Why are we using black box models in AI when we don’t need to? (2019)

Re:Why are we using black box models in AI when we don’t nee... by wongarsu on Sunday January 05, 2020 @09:50AM (#21961450)

The fact that objects fall down was well understood, obviously. What wasn't understood was the mechanism that makes this happen. Why did that apple fall down instead of up? Where exactly is down a round earth? Where is down when I stand next to the Himalaya? Why don't planets fall down?

In my eyes this is very similar to our lack of understanding about the inner workings of a CNN, or human vision. We understand the input and the output and their rough relationship, we just don't understand how the move from input to output happens.

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Re:Why are we using black box models in AI when we don’t nee... by agra on Sunday January 05, 2020 @02:32PM (#21963391)

I see it differently.

The distinction I would make is that even before Newton, people could make useful predictions about the trajectory of falling objects. My dog does it well, every time he catches a ball. He even seems to grok the effect of wind on a frisbee.

We have no way of predicting how a CNN will react to an input. GANs really illustrate this point. I think this is an important distinction.

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