> zero trust information This is a mangled neologism for epistemic vigilance. We have many terms for epistemological outlooks that describe them without confla

> zero trust information This is a mangled neologism for epistemic vigilance. We have many terms for epistemological outlooks that describe them without conflating commitments and information at large. > Suppose that all published information followed a normal distribution [wrt quality of information]: Or don't, because that's not remotely close to true or useful for modeling what to do about it. This criticism is worth making because assuming a normal distribution of information quality makes the world already flat, and your problem reduces to news media bias. This type of simplification reflects tech-culture naïveté. It is not the case that all problems are simply waiting to be properly understood as simple by someone familiar with tech. > This is not to say that the Internet means that everything is going to be ok, either in the world generally or the coronavirus crisis specifically. But once we get through this crisis, it will be worth keeping in mind the story of Twitter and the heroic Seattle Flu Study team: what stopped them from doing critical research was too much centralization of authority and bureaucratic decision-making; what ultimately made their research materially accelerate the response of individuals and companies all over the country was first their bravery and sense of duty, and secondly the fact that on the Internet anyone can publish anything. This is not true. A push/pull of many factors plays into how modern science gets done. Some of those factors include centralization, bureaucracy, piracy, and individual judgment. It is neither useful nor accurate to claim that "centralization of authority and bureaucratic decision-making" prevented a group of researchers from exploring research predicated on genome sequences whose coordination, publication, and syndication all rely heavily on centralized infrastructure projects and public health institutions. Scientific and public health bureaucracies are complicated. Lifesci loves preprints and dodging publishers, but it also loves centralized bioinformatics and genomics infra. I am comfortable generalizing "lifesci" here, because it's damn near universal. Every [reasonable] educated person resents or at least distrusts medical regulators, especially those who work for them. So it's not saying much that yes, of course, scientists do too. Within lifesci, you would be hard-pressed to find scientists who aren't simultaneously saying "open access good", "publish your data at <centralized repository>", and "I can't believe that <govt agency> is <regulating something incredibly poorly>." This differs from attitudes of general populations, whose stances on health + safety + environment bureaucracies seem to be well-predicted by factors entirely unrelated to the efficacy of the tooling and services provided by those bureaucracies. Often that means keystone issues that reflect information diet, like views on GMOs and climate change. If the first word out of your mouth when discussing the needs of modern science is "centralization", you're engaging in wrongheaded techthink. It's worth doing something about, of course, but it truly is immaterial to the everyday workflows of most lab science. I see this error a lot in tech infrastructure projects. It's frustrating to see very cool, valuable things get built by scientist-coder teams who fail to appreciate that "decentralized x" is not a selling point for the vast majority of prospective users. These projects often fail to achieve good market fit because they treat problems of scientific research as if they're problems of consumer data privacy. Nobody BLASTs a sequence because they just love the bureaucratic directives of NCBI so much, nor do they contribute new GenBank sequence data for the clout. They do so because it helps make their work feasible. Don't underestimate the impact of that separation of concerns on scientific attitudes toward centralization. It matters a hell of a lot that researchers don't have to know how GenBank is built or what BLAST actually does as an algorithm.