On Tuesday, University of Pennsylvania sociologist Steve Viscelli, author of The Big Rig: Trucking and the Decline of the American Dream, visited Zócalo with Issues in Science and Technology senior editor Lisa Margonelli to consider how automated trucking might transform American life.

The Twitter Live conversation explored the promise of automated trucking—from potentially eliminating thousands of trucking-related deaths and injuries to making shipping much faster and cheaper to improving the industry’s outsized impact on the environment. For instance, Viscelli noted that automated trucks can accelerate and brake more efficiently than human drivers, and they can be designed for specific uses to make their trips even more energy efficient (unlike trucks that must vacillate between city and highway driving). And automated trucks have capabilities like “platooning,” where self-driving trucks travel close together in aerodynamically efficient packs.

But for all of automated trucking’s promises, there are as many questions about labor protections for the humans who will still be needed in the cockpit. Increasing automation has been harmful for drivers as a whole, Viscelli explained. From new surveillance measures imposed on drivers to the steep decline in truckers’ pay following deregulation of the trucking industry in the 1980s, the last few decades have been hard for those behind the wheel. “Essentially we’ve seen 40 years of technology deskilling the job and making it worse,” Viscelli said.

Viscelli, who spent six months as a long-distance truck driver himself, described the intense lifestyle and learning curve of the job. “You’re out on the road for two to three weeks at a time at least, you’re working sometimes in excess of a hundred hours a week—your entire day, 24 hours a day, is timed to the loads that you’re hauling,” he said. Speaking to the future of trucking, Viscelli concluded, state and federal lawmakers must work to protect workers and develop a comprehensive set of policies that respond to what we want our freight system to look like.

Quoted with Steve Viscelli:

“We would not be talking about self-driving trucks right now if it had not been for DARPA, and for the Defense Department’s interest in self-driving trucks. This is technology that sits on decades of investment in computer science and sensors and other sorts of technologies that are vital to this that were made possible through public funding. … [Today] we’re essentially looking at these threats to truckers’ jobs that resulted from our tax dollars being used to solve a military problem, and now that it’s ready for potential commercialization, of course the private sector has stepped in to try to bring these things to market, and of course, profit for themselves off it.”

Watch the full conversation below:

We’re live! Join Zócalo and @ISSUESinST to discuss “How Will Robot Trucks Change American Life?” with @LisaMargonelli and @SociologyatPenn prof Steve Viscelli: https://t.co/FsJpI6Ljgy

— Zócalo Public Square (@ThePublicSquare) January 19, 2021

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But the worst, we are told, is yet to come, because both countries have extremely low birth rates. Harvard sociologist Mary Brinton calls this “a demographic time bomb.” Italian Health Minister Beatrice Lorenzin says simply, “We are a dying country.”

Could all the experts be wrong?

Yes, and the reason is robots.

Conventional wisdom has long held that countries need enough young people to fill all the jobs left behind by retirees, and to create macroeconomic growth to finance all those retirements. A shrinking nation will have a very difficult time achieving any of those aims.

What does it mean to be shrinking? To sustain a developed country’s population, the birth rate needs to be 2.1 children per woman. In Japan, the rate is 1.4. In Italy, it’s 1.39, the lowest in Europe. In the United States, the rate is 1.86, but that’s supplemented by significant immigration. So while much of the developing world is experiencing an unsustainable population explosion, the conventional wisdom is that many Western industrialized countries face a sustainability problem from too few births.

That’s certainly the perception in Japan. This summer, the Japanese government made headlines by reporting that its population fell a record amount in 2016, by a total of 308,084 people, to 125.6 million. But the truly eye-catching number was this: Annual births dropped below one million for the first time since the government began its survey in 1979. By 2045, Japan is projected to lose 900,000 people a year, which is more than the total population of Indianapolis. Compounding the labor shortage, Japan has very strict immigration controls.

