Many commentators thought Google had made a mistake with its gung ho presentation. Duplex not only violated the dictum that AI should never pretend to be a person; it also appeared to violate our trust. Duplex was a fake-out, and an alarmingly effective one. Afterward, Google clarified that Duplex would always identify itself to callers. But even if Google keeps its word, equally deceptive voice technologies are already being developed. Their creators may not be as honorable. The line between artificial voices and real ones is well on its way to disappearing.
T he most relatable interlocutor, of course, is the one that can understand the emotions conveyed by your voice, and respond accordingly—in a voice capable of approximating emotional subtlety.
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Emotion detection—in faces, bodies, and voices—was pioneered about 20 years ago by an MIT engineering professor named Rosalind Picard, who gave the field its academic name: affective computing. She and her graduate students work on quantifying emotion. I can snatch it with a sharp, angry, jerky movement. Appreciating gestures with nuance is important if a machine is to understand the subtle cues human beings give one another.
I could be nodding in sunken grief. In , Picard co-founded a start-up, Affectiva, focused on emotion-enabled AI. The company hopes to be among the top players in the automotive market. Affectiva initially focused on emotion detection through facial expressions, but recently hired a rising star in voice emotion detection, Taniya Mishra. But we betray as much if not more of our feelings through the pitch, volume, and tempo of our speech.
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Computers can already register those nonverbal qualities. The key is teaching them what we humans intuit naturally: how these vocal features suggest our mood. The biggest challenge in the field, she told me, is building big-enough and sufficiently diverse databases of language from which computers can learn. Classification is a slow, painstaking process. Three to five workers have to agree on each label. There is a workaround, however. Once computers have a sufficient number of human-labeled samples demonstrating the specific acoustic characteristics that accompany a fit of pique, say, or a bout of sadness, they can start labeling samples themselves, expanding the database far more rapidly than mere mortals can.
As the database grows, these computers will be able to hear speech and identify its emotional content with ever increasing precision. During the course of my research, I quickly lost count of the number of start-ups hoping to use voice-based analytics in the field. The software might have picked up a hint of lethargy or slight slurring in the speech that the doctor missed. I was holding out hope that some aspects of speech, such as irony or sarcasm, would defeat a computer.
The natural next step after emotion detection, of course, will be emotion production: training artificially intelligent agents to generate approximations of emotions. Once computers have become virtuosic at breaking down the emotional components of our speech, it will be only a matter of time before they can reassemble them into credible performances of, say, empathy. Taniya Mishra looks forward to the possibility of such bonds.
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She fantasizes about a car to which she could rant at the end of the day about everything that had gone wrong—an automobile that is also an active listener. At this point, it will no longer make sense to think of these devices as assistants.
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They will have become companions. By now, most of us have grasped the dangers of allowing our most private information to be harvested, stored, and sold. We know how facial-recognition technologies have allowed authoritarian governments to spy on their own citizens; how companies disseminate and monetize our browsing habits, whereabouts, social-media interactions; how hackers can break into our home-security systems and nanny cams and steal their data or reprogram them for nefarious ends. Virtual assistants and ever smarter homes able to understand our physical and emotional states will open up new frontiers for mischief making.
But there are subtler effects to consider as well. Take something as innocent-seeming as frictionlessness. To me, it summons up the image of a capitalist prison filled with consumers who have become dreamy captives of their every whim. An image from another Pixar film comes to mind: the giant, babylike humans scooting around their spaceship in Wall-E. I fear other threats to our psychological well-being. A world populated by armies of sociable assistants could get very crowded. And noisy. And once our electronic servants become emotionally savvy?
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They could come to wield quite a lot of power over us, and even more over our children. In their subservient, helpful way, these emoting bots could spoil us rotten. Programmed to keep the mood light, they might change the subject whenever dangerously intense feelings threaten to emerge, or flatter us in our ugliest moments. How do you program a bot to do the hard work of a true, human confidant, one who knows when what you really need is tough love? Children growing up surrounded by virtual companions might be especially likely to adopt this mass-produced interiority , winding up with a diminished capacity to name and understand their own intuitions.
Like the Echo of Greek myth, the Echo Generation could lose the power of a certain kind of speech. Maybe our assistants will develop inner lives that are richer than ours.
And then she leaves him, because human emotions are too limiting for so sophisticated an algorithm. Though he remains lonely, she has taught him to feel, and he begins to entertain the possibility of entering into a romantic relationship with his human neighbor. When you stop and think about it, artificial intelligences are not what you want your children hanging around with all day long.
If I have learned anything in my years of therapy, it is that the human psyche defaults to shallowness. We cling to our denials.
What better way to avoid all that unpleasantness than to keep company with emotive entities unencumbered by actual emotions? They have a way of making themselves known. The college-admissions process is so fraught with hysteria, many parents attempt to cheat their kids into elite institutions.
What the Amazon founder and CEO wants for his empire and himself, and what that means for the rest of us.
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Where in the pantheon of American commercial titans does Jeffrey Bezos belong? John D. Rockefeller refined 90 percent of American oil, which supplied the pre-electric nation with light. Bill Gates created a program that was considered a prerequisite for turning on a computer. At 55, Bezos has never dominated a major market as thoroughly as any of these forebears, and while he is presently the richest man on the planet, he has less wealth than Gates did at his zenith.
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The scope of the empire the founder and CEO of Amazon has built is wider. Indeed, it is without precedent in the long history of American capitalism. As WeWork crashes and Uber bleeds cash, the consumer-tech gold rush may be coming to an end.
Several weeks ago, I met up with a friend in New York who suggested we grab a bite at a Scottish bar in the West Village. He had booked the table through something called Seated, a restaurant app that pays users who make reservations on the platform. We ordered two cocktails each, along with some food. I am never offended by freebies. But this arrangement seemed almost obscenely generous. To throw cash at people every time they walk into a restaurant does not sound like a business.
It sounds like a plot to lose money as fast as possible—or to provide New Yorkers, who are constantly dining out, with a kind of minimum basic income. Our unpredictable and overburdened schedules are taking a dire toll on American society. Just under a century ago, the Soviet Union embarked on one of the strangest attempts to reshape the common calendar that has ever been undertaken.
As Joseph Stalin raced to turn an agricultural backwater into an industrialized nation, his government downsized the week from seven to five days. Saturday and Sunday were abolished. In place of the weekend, a new system of respite was introduced in The government divided workers into five groups, and assigned each to a different day off. On any given day, four-fifths of the proletariat would show up to their factories and work while the other fifth rested.
Each laborer received a colored slip of paper—yellow, orange, red, purple, or green—that signified his or her group. The unicorn massacre unfolding today is exactly the opposite of what happened in Both then and now , consumer-tech companies spent lavishly on advertising and struggled to find a path to profit. Both then and now , companies that bragged about their ability to change the world admitted suddenly that they were running out of money.
Both then and now , the valuations of once-heralded tech enterprises were halved in a matter of weeks. Both then and now , there was a widespread sense of euphoria curdling into soberness, washed down with the realization that thousands of workers in once-promising firms were poised to lose their jobs. As the impeachment inquiry intensifies, some associates of the president predict that his already erratic behavior is going to get worse.
The country is entering a new and precarious phase, in which the central question about President Donald Trump is not whether he is coming unstrung, but rather just how unstrung he is going to get. The boiling mind of Trump has spawned a cottage industry for cognitive experts who have questioned whether he is, well, all there.