by John Markoff
It got better. Thanks to a clever decision to place the application in a less obvious category on the App Store—Lifestyle—the Siri Assistant immediately shot right to the top of the category. It was one of the tricks Gruber had learned during his time at Real Travel—the art of search engine optimization. Although they had introduced Siri on the iPhone, Kittlaus had negotiated a spectacular agreement with Verizon, which did not yet carry the iPhone. He described it as “the greatest mobile deal in history.” The deal guaranteed that Siri would be on every new Verizon phone, which meant that the software would become the poster child for the Android smartphone. The deal was almost set in stone when Kittlaus received a call on his cell phone.
“Hi, Dag,” the caller said. “This is Steve Jobs.”
Kittlaus was momentarily stunned. “How did you get this phone number?” he asked.
“It’s a funny story,” Jobs replied. He hadn’t had any idea how to find the small development team, but he had hunted around. Because every iPhone developer had to supply a phone number to the App Store, Apple’s CEO found Kittlaus’s number in his developer database.
The team’s first foray into the legendary “reality distortion field”—Jobs’s personal brand of hypnotic charisma—wasn’t promising. Jobs invited the trio of Siri developers to his house in the heart of old Palo Alto. Jobs’s home was a relatively low-key 1930s Tudor-style set next to an empty lot that he had converted into a small grove of fruit trees and a garden. They met in the living room, which was sparsely furnished, like much of Jobs’s home, and featured an imposing Ansel Adams original.
Jobs presented the trio with a dilemma. They had all been successful in Silicon Valley, but none of them had yet achieved the career-defining IPO. The Siri team—and certainly their board members—thought it was very possible that they would receive a huge public stock offering for Siri. Jobs made it clear that he wanted to acquire Siri, but at that juncture the team wasn’t planning to sell. “Thank you very much,” they told him, and then left.
Several weeks later Apple was back. They were once again invited to Jobs’s home, where Jobs, then clearly sick despite continuing to publicly deny it, turned on the charm. He promised them an overnight market of one hundred million users—with no marketing and no business model. Or, Jobs said, they could roll the dice, try to be the next Google, and slog it out. The Siri team also understood that if they went with Verizon, they would run the risk of being shut out of the iTunes Store. Steve didn’t have to say it, but it was clear that they had to choose which half of the market they wanted.
Jobs’s offer sold them, but it didn’t immediately sell the board, which was by now eager for an IPO exit. The three founders had to reverse ground and persuade their board members. Ultimately the investors were convinced; Jobs’s offer was lucrative enough and offered much lower risk.
Soon after Apple acquired Siri in April of 2010, the Siri team moved into the very heart of the office space for Apple’s design group, on half of the top floor of Infinite Loop 2. Although Apple could have licensed Nuance to convert speech directly to text—which Google later did—Jobs decided that Apple would undertake the more ambitious task of placing an intelligent assistant software avatar on the iPhone. Siri helped solve another major problem that Apple had with its new iPhone and iPad. Glass screens and multitouch control could replace a keyboard and mouse for navigation through screens, but they did not work well for data entry. This was a weak point, despite Jobs’s magnificent demonstration of text entry and auto-correction during the first product introduction. Speech entry of single words or entire sentences is many times more rapid than painstakingly entering individual words by poking at the screen with a finger.
In the beginning, however, the project was met with resistance within the company. Apple employees would refer to the technology as “voice control,” and the Siri team had to patiently explain that their project had a different focus. The Siri project didn’t feed into the “eye candy” focus at Apple—the detailed attention of software and hardware design that literally defined Apple as a company—but was instead about providing customers with reliable and invisible software that worked well. But many engineers in the software development organization at Apple thought that if Steve—and later on one of his top lieutenants, Scott Forstall—didn’t say “make it happen,” they didn’t need to work on that project. After all, Apple was not recognized as a company that developed cloud-computing services. Why reinvent the wheel? An assistant or simply voice control? After all, how much difference would it really make? In fact, people were dying while reading email and “driving while intexticated,” so presenting drivers with the ability to use their phones safely while driving made a tremendous difference.
When Apple’s project management bureaucracy balked at the idea of including the ability to send a hands-free text message in the first version of the software, Gruber, who had taken the role of a free-floating technical contributor after the acquisition, said he would take personal responsibility for completing the project in time for the initial Apple Siri launch. He decided it was a “put your badge on the table” issue. With just a summer intern in tow, he worked on all of the design and prototyping for the text messaging feature. He begged and borrowed software engineers’ time to help build the system. In the end, it was accepted. At the time of Siri’s launch, it was possible to send and receive texts without touching the iPhone screen.
Not everything went as smoothly, however. The Siri team also wanted to focus on what he called “attention management.” The virtual personal assistant should also help people remember their “to-do list” in an “external memory” so they wouldn’t have to. The original Siri application had an elaborate design for what the team described as “personal memory”: it wove an entire set of tasks together in the right order, prodding the user at each step like a good secretary. In the race to bring Siri to the iPhone, however, much of the deeper power of the service was shelved, at least temporarily. The first iteration of Siri only included a small subset of what the team had originally created.
