Artificial Intelligence will obliterate these jobs by 2030

In the AI world, data is the new currency and analytics competency a crucial competitive differentiator across business lines

Cubicle workers. Shipping clerks. Loan processors.

“All gone,” Forrester vice president and principal consultant Huard Smith said in describing the impact of artificial intelligence on various professions by 2030.

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Awaiting the Advent of a Sleeping Giant in Edtech


Online learning taught by robots could be widespread by 2030. Thirty years ago, it was a big deal when schools got their first computers. Today, it’s a big deal when students get their own laptops.

According to futurist Thomas Frey, in 14 years it’ll be a big deal when students learn from robot teachers over the internet.

It’s not just because the technology will be that sophisticated, Frey says, but because the company responsible for it will be the largest of its kind.

“I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet,” Frey, the senior futurist at the DaVinci Institute think tank, tells Business Insider.

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AI trained on decades of food research is making brand-new foods




IBM’s AI scientists teamed up with McCormick & Company’s food developers to enhance food research.


You may not think that Tuscan chicken’s creamy, garlicky flavor is due for a high-tech upgrade, but advanced artificial intelligence is on the case all the same. An AI algorithm is about to analyze and improve that and other classic recipes before designing some brand-new foods as well.

And if it goes well, we can expect AI to play a bigger role in developing the foods we eat every day. Right now, some big names are working to amass the expertise of all the world’s food experts, head chefs, and flavor scientists into a single artificial intelligence algorithm that concocts new foods better and faster than any mere human.

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How We’ll Survive When Artificial Intelligence Gets Smarter Than Us


Physicist Max Tegmark has borne witness to the rise of artificial intelligence and insists that we start thinking about what it means for humanity—before machines decide for us.

The artificial intelligence revolution is here, and MIT physics professor Max Tegmark believes the implications are vaster than most of us imagine. Tegmark, cofounder and president of the Future of Life Institute, believes that as technology gives us the power to flourish or self-destruct, “We prefer the former.” In Life 3.0: Being Human in the Age of Artificial Intelligence, he lays out both utopian and dystopian visions of a world dominated by AI. His prescription for the day we cease being Earth’s most intelligent minds? Humility.

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AI adoption is limited by incurred risk, not potential benefit


It’s tempting to think that adoption of AI is limited by the technology itself. Headlines declaring the rise of robot doctors and approaching technological singularity, contrasted with humorous memes of robots falling over, make us alternately fear and doubt AI’s capabilities. In practice, however, decades-old AI technologies could unlock significant value, although many companies still have yet to adopt them. This is because adoption of AI is determined by both trust and risk. Thinking about AI adoption in this way enables us to more accurately anticipate opportunities for AI startups.

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Facebook’s A.I. system that learned to lie to get what it wants

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We’re beginning to get a glimpse of some of the built-in limits to artificial intelligence.

Humans are natural negotiators. We arrange dozens of tiny little details throughout our day to produce a desired outcome: What time a meeting should start, when you can take time off work, or how many cookies you can take from the cookie jar.

Machines typically don’t share that affinity, but new research from Facebook’s AI research lab might offer a starting point to change that. The new system learned to negotiate from looking at each side of 5,808 human conversations, setting the groundwork for bots that could schedule meetings or get you the best deal online.

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How to Upgrade Judges with Machine Learning

When should a criminal defendant be required to await trial in jail rather than at home? Software could significantly improve judges’ ability to make that call—reducing crime or the number of people stuck waiting in jail.

In a new study from the National Bureau of Economic Research, economists and computer scientists trained an algorithm to predict whether defendants were a flight risk from their rap sheet and court records using data from hundreds of thousands of cases in New York City. When tested on over a hundred thousand more cases that it hadn’t seen before, the algorithm proved better at predicting what defendants will do after release than judges.

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Study: 93% of suicidal patients detected with machine learning algorithms

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New research published in the journal Suicide and Life-Threatening Behavior shows how machine learning can help identify suicidal behavior using a person’s spoken or written words. The technology was able to pinpoint which participants in the study were suicidal, mentally ill but not suicidal, or neither in the vast majority of cases.

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How artificial intelligence will change our lives


Simon Worrall: We may not be aware of it, but machine learning is already an integral part of our daily lives, from the product choices that Amazon offers us to the surveillance of our data by the National Security Agency. Few of us understand it or the implications, however.

Hitachi can predict where and when crimes will occur by monitoring everything from the weather to Twitter


In the  2002 Steven Spielberg movie, Minority Report, Chief John Anderton (played by Tom Cruise) says, “No doubt the precogs have already seen this.” In the movie Cruise plays the head of Washington, D.C.’s experimental “Precrime” crime-prediction department. The movie is based on Philip K. Dick’s 1956 short story (which is also now a new Fox TV series).

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AI and deep machine learning are the future of everything


Machine learning plays a part in your everyday life. When you speak to your phone (via Cortana, Siri or Google Now) and it fetches information, or you type in the Google search box and it predicts what you are looking for before you finish, you are doing something that has only been made possible by machine learning.

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