Category: Employment

Artificial IntelligenceEmploymentExistential Risk

Why Elon Musk Is Right … Again

Less than a week after Elon Musk warned the National Association of Governors about the risks of artificial intelligence, he got in a very public dust-up with Mark Zuckerberg, who thought Musk was being “pretty irresponsible.” Musk retorted that Zuckerberg’s understanding of the topic was “limited.”

This issue pops up with such regularity as to bring joy to the copyright holders of Terminator images. But neither of these men is a dummy, and they can’t both be right… right?

We need to unpack this a little carefully. There is a short term, and a long term. In the short term (the next 10-20 years), while there will be many jobs lost to automation, there will be tremendous benefits wrought by AI, specifically Artificial Narrow Intelligence, or ANI. That’s the kind of AI that’s ubiquitous now; each instance of it solves some specific problem very well, often better than humans, but that’s all it does. This is of course true on the face of it of computers ever since they were invented, or there would have been no point; from the beginning they were better at taking square roots than a person with pencil and paper.

But now those skills include tasks like facial recognition and driving a car, two abilities that we cannot even explain adequately how we do them ourselves, but never mind; computers can be trained by showing them good and bad examples and they just figure it out. They can recognize faces better than humans now, and the day when they are better drivers than humans is not far off.

In the short term, then, the effects are unemployment on an unprecedented scale as 3.5 million people who drive vehicles for a living in the USA alone are expected to be laid off. The effects extend to financial analysts making upwards of $400k/year, whose jobs can now be largely automated. Two studies show that about 47% of work functions are expected to be automated in the short term. (That’s widely misreported as 47% of jobs being eliminated with the rest left unmolested; actually, most jobs would be affected to varying degrees, averaging to 47%.) Mark Cuban agrees.

But, there will be such a cornucopia bestowed upon us by the ANIs that make this happen that we should not impede this progress, say their proponents.  Cures for diseases, dirty risky jobs given to machines, and wealth created in astronomical quantities, sufficient to take care of all those laid-off truckers.

That is true, but it requires that someone connect the wealth generated by the ANIs with the laid-off workers, and we’ve not been good at that historically. But let’s say we figure it out, the political climate swings towards Universal Basic Income, and in the short term, everything comes up roses. Zuckerberg: 1, Musk: 0, right?

Remember that the short term extends about 20 years. After that, we enter the era where AI will grow beyond ANI into AGI: Artificial General Intelligence. That means human-level problem solving abilities capable of being applied to any problem. Except that anything that gets there will have done so by having the ability to improve its own learning speed, and there is no reason for it to stop when it gets on a par with humans. It will go on to exceed our abilities by orders of magnitude, and will be connected to the world’s infrastructure in ways that make wreaking havoc trivially easy. It takes only a bug—not even consciousness, not even malevolence—for something that powerful to take us back to the Stone Age. Fortunately, history shows that Version 1.0 of all significant software systems is bug-free.

Oops.

Elon Musk and I don’t want that to be on the cover of the last issue of Time magazine ever published. Zuckerberg is more of a developer and I have found that it is hard for developers to see the existential risks here, probably because they developed the code, they know every line of it, and they know that nowhere in it resides the lines

if ( threatened ) {
    wipe_out_civilization();
}

Of course, they understand about emergent behavior; but when they’ve spent so much time so close to software that they know intimately, it is easy to pooh-pooh assertions that it could rise up against us as uninformed gullibility. Well, I’m not uninformed about software development either. And yet I believe that it could be soon that we are developing systems that does display drastic emergent behavior, and that by then it will be too late to take appropriate action.

Whether this cascade of crisis happens in 20 years, 15, or 30, we should start preparing for it now before we discover that we ought to have nudged this thing in another direction ten years earlier. And since it requires a vastly elevated understanding of human ethics, it may well take decades to learn what we need to make our AGIs have not just superintelligence, but supercompassion.

Artificial IntelligenceEmployment

Keep on Truckin’

An article on Bloomberg suggests that in the short term at least, autonomous trucks have the potential to make the lives of truckers better by allowing them to teleoperate trucks and therefore see their families at night. Of course, many of them see this as the prelude to not being needed at all:

“I can tell the difference between a dead porcupine and a dead raccoon, and I know I can hit a raccoon, but if I hit a porcupine, I’m going to lose all the tires on the truck on that side,” says Tom George, a veteran driver who now trains other Teamsters for the union’s Washington-Idaho AGC Training Trust. “It will take a long time and a lot of software to program that competence into a computer.”

Perhaps.  Or maybe it just takes driving long enough in reality or in training on captured footage to encounter both kinds of roadkill and learn by experience.

