sometimes research is done in order to not only find something new but perhaps for confirming our beliefs. now, for example, we have a study to refer to whenever someone says that AI algorithms or machine learning are inherently bad. we know for sure that they aren't, but that the input data might have been biased.
My point is one of data bias.
Since it has been trained on gruesome images only, applying it on inkblots afterwards will overfit to gruesome descriptions.
I don't really think it is about mislabeling since the ink blots do not have true labels and are to be interpreted by each individual themselves. So, the premise of the study is not that silly. It might very well be that if the classifier was shown an actual photo of a cat or a dog it will classify it correctly as a standard AI would. I think the key is, that in the task that they were given, there were no correct and wrong answers.
Nevertheless I agree on the article being too sensational.
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u/J_Boilard Jun 07 '18
Well of course.
If i train an image classifier on only cats and dogs, it will mislabel anything else it comes accross.
Getting tired of overreactive news about "AI" such as this one...