Andrew Ng

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Andrew Ng’s predictions about Artificial Intelligence carry more weight with me than the projections of many of his peers because he never seems driven by irrational exuberance. In fact, he often urges caution when talk about the imminent arrival of driverless cars and other landscape-changing tools becomes overheated. 

So, when Baidu’s Chief Scientist asserts AI will soon deliver to us a brave new world, one in which, for instance, speech recognition is all but perfected, it’s probably wise to take notice. Computer conversation that’s wholly convincing should give us pause, however. Any technology that becomes seamless should be met as much by concern as enthusiasm.

An excerpt from a smart Wall Street Journal interview Scott Austin conducted with Ng and Neil Jacobstein of Singularity University:

Andrew Ng:

In addition to strengthening our core business, AI is creating a lot of new opportunities. Just as about 100 years ago electrification changed every single major industry, I think we’re in the phase where AI will change pretty much every major industry.

So part of my work at Baidu is to systematically explore new verticals. We have built up an autonomous driving unit. We have a conversational computer, similar to Amazon’s Alexa and Google Home. And we’re systematically pursuing new industries where we think we can build an AI team to create and capture value.


Let’s talk about speech recognition. I believe someone in your program has said that the hope is to get to the point where it is 99% accurate. Where are you on that?

Andrew Ng:

A couple of years ago, we started betting heavily on speech recognition because we felt that it was on the cusp of being so accurate that you would use it all the time. And the difference between speech recognition that is 95% accurate, which is where we were several years ago, versus 99% accuracy isn’t just an incremental improvement.

It’s the difference between you barely using it, like a couple of years ago, versus you using it all the time and not even thinking about it. At Baidu we have passed the knee of that adoption curve. Over the past year, we’ve seen about 100% year-to-year growth in the daily active use of speech recognition across our assets, and we project that this will continue to grow.

In a few years everyone will be using speech recognition. It will feel natural. You’ll soon forget what it was like before you could talk to computers.•

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The first driverless car fatality has apparently occurred, which is a sad situation that’s received a great deal of press. Certainly autonomous risks should be investigated and discussed, but since that crash there’ve been numerous road deaths in America in standard vehicles that have received scant attention. Those are the kind of accidents we’re used to and seem acceptable because human hands were involved. No one should think driverless cars won’t malfunction, especially in their early days–they’ll hopefully greatly reduce deaths, not eliminate them.

When this technology arrives, it will likely be great for traffic safety but a huge blow to American Labor as drivers of trucks, taxis and delivery vehicles will be made redundant. What will happen to them and all the businesses they support while on the road? In a recent Wall Street Journal article, Baidu’s Andrew Ng suggested a new New Deal might be the answer. An excerpt:

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.•


As a follow-up to the post which quoted former Google and current Baidu AI research scientist Andrew Ng, here’s a fuller explanation of his thoughts about the existential threat of intelligent machines, from a Backchannel interview by Caleb Garling:

Caleb Garling:

Do you see AI as a potential threat?

Andrew Ng:

I’m optimistic about the potential of AI to make lives better for hundreds of millions of people. I wouldn’t work on it if I didn’t fundamentally believe that to be true. Imagine if we can just talk to our computers and have it understand “please schedule a meeting with Bob for next week.” Or if each child could have a personalized tutor. Or if self-driving cars could save all of us hours of driving.

I think the fears about “evil killer robots” are overblown. There’s a big difference between intelligence and sentience. Our software is becoming more intelligent, but that does not imply it is about to become sentient.

The biggest problem that technology has posed for centuries is the challenge to labor. For example, there are 3.5 million truck drivers in the US, whose jobs may be affected if we ever manage to develop self-driving cars. I think we need government and business leaders to have a serious conversation about that, and think the hype about “evil killer robots” is an unnecessary distraction.•

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I agree with two very smart people working in Artificial Intelligence, Andrew Ng and Hod Lipson, when I say that I’m not worried about any near-term scenario in which Strong AI extincts Homo Sapiens the way we did Neanderthals. It’s not that it’s theoretically impossible in the long run, but we would likely first need to know precisely how the human brain operates, to understand the very nature of consciousness, to give “life” to our eliminators. While lesser AI than that could certainly be dangerous on a large scale, I don’t think it’s moving us back down the food chain today or tomorrow.

But like Ng and Lipson, the explosion of Weak AI throughout society in the form of autonomous machines is very concerning to me. It’s an incredible victory of ingenuity that can become a huge loss if we aren’t able to politically reconcile free-market societies with highly autonomous ones. An excerpt from Robert Hof at Forbes’ horribly designed site:

“Historically technology has created challenges for labor,” [Ng] noted. But while previous technological revolutions also eliminating many types of jobs and created some displacement, the shift happened slowly enough to provide new opportunities to successive generations of workers. “The U.S. took 200 years to get from 98% to 2% farming employment,” he said. “Over that span of 200 years we could retrain the descendants of farmers.”

But he says the rapid pace of technological change today has changed everything. “With this technology today, that transformation might happen much faster,” he said. Self-driving cars, he suggested could quickly put 5 million truck drivers out of work.

Retraining is a solution often suggested by the technology optimists. But Ng, who knows a little about education thanks to his cofounding of Coursera, doesn’t believe retraining can be done quickly enough. “What our educational system has never done is train many people who are alive today. Things like Coursera are our best shot, but I don’t think they’re sufficient. People in the government and academia should have serious discussions about this.

His concerns were echoed by Hod Lipson, director of Cornell University’s Creative Machines Lab. “If AI is going to threaten humanity, it’s going to be through the fact that it does almost everything better than almost anyone,” he said.•

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In a Wall Street Journal interview conducted by Gillian Wong, Andrew Ng, formerly of Google and now the head of AI research for Baidu, tries to cool down the hype of two hot tech sectors, driverless cars and deep learning. An excerpt:


What about the self-driving car project? We know Baidu has partnered with BMW on that.

Andrew Ng:

That’s another research exploration. Building self-driving cars is really hard. I think making it achieve high levels of safety is challenging. It’s a relatively early project. Building something that is safe enough to drive hundreds of thousands of miles, including roads that you haven’t seen before, roads that you don’t have a map of, roads where someone might have started to do construction just 10 minutes ago, that is hard. …


Who’s at the forefront of deep learning?

Andrew Ng:

There are a lot of deep-learning startups. Unfortunately, deep learning is so hot today that there are startups that call themselves deep learning using a somewhat generous interpretation. It’s creating tons of value for users and for companies, but there’s also a lot of hype. We tend to say deep learning is loosely a simulation of the brain. That sound bite is so easy for all of us to use that it sometimes causes people to over-extrapolate to what deep learning is. The reality is it’s really very different than the brain. We barely (even) know what the human brain does.•

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