Heuretics come out of people’s brains (TECHNOLOGY IS PEOPLE)

# Many approaches to augmented knowledge generation ignore humans
It’s tempting to see knowledge as the corpus of written documents and connections between them. These connections can be either explicit through citations and other references, or implicit through shared authorship, topics, or language. 

The theoretical backing for this idea is laid out in [[Undiscovered Public Knowledge (Paper)]]. The argument in UPK is that knowledge in people’s heads is subjective knowledge, which is subsidiary to objective knowledge which includes everything written down and the *implied* connections between those things. Thus, the goal is to more effectively retrieve things from the world of objective knowledge and draw connections between them. 

In other words, [[UPKD assumes that all valuable knowledge is both written down somewhere and interpretable when you find it]]. This ignores the prevalence of [[Tacit Knowledge]] in the world, especially at the [[Knowledge frontier]]. In other words, it ignores the the knowledge that is in human brains. This is problematic considering [[Heuretics come out of people’s brains (TECHNOLOGY IS PEOPLE)]].

I would argue that [[Most human knowledge is not encoded]], and may be impossible to encode without some fundamental discoveries. [[In order for knowledge to be discoverable and interpretable that means that it needs to be encodable]]. Even ignoring unencodable knowledge and accepting UPK’s knowledge model, most interesting areas are still replete with people still in the process of generating subjective knowledge and figuring out how to encode it (or who are too busy or are missing the skills necessary to encode it well.) 

Perhaps there’s a way around these two barriers, but I don’t see it. Instead,  [[Treat people as nodes and artifacts as edges]]

### Related
- [[Fast moving fields have lots of unconnected nodes]]
- [[Researchers are more important than the research]]
- [[Process Knowledge]]



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Do a deep dive into the different attempts at algorithmic knowledge generation

Joel Chan Conversation 13/2/20

Many approaches to augmented knowledge generation ignore humans

# What if instead of doing knowledge maps where you draw connections between papers, you model it with people as the nodes and papers as the edges? 
So many time reading a paper is mostly worthless except as a pointer to the people you need to talk to

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Ben's working notes

What if instead of doing knowledge maps where you draw connections between papers, you model it with people as the nodes and papers as the edges?

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