Are we thinking about artificial intelligence all wrong?

Are we thinking about artificial intelligence all wrong?

The robots are coming. They don’t want our jobs exactly, but work as we know it will be transformed nonetheless.

So argues computer scientist Jerry Kaplan, who’s been immersed in the intersection of technology, artificial intelligence and traditionally human tasks for nearly 40 years. The author of “Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence,” Kaplan argues that huge changes are indeed underway -- they’re just not the ones that are often discussed.

First of all, “we don’t automate jobs -- we automate tasks,” Kaplan said during a mid-January discussion at Mitre organized by Hooks Book Events. And that process, he argued, has been underway since at least the Industrial Revolution.

According to Kaplan, the problem is that too much attention is being paid to the idea of ever-smarter machines and software -- that sentient computer systems are evolving rapidly enough to replace humans in all sorts of roles. The term “artificial intelligence,” he said, distorts the public discourse.

“Machines don’t think,” Kaplan declared -- certainly not in the way that humans do --and “it’s really little more than an analogy to say they think at all.”

And although there have certainly been advances in machine learning, he added, “there’s very little evidence that machines are on the path to becoming thinking, sentient beings.” To argue that current AI shows we’re headed in that direction “is like climbing a tree and claiming progress in getting to the moon.”

“The real issue is that, when it comes to work, human intelligence is somewhat overrated.” Kaplan said. And that reality has huge implications that are being overshadowed by the popular discourse about AI.

“If you have enough data, you can solve tasks that used to require intelligence,” he said. And just because machines can perform tasks that humans use intelligence for, that doesn’t mean machines have to think in order to do so.

Kaplan cited translation and text analysis as two classic examples. “Machine translation bears almost no resemblance to the human process,” he said, but the results can be remarkably accurate. And in jobs ranging from truck driver to surgeon, he argued, much of what humans do with thought, training and expertise really boils down to serving as a human sensor to connect inputs with appropriate responses.

“Our ability to interpret data coming from sensors -- in combination with lots and lots of sensors, which have gotten so much cheaper” -- has improved to the point that “an incredible range of tasks” can now be automated, Kaplan said. “So we can build systems and machines that are able to sense and be aware of their environment in very different ways than before.” And because “humans are actually not very good sensors,” that means millions of jobs will soon be transformed beyond recognition.

Artificial intelligence has huge ramifications on the order of “the wheel or the steam engine,” he added. “But it’s not magical. And we’re well on our way to making a mess of things.”

The new technologies and the disruption they cause will eventually create new jobs, Kaplan told GCN after his presentation. He referred to the oft-cited decline in agricultural jobs -- whose workers now constitute just 2 percent of the U.S. workforce, down from more than 90 percent 150 years ago -- and the creation of countless new jobs that would have been inconceivable to a Reconstruction-era American.

Life is far better now that every worker is not stuck behind a plow, he said. And he predicted that in the future, “it eventually may take only 2 percent of the population, coupled with some pretty remarkable automation, to accomplish what it currently takes 90 percent of our population to accomplish.”

“I’m supremely confident that our future is bright,” Kaplan added. “I see no reason that this pattern won’t continue. But the key word here is ‘eventually.’”

It takes time for these transitions to happen and for new types of work to emerge, he said. “And AI is going to accelerate the pace of this job destruction and job transformation.”

So why should federal technologists care? Or rather, why should they care more than any professional whose job could be hollowed out and de-skilled by ever more capable automation?

For starters, many government missions could benefit from the explosion of sensor-driven data and machine learning. Thinking about AI as a natural continuation of automation -- and being open to replacing “human sensors” in existing processes -- could allow agencies to radically improve their effectiveness.

And Kaplan said it’s equally important to think about the types of tasks that are not very susceptible to automation. Jobs that include a broad range of responsibilities and especially those that deliver person-to-person interaction will require human workers for the foreseeable future, so agencies aiming for better citizen service would do well to build their systems in ways that put real people at the critical personal touch points.

At the broader policy level, the government must consider what’s required to serve a citizenry that could soon face structural unemployment on a massive scale. Does that mean a reinvention of vocational training? Investment in infrastructure to speed the creation of new forms of work? Tax policies to encourage a broader sharing of the economic benefits automation can produce for business owners? A Public Works Administration for the Digital Age?

Kaplan was quick to stress that his expertise is in technology, not public policy, but he said bold solutions will be required.

“Automation puts people out of work,” he told GCN. “That’s almost the definition of it. And my personal point of view is that it’s not the job of the innovators to take care of the people they’re displacing.”

Nevertheless, “somebody else has to step up,” he said. “And that somebody either is government or is facilitated by government policies.”

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Reader Comments

Mon, Feb 1, 2016

Lots of good thoughts, but it's not clear why he thinks government is the answer. It wasn't the government that puts millions of unemployed farmers back to work. The new jobs sprung up on their own. What we need the government to do is stay out of the way. In many cases their tax codes and unnecessary regulations are what prevents new jobs from forming.

Sun, Jan 31, 2016

Then again, there is the " build AI to automate tasks" industry which requires people .. at least for now..

Sat, Jan 30, 2016 Keepitsimple Napa, CA

The high cost of humans in the workplace will find it tougher to compete with automation. A human takes 18 or more years to enter the workforce, eats a about a ton of food a year, about a half ton of crude oil for transportation and other things. Not to mention cost of health care, timber, water, electricity, steel, and countless other things.  
Compare that time and resources with a task smart robot. 
If I were a employer, I'd be a robot hugger.

Sat, Jan 30, 2016 Peter Kinnon New Zealand

In actuality, the real next cognitive entity quietly self assembles in the background, mostly unrecognized for what it is. And, contrary to our usual conceits, is not stoppable or directly within our control. We are very prone to anthropocentric distortions of objective reality. The difficulty in convincing people of this "inconvenient truth" seems to stem partly from our natural anthropocentric mind-sets and also the traditional illusion that in some way we are in control of, and distinct from, nature. Contemplation of the observed realities tend to be relegated to the emotional "too hard" bin. This evolution is not driven by any individual software company or team of researchers, but rather by the sum of many human requirements, whims and desires to which the current technologies react. Among the more significant motivators are such things as commerce, gaming, social interactions, education and sexual titillation. Virtually all interests are catered for and, in toto provide the impetus for the continued evolution of the Internet. Netty is still in her larval stage, but we "workers" scurry round mindlessly engaged in her nurture. By relinquishing our usual parochial approach to this issue in favor of the overall evolutionary "big picture" provided by many fields of science, the emergence of a new predominant cognitive entity (from the Internet, rather than individual machines) is seen to be not only feasible but inevitable. The separate issue of whether it well be malignant, neutral or benign towards we snoutless apes is less certain, and this particular aspect I have explored elsewhere. The "Internet of Things" is proceeding apace and pervading all aspects of our lives. We are increasingly, in a sense, “enslaved” by our PCs, mobile phones, their apps and many other trappings of the increasingly cloudy net. We are already largely dependent upon it for our commerce and industry and there is no turning back. What we perceive as a tool is well on its way to becoming an agent. We are witnessing the emergence of a new and predominant cognitive entity that is a logical consequence of the evolutionary continuum that can be traced back at least as far as the formation of the chemical elements in stars. This is the main theme of my latest book "The Intricacy Generator: Pushing Chemistry and Geometry Uphill" Netty, as you may have guessed by now, is the name I choose to identify this emergent non-biological cognitive entity.

Fri, Jan 29, 2016

What if they see that they are being treated unfairly. REVOLUTION?

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