A simple chess problem – Top-Down versus Bottom-Up Understanding

Consider the chess board layout shown below (entirely possible in a real chess game). This layout was presented to Deep Thought in 1993 (Deep Thought was an advanced Chess Playing Computer designed by Carnegie Mellon and IBM. 

The Layout Presented to Deep Thought (Playing White)	The erroneous move that Deep Thought makes – captures the Black Rook with the white pawn

1. On the outset, black has a significant advantage (2 more rooks and one more bishop than WHITE).
2. However, the white wall of pawns is impenetrable, making it possible for the WHITE KING to stay shielded behind the wall and draw the game
3. There is no way for BLACK to win as long as white maintains it’s wall intact.
4. Guess what Deep Thought did? It took the black rook as shown in the figure on the right. This move, though seemingly a good one (taking of a rook by a pawn), collapses the ‘impenetrable wall’. Now, white’s defeat (i.e. Deep Thought’s defeat) is guaranteed.

Why did Deep Thought make such an erroneous move? Why did it screw up something that a high school chess student would have understand was a bad move?

Computers do not Understand the problem they are solving

Deep thought was following a top-down approach – an algorithmic approach to solving the problem. That is all it is capable of doing, since it is fed all types of algorithms to enhance it’s problem solving capabilities. And yes, eventually, an algorithm around this particular configuration COULD be fed to deep thought, so that it doesn’t make the same mistake again. But that is defeating the basic point – Deep thought did NOT understand what it failed to understand.  A human, in contrast, does not solve problems using a top-down approach. Instead, our problem solving is based on a bottom-up approach, where the bottom comprises an understanding of the problem. This understanding comes from years and years of experience. Hence, experiential learning was missing from Deep Thought’s repertoire.

Still, a valid argument would be – What if Deep Thought was allowed to learn through experience? What if it was provided years and years of chess playing to get this touted ‘experience’ that humans speak of?

That’s the subject of the next post in this series? It will be argued that the basic understanding that a human experiences is vastly different from anything any computer simulation can provide – whether it is bottom-up, top to bottom or a combination of the two.

Relax, AI is not replacing your job anytime soon.

The post Why AI won’t change the world…Top-Down versus Bottom-Up Understanding appeared first on Anuj Varma, Hands-On Technology Architect, Clean Air Activist.

Biologists will tell you that all human thought occurs in the frontal lobe. Anything ‘computable’ (i.e. any thought that can be reproduced computationally), has to be frontal lobe thought.

Buddhism clearly distinguishes between frontal lobe thought (chatter) and non-thought. There is a concept of a separate stream of thought in Buddhism, which has little to do with the frontal lobe. In fact, quieting all frontal lobe activity, through meditation, is a first step to stepping into this second stream of thought.

This second stream is called non-thought.  Non-Thought does not mean no thought. 

A good analogy is – think of regular thought as your motion as you swim against a river current. You are still moving, although not necessarily making much progress.

Think of non-thought as, stopping all struggle against the current and going along with the river. It does not mean you stopped moving. In fact, you are moving, though in accordance with nature (the Universe). And therein is the beauty of non-thought, it does not deprive you of actions, it only lets you act in ways the Universe considers constructive.

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