“Norman is born from the fact that the data that is used to teach a machine-learning algorithm can significantly influence its behavior,” MIT explains on their website dedicated to Norman.
“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.”
“The same method can see very different things in an image, even sick things if trained on the wrong (or, the right!) data set.”
If you’re wondering how on earth it’s possible to do that, researchers trained Norman using a particularly gruesome Reddit group that they have not named.
“Norman suffered from extended exposure to the darkest corners of Reddit, and represents a case study on the dangers of Artificial Intelligence gone wrong when biased data is used in machine learning algorithms.”
It goes on to say that, “Norman is an AI that is trained to perform image captioning; a popular deep learning method of generating a textual description of an image.”
“We trained Norman on image captions from an infamous subreddit (the name is redacted due to its graphic content) that is dedicated to document and observe the disturbing reality of death.”
“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.”
For example, one of the Rorschach inkblots might be interpreted by a normal AI that sees a couple of people standing next to each other, but Norman sees it as man jumps from floor window.
MIT; pictured above is an example of what Norman sees vs. a normal AI
How creepy is that?
You can learn more about Norman on MIT’s website here.
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