Not for the first time in its history, artificial intelligence is rising on a tide of hype. Improvements to the technology have produced some apparently impressive advances in fields such as voice and image recognition, predictive pattern analysis and autonomous robotics. The problem is that people are extrapolating many unrealistic expectations from these initial successes, without recognizing the many constraints surrounding their achievements.
Machine intelligence is still pretty dumb, most of the time. It's far too early for the human race to throw in the towel.

People are misled by artificial intelligence because of a phenomenon known as the Eliza effect, named after a 1966 computer program that responded to people's typed statements in the manner of a psychotherapist. The computer was executing some very simple programming logic. But the people interacting with it ascribed emotional intelligence and empathy to its replies.

The same phenomenon happens today in our reactions to the apparent successes of machine learning and AI. We overestimate its achievements and underestimate our own performance because we rarely stop to think how much we already know. All of the context we bring to interpreting any situation is something we take for granted.