nationality data with the Home Office. What could possibly go wrong.
Kelp on White Beach, Tasmania, December 2009.
Kelp, a large seaweed that grows in underwater forests along temperate coasts, supports many marine species in turn. The Kelp Highway Hypothesis postulates that Pacific Rim kelp forests and the wealth of fish, mammals and birds that they supported sustained maritime hunter-gatherers spreading into the New World 16,000 years ago. Kelp species play an important role in Chinese, Japanese, and Korean cuisines, and fuelled the production of soda ash in the Scottish Highlands and islands until the industry’s collapse in the 19th century, which fuelled emigration to North America and beyond. Charles Darwin wrote of the kelp forests of Tierra del Fuego that “if in any country a [terrestrial] forest was destroyed, I do not believe nearly so many species of animals would perish as would here, from the destruction of the kelp”.
In October 2016, an ocean heatwave destroyed the last giant kelp forest on the east coast of Tasmania, bringing an end to an ecosystem that has dominated it for tens of thousands of years.
The Great A.I. Awakening: How Google used artificial intelligence to transform Google Translate (via Mefi) is a fantastic article, both for its contents and as a piece of journalism (I’m enjoying the author’s earlier article on travel photography as a result). As a computer science undergrad in the late 1980s, I took a course on AI, which involved building our own expert systems; it seemed obvious what a challenge that was always going to be, compared with some of the promising machine-learning alternatives. I now see that this was a brief window when neural networks were taken seriously, before their proponents were cast into the wilderness for the next decade and a half. That seems crazy to me, as someone who left the field. In the 1990s I was reading neuroscience theories about how minds emerge in an evolutionary way. Surely these theories and AI research would cross-fertilize each other, leading to new insights in both domains? But it seems that for a long time they didn’t. Maybe they will now.