TED SUMMARY: The Jobs We'll Lose to Machines And The Ones WE Won't
Anthony Goldbloom works in Kaggle, a company which operates on the cutting edge of machine learning and it brings together hundreds of thousands of experts to solve important problems for industry and academia. This gives them, especially for him a new perspective on what machines can and can't do, then finds out what jobs they might automate or threaten. He started to reveal that machine learning isn't just for simple tasks like assessing credit risk and sorting mail anymore, as like in early 90s. Today, it's capable of far more complex applications, like grading high-school essays, and the most challenging task is to diagnose diseases, such as diabetic retinopathy.
The data has clearly shown that machines are going to give better work performance at all the tasks like these. A teacher might read 10.000 essays over a 40 years career, an Ophthalmologist see 50.000 eyes for a whole life, while a machine can read million of essays and see million of eyes only within minutes. Anthony convinced the audiences that we have no change to competing against machines, however there are things that a machine can't do. One of them is tackling a novel situations. It doesn't capable to handle thing they haven't seen many times before. Finally, he stated that whatever we decide to do, let everyday bring a plenty of challenges, if they do, then we will stay ahead of the machines.
Anthony Goldbloom works in Kaggle, a company which operates on the cutting edge of machine learning and it brings together hundreds of thousands of experts to solve important problems for industry and academia. This gives them, especially for him a new perspective on what machines can and can't do, then finds out what jobs they might automate or threaten. He started to reveal that machine learning isn't just for simple tasks like assessing credit risk and sorting mail anymore, as like in early 90s. Today, it's capable of far more complex applications, like grading high-school essays, and the most challenging task is to diagnose diseases, such as diabetic retinopathy.
The data has clearly shown that machines are going to give better work performance at all the tasks like these. A teacher might read 10.000 essays over a 40 years career, an Ophthalmologist see 50.000 eyes for a whole life, while a machine can read million of essays and see million of eyes only within minutes. Anthony convinced the audiences that we have no change to competing against machines, however there are things that a machine can't do. One of them is tackling a novel situations. It doesn't capable to handle thing they haven't seen many times before. Finally, he stated that whatever we decide to do, let everyday bring a plenty of challenges, if they do, then we will stay ahead of the machines.
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