Norman is an AI system trained to perform image captioning, in which deep learning algorithms are used to generate a text description of an image. The researchers note that Norman is a case study aiming to see how AI could turn bad if its machine learning algorithms feed on this kind of data. How they created this AI was by feeding it using disturbing image captions from Reddit from a subreddit "dedicated to document and observe the disturbing reality of death".
After the gruesome exposure, Norman was subjected to the Rorschach inkblot test - a psychological exam from 1921 which tests what subjects see when they look at nondescript inkblots.
Due to ethical concerns, MIT only introduced bias in relation to image captions from the subreddit which are later matched with randomly generated inkblots. "Then, we compared Norman's responses with a standard image captioning neural network (trained on MSCOCO dataset) on Rorschach inkblots; a test that is used to detect underlying thought disorders". As Newsweekreports, Norman then responded differently to the testing than the more standard AI, seeing gory auto deaths rather than every day appliances or things like umbrellas.
In one inkblot, the standard AI might see "a closeup of a vase with flowers", while Norman sees "a man is shot dead". " Another test saw the regular bot report "a black and white photo of a small bird", when Norman said it shows the moment a "man gets pulled into dough machine". Where the standard AI sees "a close up of a wedding cake on a table", Norman, our malicious AI robokiller sees "a man killed by speeding driver". "So when people talk about AI algorithms being biased and unfair, the culprit is often not the algorithm itself, but the biased data that was fed to it".
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