Crisis- 2038

by Gerald Huff

  “So you’re going to set them up to fail?” asked Ellul. “Use them as propaganda tools?”

  “No, of course not,” replied Pam. “If they succeed that’s great too, we’ve got more operational capability.”

  “This is an idiotic idea,” said Othello. “Let the community organizers put together marches with their little signs. Leave the operations to the professionals.”

  “I think the idea has some merit,” said Ellul. “I’d like to canvas the group. Do members think we should recruit Jacob and Melissa for an operation in LA?” Everyone tapped their screens or tablets. “Members are in favor seventeen to seven. I think we should proceed. Geneva and Zurich, do you have an operation identified?” Ellul asked, referring to JT’s code name.

  “Just like that?” interrupted Othello. “Some of us get completely ignored?”

  “Othello, you weren’t ignored,” said Ellul. “You made your case, as did Geneva, and the membership expressed its opinion. I took all the input and made a decision. Those are the rules in this collective.”

  “Fucking stupid rules,” said Othello not quite under his breath.

  “We did some scouting,” said JT. “There is a fully automated factory producing humanoid care robots in San Gabriel. It’s quite large and has some anti-drone defenses in place. But we think we’ve found a potential weakness, a synfuel tank just outside one of the key production areas.”

  “Another explosive drone attack?” asked Artemis.

  “No, unfortunately. LA is a trial site for new explosives detection tech. They’ve got ground and air assets that can sniff a few hundred molecules. We have to do it without explosives.”

  “What about an industrial laser mounted on a drone?” said Zerzan.

  “That might work,” said Pam. “We’ll look into that.”

  “And how are your civilians going to launch a drone undetected in a major city?” asked Othello.

  “They know the area and they’re creative,” said Pam. “We’ll see if they can figure that part out.”

  CHAPTER THIRTY-THREE

  SANTA BARBARA - NOVEMBER 29

  “Good morning, Allison.”

  “Good morning Roger. Would you like to hear the overnight summary of network activity or client news?”

  “No thank you. Bring up the RingTrue workspace please.”

  “Roger, it has been six days since you last engaged with network activity and client news, which is a significant break from your historical pattern. There are some alerts that have been active for several days now. Would you like me to silence them?”

  “Yes, Allison. I’m quite busy on the RingTrue project.”

  “And you also haven’t taken any new client requests. Should I automatically reject all new client calls?”

  “That would be best.”

  “I understand. Here is the RingTrue workspace.”

  “Great. Can you have Rosie make some eggs and toast and bring them with some coffee?”

  “Yes, Roger. Instructions transmitted.”

  Roger took a few minutes to reorient himself to the neural net configurations he’d been working on late the prior evening. With intimate knowledge of his own network he’d already reached nearly one hundred percent discovery of his synths with very few false positives. But before he went public with the tech he wanted to try to find other networks like his. The overnight runs had been searching for other synths.

  Rosie, his household robot, wheeled up with breakfast. “Just put it on the desk please Rosie.” The bot slid a tray onto the desk and wheeled back to the kitchen. Roger took a sip of coffee and stared at the results on his monitor. “Allison, is the data in window three accurate?”

  “Analyzing. Window three contains RingTrue analysis of highly negative sentiment areas of omnipresence. It identified over one hundred million possible synthetic online personas excluding your synths.”

  Jesus. That was nearly the size of his own network. “Display demographic profile of those personas please.” Allison computed and displayed geographic heat maps and charts by age, gender, online history, political leaning, religious affiliation, and cultural cohorts. Nothing jumped out at him compared to typical English speaking country demographics. “What about subject areas?” More charts appeared. There was one anomaly that interested him.

  “On chart four the highest bar is labeled technology. What was the sentiment on those topics?”

  “These personas were highly favorable towards technology and harshly critical of those against it,” Allison replied.

  “Wait, did you say favorable?”

  “Yes, Roger.”

  “Display a scrolling grid of persona commentary on technology please.” Roger watched as the OP posts rolled down his display. They were filled with stories of how tech of all sorts had made people’s lives easier. Medtech was a clear favorite, but there was a lot of chatter about the public service bots saving lives in natural disasters and how easy it was to transact with AIs.

  “Clear the grid, Allison. Show IP address range distribution for the OP posts from these personas on a time lapse for the last thirty days.” The IPv6 space was huge, so he didn’t expect to find anything. But he’d had embarrassing slip-ups with his own network in the early days with too many synths posting from the same IP. The distribution was about what you’d expect from random people in English-speaking countries, but there was one spot that caught his eye.

  “Allison, stop. Go back about 5 seconds. In the lower right corner there is a cluster of IPs, can you zoom in there?” Yes, this was definitely an anomaly. For about an hour the prior Friday there were nearly a million IPs in the 8A2E network. Roger opened a connection using the anonymous Torpedo service to a dark web IP mapping service and entered 8A2E and the relevant time frame. The network mapped to an organization called AstroFast Ventures.

  “Allison, please research AstroFast Ventures.”

