A Quote by Tarleton Gillespie

These algorithms, which I'll call public relevance algorithms, are-by the very same mathematical procedures-producing and certifying knowledge. The algorithmic assessment of information, then, represents a particular knowledge logic, one built on specific presumptions about what knowledge is and how one should identify its most relevant components. That we are now turning to algorithms to identify what we need to know is as momentous as having relied on credentialed experts, the scientific method, common sense, or the word of God.
Experts are able to identify patterns related to a specific problem relevant to their area of knowledge. But because nonexperts lack that base of knowledge, they are forced to rely more on their brain's ability for abstraction rather than specificity.
When Spotify launched in the U.S. in 2011, it relied on simple usage-based algorithms to connect users and music, a process known as 'collaborative filtering.' These algorithms were more often annoying than useful.
The problem with Google is you have 360 degrees of omnidirectional information on a linear basis, but the algorithms for irony and ambiguity are not there. And those are the algorithms of wisdom.
In deep learning, the algorithms we use now are versions of the algorithms we were developing in the 1980s, the 1990s. People were very optimistic about them, but it turns out they didn't work too well.
As algorithms push humans out of the job market, wealth and power might become concentrated in the hands of the tiny elite that owns the all-powerful algorithms, creating unprecedented social and political inequality. Alternatively, the algorithms might themselves become the owners.
We have heard of a Society for the Diffusion of Useful Knowledge. It is said that knowledge is power, and the like. Methinks there is equal need of a Society for the Diffusion of Useful Ignorance, what we will call Beautiful Knowledge, a knowledge useful in a higher sense: for what is most of our boasted so-called knowledge but a conceit that we know something, which robs us of the advantage of our actual ignorance? What we call knowledge is often our positive ignorance; ignorance our negative knowledge.
Knowledge without know-how is sterile. We use the word academic in a pejorative sense to identify this limitation.
On a strategic level, employers really are behaving stupidly. Look at how they do recruiting: this automated process under which they will publish a job description chock full of so-called "key words", and then have software algorithms that attempt to match applicants to the resumes against those key words. So where in the key word collection do we capture institutional knowledge? No one advertises for that. Of course they don't.
Scientists need the infrastructure for scientific search to aid their research, and they need it to offer relevancy and ways to separate the wheat from the chaff - the useful from the noise - via AI-enabled algorithms. With AI, such an infrastructure would be able to identify the exact study a scientist needs from the tens of thousands on a topic.
Learn when and how to use different data structures and their algorithms in your own code. This is harder as a student, as the problem assignments you'll work through just won't impart this knowledge. That's fine.
Once you see the problems that algorithms can introduce, people can be quick to want to throw them away altogether and think the situation would be resolved by sticking to human decisions until the algorithms are better.
Knowledge is theory. We should be thankful if action of management is based on theory. Knowledge has temporal spread. Information is not knowledge. The world is drowning in information but is slow in acquisition of knowledge. There is no substitute for knowledge.
We achieve self knowledge through the Kundalini. Now the journey starts towards God knowledge. Without self knowledge one cannot know about God as actualised knowledge.
Now I wonder what our knowledge has in common with God's knowledge according to those who treat God's knowledge... Is there anything else common to both besides the mere name? ...there is an essential distinction between His knowledge and ours, like the distinction between the substance of the heavens and that of the earth.
The classes of problems which are respectively known and not known to have good algorithms are of great theoretical interest. [...] I conjecture that there is no good algorithm for the traveling salesman problem. My reasons are the same as for any mathematical conjecture: (1) It is a legitimate mathematical possibility, and (2) I do not know.
The knowledge we now consider knowledge proves itself in action. What we now mean by knowledge is information effective in action, information focused on results. Results are outside the person, in society and economy, or in the advancement of knowledge itself. To accomplish anything this knowledge has to be highly specialized.
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