It is, except that people are discovering that the programs faithfully learn from their training material, even including traits and biases present that are not

It is, except that people are discovering that the programs faithfully learn from their training material, even including traits and biases present that are not consciously included by the person that selected the training data. It seems a lot of people don't realize that there's likely a large disconnect between what people think they're training an AI to do and what they're actually training it to do. If they're lucky, the two are close enough that the learning program will be useful for what was hoped, and if they're unlucky it will look like it's useful and correct but will include behavior learned from the training data that was not predicted and which taints the result. IE, if you train an AI with what you think is unbiased data but which includes a subtle bias, then the results you get from it may be biased... and the bias may be so subtle it's undetectable except by another AI, which is a problem if you assume that since your training data was unbiased, your AI must be unbiased. Putting it another way... garbage in, garbage out.