The there are differences in human learning and knowledge and machine learning, one being the kind of errors machines makes compared to humans. A human is unlik

The there are differences in human learning and knowledge and machine learning, one being the kind of errors machines makes compared to humans. A human is unlikely to confuse the side of a truck with the sky (tesla), or the image of an item with the actually item. Humans in turn get effected by stress, metabolism and other biological factors. For an AI to actually predict which employees are going to benefit the company, it need to understand both how the company has evolved over the data period, how it will likely continue to grow, and that some employees that have successful careers are not necessary the people that contribute to the success of the company. An AI might think nepotism is a great indicator for a highly retained and employable employee, but a human would recognize it for what it is but may accept it as an acceptable level of corruption. It would be the same conclusion (ie, hire the person), but for two very different reasons.