So, what will your second career be? There's no playing coy with it anymore: intelligent machines are coming for our jobs, but rather than let this be a point of fear and the start of even greater class division, Vice President of Booz Allen Hamilton Angela Zutavern hopes that human leaders, in politics and in corporations, with be proactive in the face of job automation by re-training displaced workers with new skills that will be highly valued in the AI landscape. She's not just talking about manual laborers, either; job automation will not discriminate on the color of your collar, and doctors and lawyers will be hit just like truck drivers and rote-task professionals. The upside is that machine intelligence will spawn new industries we haven’t even thought of yet, so while it's true you may lose your job, you'll already have teed up a new one—provided we develop appropriate policy sooner rather than later, warns Zutavern. If we do this right, machine learning won’t replace humans, it will augment us, leaving our talents to be put to better use in creative and reasoning tasks, which is where we are yet to be beaten. Angela Zutavern and Josh Sullivan are the authors of The Mathematical Corporation: Where Machine Intelligence and Human Ingenuity Achieve the Impossible.
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So machine intelligence includes two main areas. One is high-performance computing; all the chips you need to do the complex math required, and then artificial intelligence.
Within artificial intelligence all the breakthroughs are happening in the area of machine learning, and machine learning includes the ability for computers to think, learn and act on their own. There are a lot of great examples throughout business, government, and the nonprofit world as well. For example, in the U.S. government, machine learning is completely changing how census workers visit houses to collect the census data. These enumerators in the past would just use their own judgment on what routes to take and when to visit houses and, of course, they often found people not home. In the upcoming 2020 decennial census, machine learning will actually give them the best routes and the best predicted times to find when people are going to be home.
When people ask me if machine intelligence will affect them I turn the question back around and say, “Could you imagine your life or your job without the Internet?” And most people will say no. And I say, that's how machine intelligence will become for us. It's already involved in our personal lives whether it's Amazon recommendation engines or Netflix recommendations, but it will continue to spread not only in our personal and entertainment lives but also in our day-to-day work lives as well.
One example is IT departments in corporations. Many companies spend the majority of their IT budget on IT operations, operations and maintenance, and it's a huge budget line item. Machine intelligence is now able to perform most or all of those mundane routine activities. That frees up an entire skilled workforce to focus on creativity and innovation beyond the jobs that they're doing today.
So, machine intelligence is not about completely removing the person from the equation, it's about machines and humans working together. We never recommend that you completely abandon your judgment as a leader. Many times machine learning is wrong and as leaders we need to recognize that and know when to ask questions and how to adapt. So judgment is still absolutely critical in this equation.
An interesting example is automated trucking company Otto. It was formed by Google engineers and within ten months was bought by Uber for $680 million.
Now what would make a company worth $680 million in ten months? Well, Otto developed a cab-top device that sells for $30,000, and can fully automate any 18-wheeler truck built after 2013. In fact they've already made their first delivery using a self-driving truck: it was 50,000 cans of Budweiser beer, last year.
Right now the truck can't handle every situation, it's really great on the highways, but it has problems in bad weather and on city streets, so for now the drivers continue to ride in the cab, but when they're in on the highway the driver is free to conduct whatever activities they choose—and I love the story of a driver doing yoga while going down the highway—and then the driver takes over in difficult situations.
Read more at BigThink.com:
Follow Big Think here:
YouTube:
Facebook:
Twitter:
So machine intelligence includes two main areas. One is high-performance computing; all the chips you need to do the complex math required, and then artificial intelligence.
Within artificial intelligence all the breakthroughs are happening in the area of machine learning, and machine learning includes the ability for computers to think, learn and act on their own. There are a lot of great examples throughout business, government, and the nonprofit world as well. For example, in the U.S. government, machine learning is completely changing how census workers visit houses to collect the census data. These enumerators in the past would just use their own judgment on what routes to take and when to visit houses and, of course, they often found people not home. In the upcoming 2020 decennial census, machine learning will actually give them the best routes and the best predicted times to find when people are going to be home.
When people ask me if machine intelligence will affect them I turn the question back around and say, “Could you imagine your life or your job without the Internet?” And most people will say no. And I say, that's how machine intelligence will become for us. It's already involved in our personal lives whether it's Amazon recommendation engines or Netflix recommendations, but it will continue to spread not only in our personal and entertainment lives but also in our day-to-day work lives as well.
One example is IT departments in corporations. Many companies spend the majority of their IT budget on IT operations, operations and maintenance, and it's a huge budget line item. Machine intelligence is now able to perform most or all of those mundane routine activities. That frees up an entire skilled workforce to focus on creativity and innovation beyond the jobs that they're doing today.
So, machine intelligence is not about completely removing the person from the equation, it's about machines and humans working together. We never recommend that you completely abandon your judgment as a leader. Many times machine learning is wrong and as leaders we need to recognize that and know when to ask questions and how to adapt. So judgment is still absolutely critical in this equation.
An interesting example is automated trucking company Otto. It was formed by Google engineers and within ten months was bought by Uber for $680 million.
Now what would make a company worth $680 million in ten months? Well, Otto developed a cab-top device that sells for $30,000, and can fully automate any 18-wheeler truck built after 2013. In fact they've already made their first delivery using a self-driving truck: it was 50,000 cans of Budweiser beer, last year.
Right now the truck can't handle every situation, it's really great on the highways, but it has problems in bad weather and on city streets, so for now the drivers continue to ride in the cab, but when they're in on the highway the driver is free to conduct whatever activities they choose—and I love the story of a driver doing yoga while going down the highway—and then the driver takes over in difficult situations.
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