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flux_capacitor73 t1_izppnpd wrote

To a degree these systems are block box, or at least relatively opaque. They can provide results which are difficult to understand. There's work being done to counter this, but there definitely are legitimate concerns.

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321gogo t1_izqfe7j wrote

> they provide results that are difficult to understand

Care to elaborate on this? I’m no expert in AI/ML, but generally I wouldn’t say the results are difficult to understand. I think it’s pretty clear that computers can outperform humans by a wide margin in analyzing large sets of data. Most of these concepts are applications of this computing power.

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flux_capacitor73 t1_izrh3el wrote

There's an example where an ad bot from target would predict the pregnancy of its customer by look at the purchase of certain items. Human advertisers weren't able to figure it out.

This example is benign, but others are problematic.

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321gogo t1_izrjlai wrote

What do you mean “figure it out”? I’m not familiar with the example, but this sounds like a fairly simple application of ML. At the end of the day it is just finding trends in extremely large datasets that humans don’t have the brain power to process. Just because humans can’t do that work doesn’t mean we can’t understand it.

For example with predicting the pregnancy. A human might try to predict this by working backwards. You can first just try to understand the persons age and if they are female. Not too crazy to figure out from purchase history. Maybe you see that the person is in a relationship because they started buying Mens shampoo. Maybe they started buying dogfood and you find in your training data people tend to have a child within a few years of getting a pet. Tons of little things that can point you in the right direction. Now a computer is just doing this but ramped up to the max. The applications are very simple, the computation is the part the is complex.

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