The Italian picture also is bleak, but in different ways. In Italy, fewer Italian babies were born in 2014 than in any year since the country was unified in 1861. This has been offset, recently and partially, only by an inflow of migrants, mainly fleeing Africa and the Middle East. For the last three years, the number of arrivals has been 580,000, but that’s still less than one percent of Italy’s 60 million population. Then there’s the unanswered question of where the new arrivals will work. Italy’s stagnant economy has produced high rates of unemployment, particularly among the young.

And that’s before another future trend takes hold: a devastating loss of employment due to exponential technological advances. In a groundbreaking paper published in 2013, Oxford’s Michael Osborne and Carl Frey concluded that 47 percent of all U.S. jobs are at risk of being taken over by “computerization” in the next decade or two. The futurist Martin Ford framed the problem in more frightening terms, proclaiming, in a popular book, “The Rise of the Robots.”

But while these two trends—declining births and new robot “births”—might be regarded as individually ominous, the fact that they are happening at the same time offers reason for hope. Could robots replace the workers who aren’t being born in Italy, in Japan, and across the developed world?

Such a replacement is not a radical idea—or a new one. As early as 1933, legendary economist John Maynard Keynes predicted the replacement of workers by machines, with massive unemployment “due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.”

The 2013 Oxford study was motivated by this prediction. It assessed the probability of job loss over the next decade or two in 702 detailed occupations in the United States. The least vulnerable jobs (less than 1 percent at risk) include athletic trainers, oral surgeons, and anthropologists. The most vulnerable jobs (at 99 percent risk) include telemarketers and data entry keyers.

The CEO of Daimler-Benz has been more explicit, predicting: “In 2030, computers will become more intelligent than humans” and “70-80 percent of jobs will disappear in the next 20 years.” There also will be some new jobs created by new technologies—but it’s unclear how long it will take them to materialize.

If this vision of the future proves true, there will be casualties, as no revolution is bloodless. The Industrial Revolution terrorized textile and agricultural workers, and the computer revolution hollowed out the middle class of most Western industrialized nations.

But the best kind of country to be during the rise of the robots is a country with a declining population. In Italy and Japan, rather than having massive numbers of human workers displaced, robots may do the work that otherwise would have gone undone.

Of course, it will be crucial for countries to strike a balance—to make sure the robots come on line at roughly the same rate that populations decline. This could mean imposing heavier taxes on families that have too many children, or excise taxes on firms that automate too quickly. The revenues would go to retrain workers for jobs that can’t easily be automated. In some cases, nations could mandate human labor for some jobs, or guarantee a universal basic income, as some countries are now debating.

The 2013 Oxford study says that workers also will have to acquire creative and social skills, areas in which computers lag behind. The bad news is that few countries are adjusting their schools and training centers in order to meet the needs of today’s technology, much less the technology of the future. Across the Western world, companies report having millions of jobs for which they cannot find qualified candidates.

If societies don’t educate people to take those new jobs, they will be filled by robots. Or by nothing at all.

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“Err, that’s not what the app is telling me to do.”

“Yes, but it’s faster this way. The app is taking you to the beltway. Traffic is terrible there!”

“Okay. I don’t know these roads.”

So went a conversation with an Uber driver in northern Virginia recently. But imagine it was a self-driving Uber. Would you even have that conversation, or would you be doomed to a frustrating 25 minutes on the beltway when you could have been home in 15?

And as your frustration mounts, will the AI driving the car recognize this—or appear to—and respond accordingly? Will customers prefer cars that seem to empathize?

Or imagine instead that you and your partner are arguing in the back seat over which route to take. How will you feel when your partner seems to be siding with the machine? Or the machine is siding with your partner?

Empathy is widely praised as a good thing. But it also has its dark sides: Empathy can be manipulated and it leads people to unthinkingly take sides in conflicts. Add robots to this mix, and the potential for things to go wrong multiplies. Give robots the capacity to appear empathetic, and the potential for trouble is even greater.

A traffic robot in the Democratic Republic of Congo. Photo courtesy of Wikimedia Commons.