In his final act in the computing world, Steve Jobs had come down emphatically on the side of the forces of augmentation and partnership. Siri was intended to be a graceful, understated model for the future collaboration between humans and machines, and it marked the beginning of a sea change at Apple that would take years to play out. The project also came together in a furious rush, and sadly Jobs died the day after Siri’s debut. The product launch event in October 2011 thus had to acknowledge a muted counterpoint in what was otherwise a glorious crowning moment to their rocket-fast three-year crusade. Naturally, there was a shared feeling of triumph. On the morning of Siri’s unveiling, Cheyer found himself back in an Apple Store. He walked up to the store and next to the front door was a giant plasma display that read: “Introducing Siri!”
9|MASTERS, SLAVES, OR PARTNERS?
It was almost midnight in Grand Central Station on a spring night in 1992. An elderly man wearing a blue New York Times windbreaker was leaning on a cane on the platform, waiting for a train to Westchester County. I had been at the Times for several years and I was puzzled by the ghostly figure. “Do you work for the paper?” I asked.
Many years earlier, he said, he had been a typesetter at the Times. In 1973 his union negotiated a deal to phase out workers’ jobs while the company implemented computerized printing systems in exchange for guaranteed employment until retirement. Although he had not worked for more than a decade, he still enjoyed coming to the press in Times Square and spending his evenings with the remaining pressmen as they produced the next day’s paper.
Today, the printer’s fate remains a poignant story about labor in the face of a new wave of AI-based automation technologies. His union first battled with newspaper publishers in the 1960s and struck a historic accommodation in the 1970s. Since then, however, the power of unions has declined dramatically. In the past three decades, the unionized percentage of the U.S. workforce has fallen from
20.1 to 11.3 percent. Collective bargaining will not play a significant role in defending workers’ jobs against the next wave of computerization. Printers and typographers in particular were highly skilled workers who fell prey to the technical advances of a generation of minicomputers during the 1970s, and the cost of computing plummeted as technologies shifted from transistor-based machines to lower-cost integrated circuits. Today, the lone typesetter’s soft landing is an extraordinary rarity.
There is evidence that the 2008 recession significantly accelerated the displacement of workers by computerized systems. Why rehire workers when your company can buy technology that replaces them for less cost? A 2014 working paper released by the National Bureau of Economic Research confirmed the trend, and yet Henry Siu, an associate professor at the University of British Columbia and one of the authors of the report, clung to the conventional Keynesian view on technological unemployment. He explained: “Over the very long run, technological progress is good for everybody, but over shorter time horizons, it’s not that everybody’s a winner.”1 It is probably worth noting that Keynes also pointed out that in the long run, we are all dead.
Indeed, Keynes’s actuarial logic is impeccable, but his economic logic is now under assault. There is an emerging perspective among technologists and some economists that Keynesian assumptions about technological unemployment—that individual jobs are lost but the overall amount of work stays constant—no longer hold true. AI systems that can move, see, touch, and reason are fundamentally altering the equation for human job creation. The debate today is not whether AI systems will arrive, but when.
It is still possible that history will vindicate the Keynesians. Modern society may be on the cusp of another economic transformation akin to the industrial revolution. It is conceivable that social forces like crowdsourcing and the Internet-enabled reorganization of the workforce will remake the U.S. economy in ways that are now inconceivable. The Internet has already created new job categories like “search engine optimization,” and there will certainly be other Internet-enabled and unexpected new job categories in the future.
However, if there is a new employment boom coming, it is still over the horizon. The Bureau of Labor Statistics projections now predict that U.S. job growth will be primarily influenced by the aging of American society, not by technological advances that displace and create jobs. The BLS predicts that of the 15.6 million jobs that will be created by 2022, 2.4 million of those jobs will be in the health-care and elder-care sectors. It is striking that among new types of jobs, those based on technological advances and innovation will account for a relatively small portion of overall job growth according to the BLS, and of those, software developers were highest ranked at twenty-sixth, with just 139,000 new jobs projected by 2022.2 The BLS projections suggest that technology will not be a fount of economic growth, but will instead pose a risk to all routinized jobs and skill-based jobs that require the ability to perform diverse kinds of “cognitive” labor, from physicians to reporters to stockbrokers.
Still, despite fears of a “jobs apocalypse,” there is another way to consider the impact of automation, robotics, and AI on society. Certainly AI and robotics technologies will destroy a vast number of jobs, but they can also be used to extend humanity. Which path is taken will be determined entirely by individual human designers. Tandy Trower is a software engineer who once oversaw armies of software engineers at Microsoft Corporation, but now works from a cramped office in South Seattle. The four-room shop might be any Silicon Valley garage start-up. There are circuit boards and computers strewn in every direction, and there are robots. Many of them are toys, but several look suspiciously like extras from the movie Robot & Frank. The idea of developing a robot to act as a human caregiver speaks directly to the tensions between AI and IA approaches to robotics.
