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by bane 4157 days ago
The problem with AI systems has almost always been that they tend to be both right and wrong in ways that humans would never be.

Watson gives high confidence to it being a color photo of a human (which is a Person, and an Animal). Which is right. But the only part that a human would ever really care about is that there's another human in the picture.

It gets things wrong with a reasonable confidence for Dog, Placental_Mammal and Long_Jump...importantly, these are wrong in ways that humans would never get wrong.

Just as important are the omissions. A human would probably describe this as a picture of a girl or young woman, laughing or smiling, with curly brown hair wearing a scarf -- and maybe some other incidental information.

Of that description, Watson only got the superclass of one part correct (Human, Person) and didn't provide any of the other parts.

AI fundamentally "thinks" differently than a human, and that makes it hard for humans to use AI as a cognitive enhancement tool in the same way humans use calculators, books, writing, etc. We don't trust what an AI is doing or the answers it provides because for the information it provides, AIs tend to provide right-and-irrelevant, weirdly wrong, or omits obvious and necessary information that a human might use for informational purposes.

If humans ever encounter aliens, it's likely that their mode of thinking will be just as different. So bridging that gap, and figuring out how to make AI like this useful could be a useful endeavor.

1 comments

One thing a machine learning system can do that any one human cannot do is ingest lots of data. For example, for some tasks in which I have tried to compare human vs machine speech recognition performance the machine actually does better because the machine may - for example - know a singer's name that an individual human may not recognize.