The jobs we'll lose to machines -- and the ones we won't | Anthony Goldbloom

Summary

This video discusses the impact of machine learning on the future of work, exploring how technology is poised to automate many jobs, particularly those involving frequent, high-volume tasks like grading essays or diagnosing diseases. However, it emphasizes that machines still struggle with novel situations, where humans excel. The speaker stresses that jobs requiring creativity and complex problem-solving, such as marketing or business strategy, will continue to rely on human skills. The key takeaway is that staying ahead of machines involves embracing new challenges that push human creativity and adaptability.

Takeaways

• 😀 Yahli, a nine-month-old baby, represents the next generation who will experience major changes in the job market.
• 😀 Researchers predict that by the time Yahli enters the workforce, nearly 50% of jobs will be at high risk of being automated.
• 😀 Machine learning, a branch of artificial intelligence, is responsible for automating many jobs by mimicking human tasks.
• 😀 Kaggle, the company mentioned, is a leader in the machine learning field, connecting experts to solve complex problems.
• 😀 Machine learning's history started with simple tasks in the '90s, like assessing credit risk and reading zip codes.
• 😀 In recent years, machine learning has achieved remarkable advancements, such as grading high-school essays and diagnosing medical conditions like diabetic retinopathy.
• 😀 Machines can outperform humans on repetitive, high-volume tasks, such as grading essays or diagnosing diseases, but struggle with new and novel situations.
• 😀 Humans excel at solving problems that machines can't, like making creative connections or tackling unique challenges.
• 😀 A key limitation of machine learning is its reliance on vast amounts of past data, while humans can learn and adapt without it.
• 😀 Jobs involving frequent tasks (like accounting or legal work) will be automated, but jobs requiring creativity and novel thinking (like marketing or business strategy) will still need humans.
• 😀 Yahli's future career will depend on her ability to embrace new challenges, which will keep her ahead of machines.

Q & A

What is the main message of the script?

The main message is that machines, particularly through machine learning, are automating many jobs that were once done by humans, especially tasks involving high-volume, repetitive work. However, humans still excel in handling novel situations and tasks requiring creativity.

How are machine learning technologies impacting the job market?

Machine learning technologies are automating a large number of jobs, particularly those that involve frequent, high-volume tasks. Jobs in fields like grading essays, diagnosing diseases, and analyzing contracts are being affected. However, jobs requiring creativity and tackling novel problems remain safe.

What is machine learning, and why is it so important in automation?

Machine learning is a branch of artificial intelligence that enables machines to learn from data and perform tasks that typically require human intelligence. It is important in automation because it allows machines to take over repetitive and high-volume tasks, thus disrupting many industries.

Can you provide examples of how machine learning has been applied in different fields?

Machine learning has been applied in fields like education, where algorithms are now able to grade high-school essays, and healthcare, where algorithms can diagnose eye diseases like diabetic retinopathy with accuracy comparable to human professionals.

Why are humans still needed in certain professions despite the advancement of machine learning?

Humans are needed in professions that require creativity, critical thinking, and the ability to solve novel problems. Machines struggle with tasks that involve new or unpredictable situations, making human involvement essential in areas like business strategy and marketing.

How has Kaggle contributed to the advancement of machine learning?

Kaggle has been at the forefront of machine learning by bringing together experts to solve complex problems. They have hosted challenges that have pushed the boundaries of machine learning, such as grading essays and diagnosing diseases from medical images.

What is the significance of the Oxford University study mentioned in the script?

The Oxford University study concluded that nearly 50% of jobs are at high risk of being automated due to advancements in technology, particularly machine learning. This highlights the potential impact of automation on the workforce in the future.

How are the roles of accountants and lawyers expected to change due to automation?

While automation may reduce the need for accountants and lawyers in routine tasks like audits or reading legal contracts, their roles will still be essential for more complex tasks such as tax structuring and litigation. Machines will shrink their numbers and make such jobs harder to come by.

What does the script suggest about the future of work for young people like Yahli?

The script encourages young people like Yahli to embrace new challenges and tackle novel problems, as this will help them stay ahead of machines in the future. It suggests that creativity and the ability to solve new problems will be key to thriving in the future job market.

What key difference between machines and humans is emphasized in the script?

The key difference highlighted is that machines excel at tasks involving large volumes of data and repetition, but they struggle with novel situations. Humans, on the other hand, can connect disparate ideas and solve problems that they haven't encountered before, which gives them an edge over machines in certain jobs.