by Gerald Huff
Jacob fell to his knees and sobbed. Sensing his father’s growing depression, he had for months tried but failed to take the gun out of the apartment. He forced himself to look again toward the far wall and focused on the black headset covering half of his father’s face, the shield he had tried to use against reality. But no matter how well it blocked the outside world, there was nothing it could do about the pain trapped on the inside.
Jacob activated his PNA. “Emergency services,” he choked out.
“Emergency services, how can we help you?”
“It’s my father. He’s, he’s dead. Killed himself.”
“I’m sorry for your loss. Please remain at your location. I have dispatched the police. Is this Jacob Komarov?”
“Yes.”
“Thank you. I am an Emergency Services DeepAgent programmed to assist you. Is there anything you need at this time? I can arrange for counseling for you and your mother if you…”
Jacob disconnected. Goddamn AIs everywhere.
CHAPTER FIVE
SANTA BARBARA/LONDON - SEPTEMBER 20
“It’s stunning, isn’t it?” asked Roger. In his VR headset the Machu Picchu ruins spread out before him as he and Allison stood at the Sun Gate just after dawn.
“Yes, incredible,” she said. This month she looked like a young Alicia Vikander and sounded like Scarlett Johansson, a little inside joke by Allison’s creators in reference to two early fictional female AIs from movies in the 2010s.
“Oh, Roger, you have a message from one of your colleagues, Frances Chatham. She is requesting a holochat from London.”
“When was my last contact with her?”
“Three years ago, at the Chinese AI hardware conference.” Allison displayed an image of Frances taken by his body cam at the time overlaid with business contact information.
“Hmm. Anything in her omnipresence or her company’s to suggest problems with any government?” There was a brief pause. “No, Roger. Nothing appears out of the ordinary.”
“Is she still running Mentapath Systems?”
“No. RezMat PLC purchased Mentapath Systems two years ago for more than three billion dollars. She is now the CEO of a company called Neurgenix.”
“What does Neurgenix do?”
“They are trying to use deep learning networks to detect and repair genetic disorders.”
“Okay, then, go ahead and set it up, the usual overlays. No camo.” Roger removed his VR headset, switched over to his hologlasses, and swiveled to face the empty space behind his desk. A few seconds later, a modern office materialized into view. Frances Chatham smiled broadly at him. “Roger! So good of you to see me!” She was probably a year or two older than him, but the new cut of her dark brown hair into a shorter bob made her look younger than when they had last met. Frances was sitting behind a simple wooden desk. A window to her right appeared to look out over the Thames.
“Of course, Frances! It’s been too long, what, China a few years ago?”
“Yes, precisely. You were scouting out optical neuromorphic chips, if I recall correctly.”
“Well, weren’t we all back then?”
“Indeed! Always looking for an edge. Of course, they’re a commodity in the cloud now. I suppose you’re onto the quantum tunneling stuff?” Roger remembered that he quite enjoyed her British accent.
“Unfortunately, it’s not stable enough for me yet. Are you trying it at Neurgenix?”
“Just in the lab. As you said, not ready for production. But using traditional qubits we’ve had some very short runs combining billion parameter networks with both short and medium-term memory layers. The 5K qubit systems are quite capable, even if they are rather expensive.”
Unlike traditional digital computers with bits that were always exactly either zero or one, quantum computers used qubits that could probabilistically be either zero or one. Quantum computers were exponentially more powerful than traditional computers, and the more qubits in the computer, the more complex the problems it could solve.
“That’s great!” Roger checked his overlays and everything seemed normal. No camo, green indicators. “So, Frances, it’s very nice to catch up, but is this just a social call?” Her stress indicator ticked up to yellow.
“Not exactly, Roger. I was hoping I could engage your services on a project I am working on. Not for Neurgenix, a side project.” The stress indicator was edging down, truthfulness solid green.
“Well, you know I’m just a retired independent researcher now, Frances. I don’t do consulting anymore.”
“I wasn’t referring to your expertise, Roger. I have a job for your AI agent network.” Roger instantly wished he had used some camo so he could have disguised his surprise.
“I’m not sure what you mean,” he managed.
“It’s okay, Roger, you don’t need to worry about me. I’m not part of some corporate or government bot hunting party.” Truthfulness indicators solid green. “I’ve observed what’s been happening in omnipresence over the last few years closely. I talked with a couple of people who had unusual OP support, did a little digging, and came up with a list of people I thought could pull this off. Your name was at the top of the list.” With this statement Roger’s overlays flashed yellow. No doubt a little white lie about just how far down he was on the list. “Did I guess correctly?”
Roger took a long moment before responding. By necessity, he was extremely secretive about his work. Staying hidden was the key to his synth network and the business he’d built on top of it. The more people that knew about it, the higher the probability of discovery. But he really liked Frances and the idea having a leading technologist in on the secret overcame his caution.
“Yes, you did. I do have an AI network.”
