At some point in this scenario you outline, there will be so much ML generated content referencing generated content, the (already muddled) primary sources will be lost in the mix and the role of ML will be forced to synthesize sensible, meaningful content out of conflicting "truth".
What I'm trying to get at is that ML is currently terrible at contextualizing information, but in the future the successful knowledge-query engine will be the one that do the best job of wading through the explosion of digital content and pulling out the parts that are coherent and more connected to reality.
This program will need to be able to contextualize information to form a coherent model where knowledge is interconnected into a larger model of reality.
Easier said than done, we'll see if that is even possible. This is getting towards AGI.
What I'm trying to get at is that ML is currently terrible at contextualizing information, but in the future the successful knowledge-query engine will be the one that do the best job of wading through the explosion of digital content and pulling out the parts that are coherent and more connected to reality.
This program will need to be able to contextualize information to form a coherent model where knowledge is interconnected into a larger model of reality.
Easier said than done, we'll see if that is even possible. This is getting towards AGI.