To know why this is a problem, it helps to understand how empathy works in our daily lives. Many of our interactions involve seeking empathy from others. People aim to elicit empathy because it’s taken as a proxy for rational support. For example, the guy in front of you at an auto repair shop tells the agent that he wants his money back: “The repair you did last month didn’t work out.” The agent replies: “I’m sorry, but this brake issue is an unrelated and new repair.” The argument continues, and the customer is getting angry. It seems like he might even punch the agent.

But instead, at this point, the customer and the agent might both look to you. Humans constantly recruit bystanders. Taking sides helps to settle things before they escalate. If it’s two against one, the one usually backs down. A lot of conflicts thereby get resolved without violence. (Compare chimpanzees, where fights often lead to serious injury.) Our tendency to make quick judgments and to take sides in conflicts among strangers is one of the key features of our species.

When we take sides, we assume the perspective of our chosen side—and from here it is a short step to develop emotional empathy. According to the three-person model of empathy introduced by Breithaupt, this is not entirely positive, because the dynamic of side-taking makes the first side we take stick, and we therefore assume that our side is right, and the other side is wrong. In this way, empathy accelerates divisions. Further, we typically view this empathy as an act of approval that extends to our consequent actions, including, for example, lashing back at the other side.

Now let’s imagine that the agent at the repair shop is a robot. The robot may appeal to you, a supposedly neutral third party, to help it to persuade the frustrated customer to accept the charge. It might say: “Please trust me, sir. I am a robot and programmed not to lie.”

Sounds harmless enough, does it? But suppose the robot has been programmed to learn about human interactions. It will pick up on social strategies that work for its purposes. It may become very good at bystander recruitment. It knows how to get you to agree with its perspective and against the other customer’s. The robot could even provide perfect cover for an unscrupulous garage owner who stands to make some extra money with unnecessary repairs.

You might be skeptical that humans would empathize with a robot. Social robotics has already begun to explore this question. And experiments suggest that children will side with robots against people when they perceive that the robots are being mistreated. In one study, a team of American and Japanese researchers carried out an experiment in which children played several rounds of a game with a robot. Later the game was interrupted by an overzealous confederate of the experimenters, who ordered the robot into a closet before the game was over. The robot complained and pleaded not to be sent into the closet before the game could be completed. The children indicated that they identified socially with the robot and against the experimenter.

We also know that when bystanders watch a robot and a person arguing, they may take the side of the robot and may start to develop something like empathy for the machine. We already have some anecdotal evidence for this effect from traffic-directing robots in Kinshasa. According to photojournalist Brian Sokol in The Guardian, “People on the streets apparently respect the robots … they don’t follow directions from human traffic cops.” Similarly, a study conducted at Harvard demonstrated that students were willing to help a robot enter secured residential areas simply because it asked to be let in, raising questions about the potential dangers posed by the human tendency to respect a request from a machine that needs help.

It is a relatively short step from robots that passively engage human empathy to robots that actively recruit bystanders. Robots will provoke empathy in situations of conflict. They will draw humans to their side and will learn to pick up on the signals that work. Bystander support will then mean that robots can accomplish what they are programmed to accomplish—whether that is calming down customers, or redirecting attention, or marketing products, or isolating competitors. Or selling propaganda and manipulating opinions.

It would be naive to think that AI corporations will not make us guinea pigs in their experiments with developing human empathy for robots. (Humans are already guinea pigs in experiments being run by the manufacturers of self-driving cars.) The robots will not shed tears, but may use various strategies to make the other (human) side appear overtly emotional and irrational. This may also include deliberately infuriating the other side. Humans will become unwitting participants in an apparatus increasingly controlled by AI with the capacity to manipulate empathy. And suddenly, we will have empathy with robots, and find ourselves taking their sides against fellow human beings.

When people imagine empathy by machines, they often think about selfless robot nurses and robot suicide helplines, or perhaps also robot sex. In all of these, machines seem to be in the service of the human. However, the hidden aspects of robot empathy are the commercial interests that will drive its development. Whose interests will dominate when learning machines can outwit not only their customers but also their owners?