How will we care for our elderly? For some, integrating robots into elder care taps into a largely unmined market and offers roboticists the chance to orient their research toward a social good. Many argue that there is a shortage of skilled caregivers and believe that the development of robots that will act as companions and caregivers is a way of using artificial intelligence to ward off one of the greatest hazards of old age—loneliness and isolation.
The counterpoint to this argument is that there is not really a shortage of caregivers but rather a shortage in society’s willingness to allocate resources for tasks such as caregiving and education. “Of course we have enough human caregivers for the elderly. The country—and the world—is awash in underemployment and unemployment, and many people find caregiving to be a fulfilling and desirable profession. The only problem is that we—as a society—don’t want to pay caregivers well and don’t value their labor,” writes Zeynep Tufekci, a social scientist at the University of North Carolina at Chapel Hill.3 Tufekci was responding to an essay written by Louise Aronson, a gerontologist at the University of California, San Francisco who argued that there is an urgent need for robot caregivers to perform tasks that range from watching over the health of elder patients, organizing their lives, and serving as companions. She describes making house calls and staying much longer than she should for each patient as she is forced to play the dual role of caregiver and companion.4 Tufekci envisions a society in which a vast army of skilled human doctors will be trained to spend time with the elderly. Sadly, as she notes, we live in a world that places more value on the work of stockbrokers and lawyers than nursing aides and teachers. In the end, however, this argument is not about technology. Once, in agrarian communal societies, families cared for their elders. In Western society, that is frequently no longer the case, and it is inconceivable that we will return to any kind of geographically centralized extended family structure soon.
Still, Tufekci’s challenge poses several questions.
First, will robots ever approximate the care of a human stranger? There are many horror stories about elder-care treatment in modern nursing homes and care facilities. Tufekci argues that every elder deserves the attention of an educated, skilled, and compassionate Dr. Aronson. However, if that doesn’t happen, will increasingly low-cost robots make life for elders better or worse? The vision of an aging population locked away and “watched over by machines of loving grace” is potentially disturbing. Machines may eventually look, act, and feel as if they are human, but they are decidedly not.
However, robots do not need to entirely replace human caregivers in order to help the elderly. For example, there could be a web of interconnected robots that make it possible for elders who are isolated to build a virtual human community on the Internet. Perhaps shut-in elders will be the most loyal users of augmented reality technologies being designed by Magic Leap, Microsoft, and others. The possibility of virtual caregivers is a compelling idea for those who are physically infirm.
Today Tandy Trower places himself squarely in the augmentation camp. He came to robotics as a member of Bill Gates’s technical staff at Microsoft. Gates was touring college campuses during 2006 and realized that there was an intense interest in robotics at computer science departments around the country. Everywhere he went, he watched demonstrations of robotics research. After one of his trips, he came back and asked Trower to put together a proposal for a way that Microsoft might become more active in the emerging robotics industry. Trower wrote a sixty-page report calling on Microsoft to create a group that built software tools to develop robots. Microsoft gave Trower a small group of researchers and he went off to build a simulator and a graphical programming language. They named it the Microsoft Robotics Developer Studio.
Then, however, Gates retired to start his foundation, and everything changed at Microsoft. The new chief executive, Steve Ballmer, had a very different focus. He was more concerned about making money and less willing to take risks. Through Microsoft veteran and chief strategy officer Craig Mundie, he sent Trower a clear message: tell me how Microsoft is going to make money on this.
Ballmer was very clear: he wanted a business that
generated one billion dollars in revenue annually within seven years. Microsoft had industrial robotics partners, but these partners had no interest in buying software from Microsoft—they already had their own software. Trower started looking for different industries that might be interested in purchasing his software. He looked at the automotive industry, but Microsoft already had an automotive division. He looked at the science education market, but it didn’t have much revenue potential. It seemed too early to pitch a telepresent robot. The more he looked, the more he considered the problem of aging and elder care. “Wow!” he thought to himself. “Here is a market that is going to explode in the next twenty or thirty years.” Today in the United States more than 8.5 million seniors require some kind of assistance, and that number will increase to more than 21 million in the next two decades.
There was an obvious need for robotic assistance in elder care, and no major players were angling for that market. Despite his enthusiasm, however, Trower wasn’t able to persuade Mundie or Ballmer that Microsoft should invest in the idea. Ballmer was interested in shrinking the range of Microsoft investments and focusing on a few core items.
“I have to do this,” Trower thought to himself. And so in late 2009, he left Microsoft after twenty-eight years and founded Hoaloha Robotics—the word hoaloha translates from Hawaiian as “friend”—with the intent of creating a mobile elder-care robot at a reasonable cost. Half a decade later, Trower has developed a four-foot-tall robotic prototype, affectionately known as Robby. It isn’t a replacement for a human caregiver, but it will be able to listen and speak, help with medicine, relay messages, and act as a telepresence when needed. It doesn’t walk—it rolls on a simple wheel assembly that allows it to move fluidly in any direction. Instead of arms, it has a tray whose height it can adjust. This allows Robby to perform certain tasks, like picking up dropped items.