Recognising objects in pictures is something that, in principle, a machine could do better than humans, because there is ground truth.
I think it's not possible in principle for a machine to do better than humans at recognising human emotions, because a human can't exactly be wrong at this. (Other than edge cases such as not knowing the right name for an emotion, perhaps.)
But suppose a sample of 1000 humans answered a survey on emotional content of a song and a machine was able to predict the distribution within some tolerance. In a sense, this would be superhuman performance, but even if we don't like that interpretation, it would still be very good performance. And it is possible in principle. So the argument that humans sometimes disagree doesn't prevent a machine doing well on the task.
I think it's not possible in principle for a machine to do better than humans at recognising human emotions, because a human can't exactly be wrong at this. (Other than edge cases such as not knowing the right name for an emotion, perhaps.)
But suppose a sample of 1000 humans answered a survey on emotional content of a song and a machine was able to predict the distribution within some tolerance. In a sense, this would be superhuman performance, but even if we don't like that interpretation, it would still be very good performance. And it is possible in principle. So the argument that humans sometimes disagree doesn't prevent a machine doing well on the task.