How to make a racist AI without really trying

#artificialintelligence 

Recognizing whether people are expressing positive or negative opinions about things has obvious business applications. It's simplistic, sometimes too simplistic, but it's one of the easiest ways to get measurable results from NLP. In a few steps, you can put text in one end and get positive and negative scores out the other, and you never have to figure out what you should do with a parse tree or a graph of entities or any difficult representation like that. This model is not the point of that paper, so don't take this as an attack on their results; it was there as an example of a well-known way to use word vectors.