Deeper Learing

A recent article (1) that demonstrates how neural networks could be used to approximate light scattering by nanoparticles is an interesting new direction. We appear to be approaching a regime in which prescriptive analytical solutions and conventional simulation become inferior to deep learning. This is exciting but it also presents a huge downside for the advancement of abstract knowledge. Models that show robust outcomes are welcome but a generation of new scientists, prone to taking to the machine to prove hypotheses, by feeding them small samples of historical data, could dampen theoretical advancement not only in Physics but also in other areas.

This struggle between empiricism and rationalism has been with humans from inception. Did they survive by predicting where the lion is likely to be by using historical data of previous (bad) outcomes or did they rationalize by abstracting the expected behavior of the animal? Did they predict when an animal is likely to attack by using historical data on the timing of previous attacks or did they understand the animal's incentives and available alternatives? Did they migrate incrementally by using predictions, originating from previous short excursions, or did they go boldly where no woman had ever gone? Were our ancestors empiricists or rationalists?

It is difficult to ascertain one way or the other. It appears that empiricism has been a hidden attribute in our psyche for long. Till the advent of computers, rationalism appears to have dominated but since then, empiricism has been on a steep rise. In Physics, they now collect and stream data to find "new particles," without even asking why such observations are important. In medicine, they "high throughput screen" looking for the needle in the haystack, without a clear understanding of the mechanism of action. In economics, they regress data to find insights without asking whether they are insights at all.

There is likely no stopping the trend. As computers get more powerful, empiricism will become ever more dominant. If this is a natural outcome of evolution, then, advanced societies elsewhere (if they do exist) would be asymptomatically approaching pure empiricism for knowledge generation. That could be there Achille's heal as it also means that their knowledge is dependent on the past. A planet full of robots, with no ability to abstract but with an infinite capacity to learn from the past, could be highly inefficient.

Would humans retain inefficient qualities of being a human? It seems unlikely.

(1) http://advances.sciencemag.org/content/4/6/eaar4206.full

Read more: http://www.scientificsense.com/2018/06/deeper-learning.html#ixzz5HJUCR99I 
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