  “Sorry, Roger. There is no registered entity ‘AstroFast Ventures’ in any global database.”

  Roger hit the mapping service again, trying to trace where the entries for the 8A2E network had been created from. He found another network, 14AE56, mapped to GreenTable Productions. These seemed like randomly generated names. He wrote a script to automatically trace back the IP network creation chain and search for the associated organization names. The non-existent organizations scrolled up his display. BlueTraveller Inc, YoungHunting LLC, NestWarning Ltd. Finally, after nearly a hundred traces, the script stopped. A dead end: TropicalWhetstone Systems Ltd also a non-existent entity. Someone had hidden their tracks very well.

  Roger spent several more hours tuning the configuration but couldn’t find any other large-scale networks. Using more Torpedo anonymous connections, he set up a private repo on the Tribal open source code hub and uploaded his code and neural net configurations along with some documentation he dictated to Allison. Everything was ready to go. The RingTrue extension to the RealLife project would enable every online service in omnipresence to detect and block the synths he and the mysterious other network had created. Everything he had worked on for twenty years.

  Roger paced back and forth in front of the floor to ceiling glass wall of his living room, searching the Santa Ynez Mountains and Spanish tile rooftops of downtown Santa Barbara for guidance that was not forthcoming. He argued pros and cons in his head of hitting the big green “publish” button on Tribal to make the repo public. It seemed like the right thing to do, morally. Humans should be able to engage each other for real in omnipresence, not argue with a bunch of fake AIs. But on the other hand, he had made commitments to his clients. They would lose support or, worse, be exposed as having manufactured support. Even Frances and Sara were at risk.

  As the sun began to settle down for the night, dipping below the horizon into the Pacific and turning the sky a kaleidoscope of colors, Roger returned to his desk. He tapped a button on the screen and confirmed the “Are you sure? This action cannot be undone!
” dialog. The RingTrue repo was deleted. For now. He had some revisions to make before it could go live.

  CHAPTER THIRTY-FOUR

  NEW YORK - DECEMBER 2

  The PBS TV studio lights dimmed and the director called for quiet on the set. Jake Dawson and Sara sat a few feet apart on opposite sides of a round wooden table, spot lights highlighting them against the room’s plain blue walls. Jake glanced up from his notes and tossed off his trademark greeting. “Welcome, friends, to another edition of Life Stories. I’m Jake Dawson. Tonight, we’re honored to have a unique and fascinating guest who has recently been taking the world by storm. Her name is Sara Dhawan. She was born sixteen years ago in a small village in rural India, but don’t let her age fool you. She has managed to impress millions with her intelligence, charm, and visionary prescriptions for what’s ailing the world. Welcome, Sara.”

  She smiled. “Thank you, Jake. It’s a real honor to be here.”

  “I think people have probably heard your remarkable biography and journey from a small village in India to the world stage. I’d like to talk about the message you’ve been bringing to people all over the world through your VR program and events. It seems to all start with technology. Why don’t you give us your perspective on that?”

  “You’re right, Jake. Science, technology, and engineering are the fundamental drivers of the improvement in humanity’s standard of living. Even so, this is a very recent development. If you look back over hundreds of thousands of years of human history, life remained essentially the same.

  “After thousands of generations of sitting still, in just the last dozen or so we’ve developed startling capabilities. And the rate of change is only going to accelerate. That is the nature of exponential growth, which is something hard for most of us to understand.”

  “You make this sound very positive, Sara. But many people don’t seem to be benefiting from all this technology.”

  Sara cocked her head. “I have to disagree with you, Jake. If you look over the long course of human history, we have never had such a small percentage of humanity in abject poverty, or dying of preventable diseases, or dying in wars. We have never had such a large percentage who are educated, healthy, and participating in our global economy.

  “There are two reasons why people believe things are so bad right now. The first is that our media culture thrives on drama, conflict, bad news, and the four-hour news cycle. The second is that, on a relative basis, the fruits of our technological bounty are being distributed increasingly unevenly. This is slowing economic progress and causing a great deal of tension.

  “These are the bugs in our cultural and socioeconomic system. These are problems we can fix, once we recognize them and generate the will to do so. People are being told that this is just the way things are, and the way they have to be. But that is of course not true. The way things are today certainly did not exist a thousand, a hundred, or even fifty years ago. Human beings created today’s socioeconomic systems. We write the rules that make these systems run. We can modify the existing ones or create entirely different ones when we choose to.”

  “You mentioned income inequality,” Jake said. “I was surprised to hear you say in Boston that you are in favor of income inequality. Why is that?”

  Sara said, “That’s not quite correct. It’s not a political position. I simply view income inequality as a natural outcome of the unequal distribution of talent and motivation.

  “However, it’s what we do about income inequality as a society that matters. Some say we should tax the wealthy at very high rates to level the outcomes. While I do think tax rates need to go up to fund a guaranteed basic income, I do not think that government is the right institution to solve all our problems. Giving government more money in the form of taxes is not the most efficient way to move humanity forward.”

