| The term "AI" is over-hyped. What we have now is advanced pattern recognition, not intelligence. Pattern recognition will learn any biases in your training data. An intelligent enough* being does much more than pattern recognition -- intelligent beings have concepts of ethics, social responsibility, value systems, dreams, ideals, and is able to know what to look for and what to ignore in the process of learning. A dumb pattern recognition algorithm aims to maximize its correctness. Gradient descent does exactly that. It wants to be correct as much of the time as possible. An intelligent enough being, on the other hand, has at least an idea of de-prioritizing mathematical correctness and putting ethics first. Deep learning in its current state is emphatically NOT what I would call "intelligence" in that respect. Google had a big media blooper when their algorithm mistakenly recognized a black person as a gorilla [0]. The fundamental problem here is that state-of-the-art machine learning is not intelligent enough. It sees dark-colored pixels with a face and goes "oh, gorilla". Nothing else. The very fact that people were offended by that is a sign that people are truly intelligent. The fact that the algorithm didn't even know it was offending people is a sign that the algorithm is stupid. Emotions, the ability to be offended, and the ability to understand what offends others, are all products of true intelligence. If you used today's state-of-the-art machine learning, fed it real data from today's world, and asked it to classify them into [good people, criminals, terrorists], you would result in an algorithm that labels all black people as criminals and all people with black hair and beards as terrorists. The algorithm might even be the most mathematically correct model. The very fact that you (I sincerely hope) cringe at the above is a sign that YOU are intelligent and this algorithm is stupid. *People are overall intelligent, and some people behave more intelligently than others. There are members of society that do unintelligent things, like stereotyping, over-generalization, and prejudice, and others who don't. [0] https://www.theverge.com/2018/1/12/16882408/google-racist-go... |
For the black man = gorilla problem, an untaught human, a small child for instance, can easily make the same mistake. Especially if he has seen few black people. And well educated adults can also make the mistake initially, even if they hate to admit it.
However, in the last case, a second pattern recognition happen, one that matches the result of the image classifier with social rules. And it turns out that mixing black men and gorillas is a clear anti-pattern and anything that isn't certain is incorrect.
Unlike us, computer image classifiers typically aren't taught social rules, so like a small child, they will tell things without filter. It will probably change in the future for public facing AIs.
Not stereotyping is not a mark of intelligence, it is a mark of a certain type of education. And I don't see why it couldn't be done with the usual machine learning techniques.