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Why would anyone use machine learning if not to create systems they don't understand ? That's the whole point of doing it. Not having to understand complex syst
by iofj 10y ago
Why would anyone use machine learning if not to create systems they don't understand ? That's the whole point of doing it. Not having to understand complex system to understand -or even predict- them is a very good thing indeed. I don't know anything about how to mathematically analyze pixel values to read text, but I can create such a formula using machine learning. After creating the formula I know nothing more about it. So the same person can create programs to read text, transcribe audio, predict loan repayment, ...
And when it comes to the bias in the data - bias in the system thing, well, same thing goes for human judgement. Another way of putting this would be garbage in-garbage out. Humans might be able to tell you of bias in the inputs, rather than just using it, but this ability rapidly deteriorates when the dimensionality of the inputs rises. You can tell if there's something weird about combinations of 3 numbers, but you can't tell if there is something off about 150 number sequences.
- ghgfhgfhn 10y agoAs is often the case, the most insightful comment is tucked away at the bottom of the page.
- unclebucknasty 10y agoPerhaps. But the inability to verify or predict output is a real concern, especially in the nascent stages of applying the tech to an increasing number of critical situations.
- abtinf 10y agoAlong these lines, I think these classes of algorithms might have much broader applications and could possibly solve problems that we don't even have good definitions for yet. I'm particularly curious to see how the field develops new techniques for systems that start off with poor quality results but evolve with new data to produce better results. btw, I vouched for and upvoted the parent. It makes an excellent point and, frankly, I'm baffled by the downvotes/dead status.