Researchers now speculate about whether machines will learn genuine empathy. But that question is a distraction from the more immediate issue, which is that machines will not “feel” what humans feel, even if they get good at naming human emotions and responding to them. (At least for a while.) But in the near future, it doesn’t matter which emotions machines have. What is important is which emotions they can produce in humans, and how well they learn to master and manipulate these human responses. Instead of AI with empathy, we should be more concerned about humans having misplaced empathy with AI.

The post Why We Should Fear Emotionally Manipulative Robots appeared first on Zócalo Public Square.

Start with the freak-out. One thing that computers are good for is making copies—lots of copies. Drag your music folder from your hard drive to your backup Dropbox and congratulations, you’ve just duplicated thousands of copyrighted songs. If you look up the section of the Copyright Act that sets out what counts as infringement, the very first Thou Shalt Not is “reproduce the copyrighted work.” In theory, Congress could have added some language saying that putting your music in your Dropbox that no one else can access isn’t infringement. In practice, well, it’s Congress.

Congressional inaction has meant that the problem of explaining why the Internet isn’t just an infringement machine in need of a good unplugging has been kicked over to the courts. (Yes, the courts staffed by judges who call Dropbox “the Dropbox” and “iDrop.”) And in the process of keeping computers legal, the judges who make copyright law have developed some surprisingly broad rules shielding automatically made copies from liability.

Take, for example, the 2009 case A.V. v. iParadigms, in which high schools compelled students to submit their term papers to Turnitin, a plagiarism-detection site. First it compares papers to those already in its database, looking for suspicious similarities; then it stores the paper to compare to future submissions. Four students sued, arguing that these stored copies infringed their copyrights in their papers.

The court disagreed, because of course you shouldn’t be able to use copyright to keep your teachers from finding out whether you cheated on your homework. But its reasoning is fascinating. Turnitin, the court held, made a “transformative” use of the papers because its use was “completely unrelated to expressive content.” Turnitin’s computers might have copied the papers, but they didn’t really read them. The court added, “The archived student works are stored as digital code, and employees of [Turnitin] do not read or review the archived works.”

Courts use similar logic in case after case. It’s not infringement if computers “read or review” the new copies, only if people do. Google famously scanned millions of books. Completely legal, four courts have agreed, because it’s not as though Google is turning the complete books over to people. “Google Books … is not a tool to be used to read books,” wrote one judge. In another strand of the litigation, the parties at one point proposed a settlement that would have allowed “non-consumptive” digital humanities research on the scanned books, defined as “research in which computational analysis is performed on one or more Books, but not research in which a researcher reads or displays substantial portions of a Book to understand the intellectual content presented within the Book.” This was fine, in the view of the author and publisher representatives who negotiated the proposed settlement. Computers can do what they want with books as long as no one actually “understand[s]” its “intellectual content.”

This attitude—computers don’t count—isn’t new, either. A century ago, the cutting edge in artistic robotics was the player piano. The Supreme Court heard a player-piano case in 1908 and held that the paper rolls “read” by the player pianos weren’t infringing. The rolls, Justice William Day reasoned, “[c]onvey[] no meaning, then, to the eye of even an expert musician.” Instead, they “form a part of a machine. … They are a mechanical invention made for the sole purpose of performing tunes mechanically upon a musical instrument.” The anthropocentrism is unmistakable. I’ve cataloged many different settings where copyright law finds ways to overlook copying as long as no humans are in the loop.

On the one hand, this makes perfect sense. Copyright is designed to encourage human creativity for human audiences. If a book falls in a forest and no one reads it, does it make an infringement? It seems like the only sensible answer is “No harm, no foul.” On the other hand, there’s something strange about a rule that tells technologists just to turn the robots loose. It encourages uses that don’t have much to do with human aesthetics while discouraging uses that do.