Artificial IntelligenceEmployment

This Time It’s Different

This superb video drives a stake through the heart of the meme that progress always equals more and better jobs:

All this and a cast of cartoon chickens. This is where it very much becomes clear that we need to analyze second-order effects. The video just starts wondering about those at the end. If we get very good at producing cheaper products at the expense of more and more jobs, who will buy those products? Who will be able to afford them if there is a rising underclass of unemployed that has trouble getting food, let alone iPhones? Sure, the market may turn to higher luxury items such as increasingly tricked-out autonomous cars, that can be afforded by the 1% (or less) who own the companies, but this is an unstable dynamic, a vicious circle. What will terminate that runaway feedback loop?

Artificial IntelligenceEmployment

When will a machine do your job better than you?

Katja Grace at the Future of Humanity Institute at the University of Oxford and fellow authors surveyed the world’s leading researchers in artificial intelligence by asking them when they think intelligent machines will better humans in a wide range of tasks. They averaged the answers, and published them at https://arxiv.org/pdf/1705.08807.pdfThe results are… surprising.

First up, AIs will reach human proficiency in the game of Go in 2027… wait, what? Ah, but this survey was conducted in 2015. As I noted in Crisis of Control, before AlphaGo beat Lee Sedol in 2016, it was expected to be a decade before that happened; here’s the numeric proof. This really shows what a groundbreaking achievement that was, to blindside so many experts.

Forty-eight percent of respondents think that research on minimizing the risks of AI should be prioritized by society more than the status quo. And when they analyzed the results by demographics, only one factor was significant: geography. Asian researchers think human level machine intelligence will be achieved much sooner:Screen Shot 2017-06-01 at 12.58.26 PM

Amusingly, their predictions for when different types of job will be automated are relatively clustered under 50 years from now with one far outlier over 80:  Apparently, the job of “AI Researcher” will take longer to automate that anything else, including surgeon. Might be a bit of optimism at work there…

 

Artificial IntelligenceEmploymentTechnology

Sit Up and Beg

More reader commentary:

“If in the old view programmers were like gods, authoring the laws that govern computer systems, now they’re like parents or dog trainers. […] Programming won’t be the sole domain of trained coders who have learned a series of arcane languages. It’ll be accessible to anyone who has ever taught a dog to roll over.”

Totally agree except this will not be as easy as some may think. I think the most important part of great programmers is not their programming skill but their ability to take a small number of broad requirements and turn them into the extremely detailed requirements necessary for a program to succeed in most/all situations and use cases, e.g. boundary conditions. As somewhat of an aside we hear even today about how a requirements document given to developers should cover ‘everything’. If it really covered everything it would have to be on the order of the number of lines of code it takes to create the program.

If there’s been anything about developers that elevated them to some divine level, it isn’t their facility with the proletarian hardware but their ability to read the minds of the humans giving them their requirements, to be able to tell what they really need, not just better than those humans can explicate, but better than they even know. That talent, in the best developers (or analysts, if the tasks have been divided), is one of the most un-automatable acts in employment.

The quotation was from Wired magazine, and I think, however, that it has to be considered in a slightly narrow context. Many of the tough problems being solved by AIs now are done through training. Facial recognition, voice recognition, medical scan diagnosis; the best approach is to train some form of neural network on a corpus of data and let it loose. The more problems that are susceptible to that approach, the more developers will find their role to be one of mapping input/output layers, gathering a corpus, and pushing the Learn button. It will be a considerable time (he said, carefully avoiding quantifying ‘considerable’) before that’s applicable to the general domain of “I need a process to solve this problem.”

Artificial IntelligenceEmployment

How to Prepare Your Career for Automation

This excellent article by Sam DeBrule explores how to survive the coming changes:

To position oneself to be augmented, rather than replaced by AI, one should embrace the benefits of AI enabled technology and invest in the “soft” skills that will empower her to stand out as an adaptable, personable and multi-faceted employee.

These skills are the higher-order reasoning that AI is not yet close to emulating: Creative thinking, emotional intelligence, problem solving. These are excellent arguments for those people on the higher end of the IQ scale. What does the future hold for people who are not as intellectually equipped?

Artificial IntelligenceEmployment

Creative tasks easier to automate than boring ones

Venture capitalists point out that robots are taking over the jobs we’d rather they leave alone. Artificial intelligences are making useful progress at creating original art, music, and prose, the sort of tasks we’d hoped they would free us up to be able to do ourselves. Meanwhile, the jobs we want them to do are proving “shockingly hard to automate”:

The cleaning robot Roomba was one of the first commercially available robots to everyday consumers in 2002. Almost 15 years later, there has not been any real innovation in terms of cleaning robots that has seen commercial success.

[…]

Textile manufacturing, one of the first industries to be automated, remains incredibly hard to automate completely. Robots work best when manipulating solid objects, but textiles shear, stretch, and compress, making them difficult for robots to handle.

[…]

Automating the harvesting of crops that are today picked by hand has so far been hard because many of these crops can be damaged easily and computers have had trouble with visual recognition of the fruit or produce they are trying to pick.