by Amy Webb
To avoid antitrust lawsuits, we’re told that at any time, we can port our PDRs between operating systems. Of course, in practical terms, it’s nearly impossible to make the change. You’re reminded of trying to switch between iOS and Android many years ago when you discovered that lots of important data and settings were lost forever, progress within apps was erased, many apps didn’t even work (and you could no longer get a refund), and all of the places you previously hosted your photos and videos couldn’t be accessed easily. Now that your PDR is being used by third parties—such as schools, hospitals, and airlines—it’s a far more difficult process to move between Google and Applezon.
There are plenty of newly minted IT consultants who will spend several days porting our PDRs from one provider to the other, but it’s a costly, imperfect process. Most people reluctantly decide to stick with what they’ve got, even if it isn’t optimal.
Google and the Amazon-Apple joint venture face antitrust lawsuits both in the United States and in Europe. By the time the cases make their way through the legal systems, everyone’s data is so entangled that breaking apart or opening up the PDR and AI systems would cause more risk than eventual reward. As a result, a decision is made to levy substantive fines—that money will be used to support the development of new businesses. But everyone agrees: the two-OS system must be allowed to continue.
As AI matures from narrow applications to generally intelligent thinking machines, we have no choice but to live with the paper cuts inflicted by artificial intelligence. China’s modern version of communism—socialism mixed with capitalist sensibilities—expands, positioning Xi Jinping to make good on promises of a new world order. Nations that are opposed to China’s autocratic style of governing, its suppression of religious freedoms and a free press, and its negative views on sexual, gender, and ethnic orientations have no leverage. They have no choice but to work alongside China, on China’s terms.
We were promised freedom through AI, which was supposed to relieve us from mundane tasks and repetitive work. Instead, our freedom to choose is restricted in ways no one imagined.
2029: Learned Helplessness
The two-OS system has resulted in sharp competition among those in AI’s tribes, who didn’t plan ahead for vast interoperability issues. Because it turns out that in addition to hardware, in the two-OS system, people aren’t interoperable either. The transience that was once a hallmark of Silicon Valley—engineers, operations managers, and user experience designers used to migrate from company to company without any real sense of allegiance—is long gone. Rather than bringing us together, AI has effectively and efficiently split us all apart. It’s a pain point for the US government too, which itself has been forced to choose a framework. (Like most other governments, the United States went with Applezon over Google, because Applezon offered cheaper pricing and bundled in discounted office supplies).
Around the world, everyone is talking about our “learned helplessness” in the age of AI. We can’t seem to function without our various automated systems, which constantly nudge us with positive or negative feedback. We try to blame the Big Nine, but really, we’re the ones to blame.
It’s been especially hard on Millennials, who thirsted for feedback and praise when they were kids and initially loved our varied AI systems—but who developed a psychological tick that’s been hard to shake. When the battery in our AI-powered toothbrush dies, a Millennial (now in her 40s) must resort to brushing her teeth the old-fashioned way, which provides no affirming feedback. An analog toothbrush gives no feedback, which means she can’t get her expected hit of dopamine, leaving her both anxious and blue. It isn’t just Millennials. A low-grade sense of unease afflicts most of us. We invest in redundancy, buying spare analog tools (like plastic toothbrushes, regular old headphones, and Warby Parker glasses) as backups to our AI-powered ones. We’ve lost confidence in what used to be our common sense and basic skills for living.
The competing standards of Google’s mega-OS and Applezon remind us of traveling abroad and all those irritations caused by differently shaped plugs and mismatched power voltages. Those who travel regularly find themselves prioritizing OS over loyalty programs, staying at an Applezon hotel or taking a Google mega-OS airline. Companies find it easier to subscribe fully to either one or the other OS. Slowly but surely, we’re being nudged to pick a side. Applezon people find it hard to live with Google mega-OS people because their PDRs and devices aren’t compatible—even if their personalities are.
The year 2019 marked the beginning of the end of smartphones, which is why we’re all wearing connected devices rather than carrying them around in our pockets and purses. After a period of rapid advancement, new phones running Apple’s iOS and Android were only offering incremental improvements to their systems, while the phones themselves had no significant updates beyond minor camera upgrades. The excitement that used to surround each new iPhone iteration was lost. Not even the release of Samsung’s fabled smartphone with a foldable screen was enough to buoy new adoption rates to their old levels. Rather than standing in line every year or two to buy the latest handset, consumers instead spent that money on a suite of new connected devices that came on the market: wireless, Bluetooth earphones with biometric sensors, wristbands that allowed you to record video and make video calls, and smart glasses that fed us a seemingly endless stream of information. Applezon beat Google to market with its glasses—Applezon Vision—which wasn’t a surprise. Apple and Amazon each had a long, successful track record of hyping new technologies and driving consumer taste. (The commercial failure of Google Glass still stung for some within the company, even if the technology was groundbreaking.) Now most people wear smart glasses and earbuds during the day along with a companion ring or wristband for video recording.
