I saw a great talk from Alan Kay where he gives an argument that studying historical systems is important for innovation: Imagine all the possible directions computing could move toward over the next 50-60 years. Some will be good (near-optimal), but others will probably be a waste of time and merely pursued out of fashion, while some of today's good ideas will be dropped and forgotten.
Thus in the future, when programmers find they've reached a "dead end" / local maximum, they might study ideas from 2018 and find a way forward. In the same way, someone who wants to innovate today could be advised to explore some of the "paths not taken" from the 1950's and 60's.
I saw a great talk from Alan Kay where he gives an argument that studying historical systems is important for innovation: Imagine all the possible directions computing could move toward over the next 50-60 years. Some will be good (near-optimal), but others will probably be a waste of time and merely pursued out of fashion, while some of today's good ideas will be dropped and forgotten.
Thus in the future, when programmers find they've reached a "dead end" / local maximum, they might study ideas from 2018 and find a way forward. In the same way, someone who wants to innovate today could be advised to explore some of the "paths not taken" from the 1950's and 60's.