4 fallacies of artificial intelligence
The history of artificial intelligence has been marked with periods of hype and excitement followed by long winters of disappointment. Why is it that, despite remarkable advances, AI fails to live up to its expectations again and again?
In her latest paper, computer scientist Melanie Mitchell lays out four common fallacies in AI. These are misconceptions that deceive not only the public and the media but also experts in the field.
These fallacies give a false sense of confidence about how close we are to achieving artificial general intelligence, AI systems that can match the cognitive and general problem-solving skills of humans.
“Understanding these fallacies and their subtle influences can point to directions for creating more robust, trustworthy, and perhaps actually intelligent AI systems,” Mitchell writes.
Melanie Mitchel has made some great contributions to the AI community. Her book Artificial Intelligence: A Guide For Thinking Humans provides a thorough and very accessible intro to the history and the current state of artificial intelligence. And last year, she wrote an essay in AI Magazine that explores AI’s struggle to reach understanding and meaning.