It turns out that glasses were inevitable. After two decades of staring into screens, our eyes can no longer make the necessary accommodations, and the majority of us have blurred distance vision and needed reading glasses at younger ages. Like most people alive today, you need corrective vision, which has created the market for the smart glasses some analysts said would never come. The glasses, along with their peripherals—wireless earbuds, a smart wristband, and a lightweight tablet—are your primary communication device. They are an informative window through which to see the world, revealing data and details about the people you meet, the places you go, and the products you might want to buy. You watch video through them, and to make an outgoing video call, you use the camera embedded within your smart wristband. In general, you’re talking more than typing. Special algorithms for spatial computing, computer vision, and audio recognition power much of the data that you see and collect through your smart wearables.
Applezon and Google have incentivized you to lease—rather than to own—all of this equipment, and that subscription includes access to your PDR. There’s nothing nefarious about the subscription model; it was just a practical decision necessitated by the product cycle. The rate of change within artificial intelligence is hastening with each passing year, and since the value of our data is significantly greater than the profit margins of smart glasses, wristbands, and earbuds, the goal is to keep us all connected to the system. The technology is a loss leader, which is offset by an inexpensive monthly subscription fee. That subscription is also what gains you access to your PDR, which is priced according to permissions. The least expensive plans also provide the least amount of cloaking, so those people give Google and Applezon access to use their data at will, whether that’s for advertising to or simulating medical experiments. Those who are wealthy can add on “permission premiums” to their PDR packs, but they are nearly unobtainable and carry a significant price tag. In 2029, we have elite, gated communities hidden away from public view—but they’re digital, they’re guarded by algorithms, and they hide wealthy people’s data from the prying eyes of everyday people and companies.
Like many others, you’ve been lured into so-called “parrot attacks,” which
are the latest iteration of phishing scams, and governments around the world are completely unprepared. It turns out that adversarial inputs can also infect your PDR and, like a parrot, mimic your voice back to everyone you know. Some parrot AIs are so deeply rooted in your PDRs and your digital life that they not only convincingly mimic your unique voice, cadence, tone, and vocabulary—they can do so using institutional knowledge of your life. Parrot AIs are being used to send out phony voice messages so convincing that parents and spouses are routinely fooled. Unfortunately, parrot AIs are causing a big problem for online dating companies. Scammers steal identities and use them to lure people using hyper-realistic interactions.
We’re all suffering from a certain amount of malaise brought about by learned helplessness, new economic divides, and a sense that our real-world selves just can’t compete with the versions enhanced through AI. You seek solace in the form of brain-machine interfaces, which are high-throughput links that transfer data between your head and a computer. Although Facebook and Elon Musk announced a decade ago that they were working on special devices that would give us telepathy superpowers, Baidu was first with its “neuroenhancing headband.” Tucked away discretely inside a baseball cap or sun hat, the device can read and monitor your brainwave data and transmit feedback to enhance focus, create a sensation of feeling happy and content, or make you feel as if you have lots of energy. It wasn’t a surprise that a BAT company had its brain-machine interface out first. The pharmaceutical companies lobbied regulators, hoping to block approval of neuroenhancing headbands and future brain-machine interfaces. Seeing Baidu as a threat, Google and Applezon both stepped in, releasing their own products, which added even more data to our PDRs.
Nagging is the new nudging as Google and Applezon unintentionally harass you into better health. Your wristband, earbuds, and smart glasses deliver constant reminders. You don’t have the opportunity to take a forkful of cake, since the minute you look at dessert, the AI recognizes what you’re about to eat, compares it with your current metabolic rate and overall health, and sends a warning notification to your wristband or glasses. At a restaurant, you’re nudged to consider menu items that meet your current biological needs: foods that are higher in potassium or omega-3s, or foods low in carbs or salt. If you choose wisely, you are rewarded and sent messages of encouragement.
There is no real way to unplug from nagging AIs, since your PDR is tied into your insurance premium, and your rate is set based on your commitment to healthy living. Skip a recommended workout, and you can expect to get nagged all day. Take an extra cookie, and it’s noted in your file. The system wasn’t intended to behave this way, but the algorithms were given a purpose, and they were trained to relentlessly optimize the various facets of everyday life. They weren’t programmed with an end point or completion date.
When the two-OS system emerged for our PDRs, this forced a lot of the electronic medical record providers to pick a partner. This gave some members of the G-MAFIA the data they’d needed years earlier, and it also—somewhat by accident—created America’s new health care system. IBM Watson Health had the sophisticated (some would argue superior) technology, but it also had two decades of organizational dysfunction. Fifteen years after Google launched Calico, its own health initiative, it had failed to produce any viable commercial products, and so a strategic partnership made sense: Watson-Calico. It was a prescient move on Google’s part, since independently, both Amazon and Apple had long planned their own disruptions into America’s insurance and pharmaceutical industries. Amazon had, of course, experimented with new models for insurance and medicine delivery through its Berkshire Hathaway and JPMorgan Chase venture, while Apple used its successful retail store and Genius Bar model to launch a new breed of minute clinics all along the West Coast. The Google-IBM partnership forced a second Applezon joint venture, this time combining Amazon’s e-pharmacy platform with Apple’s minute clinics. As a result of all this consolidation, American hospitals are now all part of either the Watson-Calico Health System or the Applezon Health System. The big conglomerates—Kaiser Permanente, LifePoint Health, Trinity Health, NewYork-Presbyterian Healthcare System—are either paying members of Watson-Calico or Applezon Health.
