TED Summary: The jobs we'll lose to machines and the ones we won't by Anthony Goldbloom
According to Anthony Goldbloom, in the next decades, most of proffessions such as lawyer and doctor will see a significant change as as result of machinery. In line to that, recently, researchers from Oxford University argues that nearly half of human's jobs are n the risk being take over by machine in the future.
Anthony describes machine learning as a most influential branch of man-made intelligence, it enables to learn from data and imitate some of people's abilities. Machine learning first used in early 1990 with fairly simple jobs , for example, to evaluate credit loan's risk and to sort mails using postcode. Over the past few years, machine learning was capable to handle a more complicated task such to give score on high school essays and to determine eye disease called retinopathy. At this point, it is clear that there is no opportunity for human to compete against machine when it comes to do a large number of tasks.
However, machine has limitation that they can only perform work than they had learned before in a large number, while people are able to cope with unfamiliar conditions. Business strategies, marketing campaigns and other creativities tasks are some of the people's capability that is likely hard to compete by machine.
According to Anthony Goldbloom, in the next decades, most of proffessions such as lawyer and doctor will see a significant change as as result of machinery. In line to that, recently, researchers from Oxford University argues that nearly half of human's jobs are n the risk being take over by machine in the future.
Anthony describes machine learning as a most influential branch of man-made intelligence, it enables to learn from data and imitate some of people's abilities. Machine learning first used in early 1990 with fairly simple jobs , for example, to evaluate credit loan's risk and to sort mails using postcode. Over the past few years, machine learning was capable to handle a more complicated task such to give score on high school essays and to determine eye disease called retinopathy. At this point, it is clear that there is no opportunity for human to compete against machine when it comes to do a large number of tasks.
However, machine has limitation that they can only perform work than they had learned before in a large number, while people are able to cope with unfamiliar conditions. Business strategies, marketing campaigns and other creativities tasks are some of the people's capability that is likely hard to compete by machine.