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I tend to agree, and it’s weird but there are probably lots of actual ML practitioners that have never even heard of the neat vs scruffy debate. Naturally most

I tend to agree, and it’s weird but there are probably lots of actual ML practitioners that have never even heard of the neat vs scruffy debate. Naturally most that have heard of it will feel that the issue is completely resolved already in their favor. On the whole not a very open minded climate. Credit where it’s due for the wild success of fancy stats, but we should stay interested in hybrid systems with more emphasis on logic, symbols, graphs, interactions and whatever other data structures seem rich and expressive. Call me old school but frankly I prefer the society-of-mind flavor of system should ultimately be in charge of things like driving cars, running court proceedings, optimizing cities or whole economies. Let it use fancy stats as components and subsystems, sure.. but let it produce coherent arguments or critiques that can actually be understood and summarized and debugged.

andoando 3y ago
You make a very interesting point. Human understanding and logic can be very rationally explained. A judge can for example give a very though response of exactly why they made their verdict. I think that would be an excellent benchmark for AI. This seems rather impossible when your understanding of the world is connection of billions of messy and uncertain parameters. But perhaps this is the first step? Maybe we can take the neural nets trained by Ml and create constructions on top of it.