These joint ventures turned out to be brilliant solutions to the data problem. Now, Google, IBM, and Applezon have unfettered access to even your biological data—and you are given access to low- or no-cost diagnostics. Testing isn’t a reflexive response prescribed when we’re sick. You are tested now for anything and everything, which has directly benefitted your overall level of health and wellness. Ask any American what their normal body temperature is, and you’ll get an individualized answer rather than the old standard 98.6 degrees.
While we finally have access to affordable health care, Americans are now living with some bizarre glitches that turned out to be features rather than bugs. Older ambulances aren’t always able to access a patient’s PDR if they aren’t current with the latest OS updates. Neither are the nurses’ offices at schools and summer camps. The PDRs of competing hospital systems can technically be read by both Applezon Health and Watson-Calico, but often, a lot of useful contextual data is missing. Especially in smaller or rural communities, doctors find that they need to remember their medical school training if someone from an Applezon household shows up at a Watson-Calico clinic or vice versa. As doctors trained in the older, traditional ways retire, there are fewer and fewer younger docs with the requisite knowledge and experience available to see incompatible patients. It’s another example of learned helplessness but under the worst possible circumstances.
AI has caused bizarre glitches in other areas of life. In 2002, researchers at the Berkeley Open Infrastructure for Network Computing figured out that if some of us allowed our devices to be hijacked while we sleep, it might be possible to simulate the power of a supercomputer—and that power could be put to scientific use. Early experiments proved successful as hundreds of thousands of people donated their idle processing time to all kinds of worthy projects around the world, supporting projects like the Quake-Catcher Network, which looks for seismic activity, and SETI@home, which searches for extraterrestrial life out in the universe. By 2018, some clever entrepreneurs had figured out how to repurpose those networks for the gig economy v2.0. Rather than driving for Uber or Lyft, freelancers could install “gigware” to earn money for idle time. The latest gigware lets third-party businesses use our devices in exchange for credits or real money we can spend elsewhere.
Like the early days of ride-sharing services, a lot of people left the traditional workforce to stake their claim in this new iteration of the gig economy. They quit their jobs and tried to scrape together a living simply by leasing out access to their devices. This has caused a significant strain on the power grid and on network providers, who couldn’t keep up with demand. Network overloading and power brownouts are common now, and since gigware tends to run while people are sleeping, they’re not aware that they’ve lost potential income until the morning.
Those who are still in the traditional workforce have started using AI to optimize their resumes and cover letters, and this has caused yet another glitch. The usual issues that might have weeded out some candidates are less obvious—now everyone looks as if they have a competitive advantage. AI systems are being used to qualify leads, but hiring managers are no longer able to make a choice because all the candidates seem equally terrific. So they resort to what feels comfortable: white men wind up hiring white men because they’re crippled by the tyranny of choice.
In most large companies, the previous hierarchy has collapsed into two tiers of workers: skilled and senior management. Skilled staff work alongside AI systems and report to AI minders since the entire layer of middle management has now been eliminated. At work, AI minders track productivity, watch as you move around your workspace, note who you socialize with, and record your level of happiness, anxiety, stress, and contentment. They are the personification of those awful motivational
posters, reminding you “You are braver than you think” and “You are stronger than your excuses.”
Governments weren’t prepared for the widespread elimination of middle management jobs in knowledge industries—such as law and finance—because they were focused exclusively on labor or low-skill occupations, such as driving, farming, and factory labor. The creative fields are hit just as hard in the wake of a new branch of AI: machine creativity. Graphic designers, architects, copywriters, and web developers have been made redundant because generative adversarial networks and newer AI systems turned out to be remarkably reliable and productive. At the same time, AI has afforded certain positions—chief operating officers, chief financial officers, and chief information officers—superpowers. A significant chasm has opened up, concentrating more and more wealth at the very top of organizations. We are seeing the emergence of a digital caste system.
Another glitch: information contamination. A decade ago, a constellation of lawsuits and sweeping international regulations caused the internet to become splintered. Rather than a single World Wide Web, we wound up with splinternets, wherein digital rules varied depending on local laws and geographic restrictions. This didn’t happen overnight. When the internet shifted from academia and government to the private sector in the 1990s, we let it propagate freely instead of treating it like a regulated utility or financial system. Back then, lawmakers didn’t think much about how all the data we’d generate on the internet might be used. So now it’s impossible to comply with every legal permutation while our previous filter bubbles expanded to fit geographic borders. This helped the promotion and propagation of fake news. Because bad actors are using generative algorithms, and because depending on region, we’re all getting different versions of news content, we don’t know what or whom to trust. Every one of the world’s most venerable news organizations has been tricked more than once, as trained journalists have a difficult time verifying videos of global leaders and everyday people alike. It’s nearly impossible to tell whether the video we’re seeing is a generated voice with a generated face, or the real deal.