I love the Diderot quote. I'd also encountered earlier:

"As long as the centuries continue to unfold, the number of books will grow continually, and one can predict that a time will come when it will be almost as difficult to learn anything from books as from the direct study of the whole universe. It will be almost as convenient to search for some bit of truth concealed in nature as it will be to find it hidden away in an immense multitude of bound volumes. When that time comes, a project, until then neglected because the need for it was not felt, will have to be undertaken...."

... and on for another several paragraphs. It's an extraordinarily keen observation on the state and future of knowledge. At the always excellent History of Information website:

http://www.historyofinformation.com/detail.php?entryid=2877

(Diderot is on my list of authors to explore in more depth.)

The fact that the quality of any given information or exchange is often (though not always) entirely divorced from its source (or author) is another interesting note. There are a few points here worth expanding on.

At least probabalistically, there are spaces (real or virtual) in which it's more likely to encounter good ideas. HN for its various failings, does well in today's Net. Google+, for all its faults, was similarly useful.

Size matters far less than selection. The tendency for centres of learning, research, and/or inquiry (and not necessarily in that order) to emerge is one that's been long observed, and their durability remarkable. The first universities (Bologna, Padua, Oxford, Paris, Cambridge, Heidelberg, and others, see: https://en.wikipedia.org/wiki/Medieval_university) are often still, 600 - 700 years later among the best in the world. Certainly in the US, Harvard, Yale, Princeton, M.I.T., among the earliest founded, remain the most prestigious. Though as noted in the conversation with Tyler Cowen and Patrick Collison, the list from 1920 is "completely the same, except we’ve added on California".

https://conversationswithtyler.com/episodes/mark-zuckerberg-...

What happens as the overal quantity and flux of information increases is that more effective rejection systems are required. That is: you've got too much information flowing in, you want a way to cheaply, with minimal effort or consequential residiual load, reject information that may be irrelevant, with minimal bias.

There are numerous systems that have been arrived at, and many of our cognitive biases or informal tests for truth arise out of these (optimism, pessimism, availability, sunk-cost, tradition, popularity, socio-ethnic prejudice, etc.). Randomised methods are probably far fairer and less prone to category error. Michael Schulson's sortition essay in Aeon remains among the best articles I've read in the past decade, if not several:

"If You Can't Choose Wisely, Choose Randomly"

https://aeon.co/essays/if-you-can-t-choose-wisely-choose-ran...

Another fundamental problem is self-dealing and self-selection within institutions. Much of the failure within academia (also touched on by Cowen and Collison, who, I'll note, I don't generally agree with, though they are touching on and making many points I've been pursuing for some years) comes from the fact that it's internal selection of students, faculty, articles, topics, and ideologies, rather than strict tests of real-world validity, which promote these structures.

The same problems infect government and business -- it's not as if any one social domain is immune to this.

Oh, and another lecture by H.G. Wells on that topic:

"...When I go to see my government in Westminster I find presiding over it the Speaker in a wig and a costume of the time of Dean Swift, the procedure is in its essence very much the same. The Members debate bring motions and when they divide the art of counting still in governing bodies being in its infancy they crowd into lobbies and are counted just as a drover would have counted his sheep two thousand years ago...."

https://invidio.us/watch?v=qRgP-46AC_o

(Audio quality is exceptionally poor, 1931 recording.)

Partial transcript: http://www.aparchive.com/metadata/INTERVIEW-WITH-H-G-WELLS-S...

AI ... may be useful, but seems to be result-without-explanation, a possible new form of knowledge, to go with revelation (pervasive if not particularly acurate), technical (means), and scientific (causes / structural).

Wholehearted agreement on LibGen.

Very enjoyable conversation BTW, thank you.