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What’s Next for Artificial Intelligence



Yann LeCun, director of artificial-intelligence research at Facebook, on a curriculum for software
The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple—recognizing an object in a photo, driving a car—are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a $30 gadget can beat us at a board game, but it can’t do—or learn to do—anything else.
This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats. Machine learning is the basis on which all large Internet companies are built, enabling them to rank responses to a search query, give suggestions and select the most relevant content for a given user.
Deep learning, modeled on the human brain, is infinitely more complex. Unlike machine learning, deep learning can teach machines to ignore all but the important characteristics of a sound or image—a hierarchical view of the world that accounts for infinite variety. It’s deep learning that opened the door to driverless cars, speech-recognition engines and medical-analysis systems that are sometimes better than expert radiologists at identifying tumors.
Despite these astonishing advances, we are a long way from machines that are as intelligent as humans—or even rats. So far, we’ve seen only 5% of what AI can do.
Andrew Ng, chief scientist at Chinese Internet giant Baidu, on how AI will impact what we do for a living
Truck driving is one of the most common occupations in America today: Millions of men and women make their living moving freight from coast to coast. Very soon, however, all those jobs could disappear. Autonomous vehicles will cover those same routes in a faster, safer and more efficient manner. What company, faced with that choice, would choose expensive, error-prone human drivers?
There’s a historical precedent for this kind of labor upheaval. Before the Industrial Revolution, 90% of Americans worked on farms. The rise of steam power and manufacturing left many out of work, but also created new jobs—and entirely new fields that no one at the time could have imagined. This sea change took place over the course of two centuries; America had time to adjust. Farmers tilled their fields until retirement, while their children went off to school and became electricians, factory foremen, real-estate agents and food chemists.
‘We’re about to face labor displacement of a magnitude we haven’t seen since the 1930s.’
Truck drivers won’t be so lucky. Their jobs, along with millions of others, could soon be obsolete. The age of intelligent machines will see huge numbers of individuals unable to work, unable to earn, unable to pay taxes. Those workers will need to be retrained—or risk being left out in the cold. We could face labor displacement of a magnitude we haven’t seen since the 1930s.
In 1933, Franklin Roosevelt’s New Deal provided relief for massive unemployment and helped kick-start the economy. More important, it helped us transition from an agrarian society to an industrial one. Programs like the Public Works Administration improved our transportation infrastructure by hiring the unemployed to build bridges and new highways. These improvements paved the way for broad adoption of what was then exciting new technology: the car.
We need to update the New Deal for the 21st century and establish a trainee program for the new jobs artificial intelligence will create. We need to retrain truck drivers and office assistants to create data analysts, trip optimizers and other professionals we don’t yet know we need. It would have been impossible for an antebellum farmer to imagine his son becoming an electrician, and it’s impossible to say what new jobs AI will create. But it’s clear that drastic measures are necessary if we want to transition from an industrial society to an age of intelligent machines.
How intelligent machines could resemble their makers
The next step in achieving human-level ai is creating intelligent—but not autonomous—machines. The AI system in your car will get you safely home, but won’t choose another destination once you’ve gone inside. From there, we’ll add basic drives, along with emotions and moral values. If we create machines that learn as well as our brains do, it’s easy to imagine them inheriting human-like qualities—and flaws. But a “Terminator”-style scenario is, in my view, immensely improbable. It would require a discrete, malevolent entity to specifically hard-wire malicious intent into intelligent machines, and no organization, let alone a single group or a person, will achieve human-level AI alone. Building intelligent machines is one of
The greatest scientific challenges of our times, and it will require the sharing of ideas across countries, companies, labs and academia. Progress in AI is likely to be gradual—and open. —Yann LeCun

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