  Sara leaned forward slightly. “Let’s imagine you have lots of money and I don’t. There are four ways in which we can deal with this inequality. First, the government comes, takes money from you, and gives it to me. While you are probably comfortable with some level of taxation for the public good, you will eventually start to defend your hard-earned wealth, and you will always view yourself as more deserving than those who were unable to earn their own money.

  “Second, I can beg you for money, much as the homeless still do on the streets of major cities all over the world—and as my brother did when he left our village for New Delhi. When you give me your pocket change, it makes you feel good, but not me, as I have surrendered my dignity to your begrudging graciousness.

  “The third form of inequality leveling is for you to give substantially, of your own volition, to organizations that help people like me. True philanthropy out of compassion is uplifting for everyone. But even if the richest person in the world distributed all their wealth, everyone on Earth would only get a one-time payment of $15. That’s not going to solve anything. In addition, a lot of philanthropy goes to organizations that address symptoms but not root causes.

  “That’s why I applaud those who choose the fourth path, who give their wealth strategically to people, businesses and organizations that are attacking the root causes of problems, and that create technologies that lift up all of humanity. This creates leverage that multiplies the impact of their philanthropy.

  “This started over a hundred years ago, with the Carnegie Foundation funding libraries. And of course, we have many modern examples starting in the 2000s, with Gates, Skoll, Omidyar, Schmidt, Zuckerberg, and others. Unfortunately, we have almost no corporations following the same model. We need our extremely wealthy citizens and firms to adopt the fourth way, to look for a return to humanity instead of a return on investment. Then income inequality becomes a tool for solving problems instead of a problem to be solved.”

  Jake raised an eyebrow. “Well, that certainly sounds good, Sara—but why do you think this is possible?”

  Sara’s smile broadened. “I’m an optimist when it comes to the human heart and spirit, Jake. The behavior of the wealthy is driven by cultural and social constructs that exist only in their minds. Marcus buys a yacht, so Wei buys a bigger yacht. Prema makes a killing in derivatives, so everyone else piles on. People make many decisions by asking, what would someone like me do? If they see more and more examples of people investing in social entrepreneurs—people who seek to maximize return to humanity rather than return on investment—they will change their behavior, because it has simply become what wealthy people do. And they will feel happier because of it. It has been shown time and time again that vast wealth does not bring happiness. Giving and helping others is the surest way to a happy life.”

  Jake said, “You’ve talked a lot about this idea of a basic income guarantee. This has been kicking around for a long time without getting any traction outside of a few Nordic countries and a small province in China. Can you explain how and why this would work?”

  “It’s very simple. Every citizen age eighteen and over gets a payment every month. This is enough to provide a decent life, though perhaps not a comfortable one. This is their money, with no restrictions. They get to spend it on whatever they think will bring them the most value. Any money they earn is on top of this basic income.”

  “But in the U.S. this would cost trillions of dollars. How would you pay for it?”

  “This would indeed be expensive, but there are many sources of funding. Every country will need to use its own legislative process to find solutions, but I can describe some options. First, this can replace most existing social programs, so all that spending would be converted to basic income. Second, since the primary motivation for this is technologically-based unemployment, it makes sense that companies would partially replace the salaries they used to pay with a value added tax as they automate. Third, there are a variety of tax expenditures in the form of deductions and subsidies that could be eliminated. Fourth, in the spirit of taxing the things you want to discourage, a small financial transaction tax
, or tax on idle money not in productive use, would provide significant funds and reduce the frenzy of money chasing after more money with short-term trading. And fifth there probably would be some modest increase in tax rates for the wealthy.”

  “But wouldn’t the wealthy also get the basic income?” Jake asked.

  “Yes, it is universal, everyone gets it.”

  “But why would you give money to the wealthy who don’t need it?”

  “Well as I said, they will most likely end up paying much more than their basic income in additional taxes. Here in the U.S. I believe there is a standard deduction for all tax payers. No one seems to complain that the wealthy get to take the standard deduction. This is the same principle.”

  “Well it’s an interesting idea, Sara,” said Jake. “But it sounds like this would create a lot of winners and losers. It’s not possible for it to be win-win for everyone. And it touches some real political third rails. Solutions like that have never gotten through Congress.”

  “I disagree, Jake. While tens of millions of people will have more money, and a few million people with a good deal of money will have somewhat less, everyone wins, because the economy survives. People can live stable lives, and we’ll create opportunities for ever more innovation and ever greater human happiness.

  “We need to change our mindset from maximum employment to maximum happiness, because maximum employment is simply not achievable. Each society and each person may define happiness measures differently, but happiness must be achievable when a large percentage of the population is not working in a traditional job. They will work, because the vast majority of people will not be satisfied just sitting around. But they won’t be selling their labor any more in a job. They’ll work taking care of their family, by volunteering in their community and around the world, by contributing to open source projects, by participating in the sharing economy, and in creating designs, art, entertainment, or objects that others want to buy.