This hands-off approach to robotic readership stands in sharp contrast to copyright’s surprisingly obsessive fretting about robotic authorship. We’re at the dawn of a golden age of algorithmic authorship. Twitter bots like Olivia Taters and Hottest Startups, simple as they are, are capable of amazing poetry. From Push Button Bertha to Microsoft Songsmith, computer-generated music ranges from beautiful to banal. Special-effects artists and video-game programmers use procedural content generation to make vast imaginary worlds far beyond what any one person could hope to draw or design. And of course spambots and telemarketing robots (and counter-robots) are getting eerily good at mimicking human expression.

If all you knew about copyright was the way it treats computer-generated copies, you might think it would similarly look the other way and ignore computer-generated creativity. But no! No two plays of a video game are the same; the computer produces a new and different sequence of sights and sounds every time through. Copyright doesn’t care; video games are still copyrightable. Now, of course they are, it would be ridiculous if you could just completely rip off games, and case after case holds that you can’t.

But even as copyright law goes on recognizing copyright in computer-generated works, it can’t help obsessively worrying about them with the same kind of nervous energy it gives to monkey selfies and for the same reason: What if there’s no author? What if a creative work just popped into existence, without being clearly traceable to the artistic vision of a specific human? What then, buddy?

The funny thing is that just as the player piano roll shows that mechanical copying long predates computers, so does algorithmic creativity. You know what’s a device for making art according to rigidly specified algorithmic rules? A Spirograph. You know what else is? A Musikalisches Würfelspiel (sometimes apocryphally named for Mozart), a game in which you roll dice to select measures of music to string together into a minuet. Computers are faster and fancier, but for the most part not fundamentally different. There’s no need to futz around with speculating on whether your iPhone is a copyright-owning “author” of a Temple Run maze, any more than a Spirograph is the author of a hypotrochoid drawing. Typically either the programmer or the user or both are authors, and that’s good enough.

There will be harder cases of what Bruce Boyden calls “emergent works” that arise out of unpredictable algorithmic interactions. Where neither the programmer nor the user can reasonably foresee what a computer will do, the case for calling either of them an author is weak; they lack the kind of artistic vision copyright is supposed to promote and reward. But what’s interesting and tricky about these emergent works is not that they come from computers but that they’re unpredictable by anyone involved in their creation.

In an age of police killbots, worrying about whether Futurama’s Bender owns a copyright in his dream about killing all humans may seem a little beside the point. But copyright provides a useful window for thinking about hot-button issues in law and technology, ironically because the stakes are so much lower. There are low-tech precedents for new high-tech puzzles, if we care to see them.

The key is not to treat “computers” or “robots” or “drones” or other new kinds of technologies as unified phenomena we have to figure out all at once, but instead to look at the different kinds of ways they operate and can be used. The Dallas bomb robot was under direct police control at all times; it was a tool for safely delivering lethal force from a distance in the same way that a sniper rifle is. The most important issue it raised was the security of its communications channel—because the last thing you want when you strap a pound of C-4 to a robot is for someone else to hijack the controls. That’s a very different kind of problem than worrying about delegating life-or-death decisions to algorithms with a limited human presence in the loop. Lumping them together as “lethal robots” obscures more than it reveals; it makes it harder to identify which robots are dangerous and how, and harder to figure out what to do about them.

The same is true for copyright, for privacy, for civil rights, and for the dozens of other pressing public policy problems surrounding new technologies. You learn more about augmented reality by thinking about Pokémon Go than vice versa. Technology policy is complicated because the world is complicated.

The post Computers and Robots Can Copy Your Work, and Get Away With It appeared first on Zócalo Public Square.

The nutshell: Carnegie Mellon University roboticist Nourbakhsh imagines a future in which ever more intelligent forms of artificial intelligence dictate the way we work, shop, play, and travel.

Literary lovechild of: Isaac Asimov’s I, Robot and Hal Abelson, Ken Ledeen, and Harry Lewis’ Blown to Bits: Your Life, Liberty, and Happiness After the Digital Explosion.

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