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"In a follow-up article published this week titled "No, a Remote Amazon Tribe Did Not Get Addicted to Porn," Nicas wrote that the aggregations of his article showed in part that the internet truly is a dark place, in part because of the way the story spread: "The Marubo people are not addicted to pornography. There was no hint of this in the forest, and there was no suggestion of it in The New York Times's article." In this article, Nicas blames the people who aggregated him for sensationalizing his article. That may be true, but Nicas's article is also sensationalist.  While the article does explore the history of Marubo people getting access to motor boats and radios and notes "(Some Marubo already had phones, often bought with government welfare checks, to take photographs and communicate when in a city)," it does not explain that many Marubo people have been using the internet for quite some time, and implies that the problems they are now grappling with are things that the Marubo people hadn't thought about before."

"For many experts however, the greatest risk to the internet isn't sabotage, espionage, or even rogue anchors - but the uneven spread of the cable infrastructure that threads across the globe, binding the world's digital networks together. "There aren't cables everywhere," says Starosielski. "There is a concentration in the north Atlantic Ocean connecting the United States and Europe but there are not that many in the South Atlantic.""

"Exposure to false and inflammatory content is remarkably low, with just 1% of Twitter users accounting for 80% of exposure to dubious websites during the 2016 U.S. election. This is heavily concentrated among a small fringe of users actively seeking it out. Examples: 6.3% of YouTube users were responsible for 79.8% of exposure to extremist channels from July to December 2020, 85% of vaccine-sceptical content was consumed by less than 1% of US citizens in the 2016-2019 period. Conventional wisdom blames platform algorithms for spreading misinformation. However, evidence suggests user preferences play an outsized role. For instance, a mere 0.04% of YouTube's algorithmic recommendations directed users to extremist content. It's tempting to draw a straight line between social media usage and societal ills. But studies rigorously designed to untangle cause and effect often come up short. "

"I started to feel that propaganda had fundamentally changed. The types of actors who could create it and spread it had shifted, and the impact it was having on our society was quite significant, but we weren't using the word. We were using words like "misinformation" or "disinformation", which seemed to be misdiagnoses of the problem. And so I wanted to write a book that asked, in this media ecosystem, what does propaganda look like?"

"First, lucrative state contracts are given to private corporations to build and deploy policing technologies that surveil and manage target groups. Then, using the vast amounts of biometric and social media data extracted from those groups, the private companies improve their technologies and sell retail versions of them to other states and institutions, such as schools. Finally, all this turns the target groups into a ready source of cheap labor - either through direct coercion or indirectly through stigma."