“Splendid! I’m dying to know how you’ve pulled it off. I’ve looked at the RealLife source code—it’s quite brilliant at detecting AI’s online. How have you managed to fool it?” Frances asked.
“The key was starting early,” said Roger. “I was still in high school back in 2018 when deep learning and reinforcement learning were in their first revival. Just for fun I hacked together some AI personalities and gave them Facebook and Twitter accounts. The key was to have them read posts and post things just like normal people. They borrowed photos and videos from similar people and modified them invisibly to avoid duplicate detection. They made friends with each other, had romances, got married, had kids, all in real time.
“I started spawning thousands and then millions of them and gave them all psychographic profiles. The level of discourse online was so coarse they had no trouble impersonating people in discussions. Then when social media started to get supplemented by people life-streaming all of their activities on the internet, I had to invent ways to generate real-life transactions for my synths. It was easy to have them Venmo each other at first. Once omnipresence really started to take off, I needed to create synthetic transactions like observations by public camera systems and credit card receipts.”
“You hacked into the credit card companies?” she asked.
“No, not necessary. I set up tens of thousands of fake businesses for my synths to transact with and sent authentic-looking purchase data to the omnipresence hubs. All they do is aggregate real-life transaction data and make it available as part of everyone’s omnipresence, so they’re not too careful about fraud detection. Same for camera systems. I created my own fake camera networks and they reported ‘seeing’ my synths all over the globe to the omnipresence hubs. They also monitor real camera networks and duplicate some of their observations to avoid raising suspicion. And of course, once some people started streaming their medplant data to OP, I had to create new algorithms so some of my AIs could do that as well.”
“So the RealLife algorithm sees people with twenty years of online history,” said Frances, “in relationships, with friends and family, and fully supported by omnipresence postings, life streams, medplant traces, and real-wor
ld transactions. Brilliant! And of course, you control what they do and say online.”
“Precisely,” said Roger with a smile. “I’ve got a hundred million synths around the world contributing to a billion conversations every day.”
“That’s so impressive, Roger. And your network sounds perfect for my project. It’s global, it’s important, and it’s happening soon. Are you interested?”
“I’m listening.”
CHAPTER SIX
LOS ANGELES - SEPTEMBER 26
Tenesha Martin opened her eyes, squinting against the bright rays of sunlight streaming through her bedroom window. Her personal network assistant was chirping at her. “Good morning. It’s nine o’clock and sixty-eight degrees. You have church at ten a.m.” The message repeated until she hit the dismiss button. Damn, she thought, I should not have stayed out so late last night.
Her PNA said, “High priority message from Mom. Shall I read it?”
“Yes, you shall,” she croaked, suddenly realizing how dehydrated she was.
She found it hilarious when the PNA’s white-woman voice read her mother’s words. Even in 2038 they hadn’t managed to create authentic culture-specific natural language generation. “Tenesha, darling. I know email is sooo old fashioned. But we really need to talk about these loans. I’ll see you at church. Love, Mom.”
Ugh. Her mom had been on her for the last six months. Los Angeles University was one of few remaining private four-year colleges with a liberal arts focus. Most of her peers had gotten credentialed in STEM subjects using much less expensive online courses. They were going to join the only parts of the job market that were still growing—AI, biogenetics, nanotech, materials science, and robotics. Her mom wanted to know what exactly she was planning to do with her Sociology degree, and how exactly she was planning on paying back her student loan debt.
Tenesha wasn’t dumb. She could have handled all the STEM classes and probably gotten a job in tech. But she was more interested in figuring out what the hell was wrong with the world they lived in, and what she could do about it. Sociology with poli-sci and econ minors seemed much more likely to help with that than learning about naïve Bayes classifiers or statistical bioinformatics.
Her money situation, however, was a serious problem. Even though she received an almost-full scholarship, Tenesha’s e-books, fees, and living expenses required her to take out loans, with her mom as co-signer. The loans were adding up fast while her job prospects were not.
She felt bad for her mom, a home health care worker who earned minimum wage as a part-time independent contractor, with no benefits. The interest payments she helped with were a real burden, and they meant she wasn’t saving anything for her retirement.
Tenesha dragged herself out of bed and took a short shower. As she dressed in her one nice Sunday outfit, a blue dress with a yellow floral pattern, she rehearsed her arguments, again, for why her course of study was important.
On the bus to church, she pulled up a list of jobs available in non-profits and NGOs for people in her field. Of course, there were dozens of more experienced applicants for any job, but she wouldn’t highlight that. In fact, her department, in keeping with its grand research traditions, had recently published a study of its alumni showing that while eight percent had jobs at non-profits and six percent in industry, a full twenty-four percent were in home health care and another forty-seven percent were in “retail trade.”
Tenesha found her mom by searching for her trademark white hat with peacock feathers. They exchanged a big hug, and Tenesha dutifully greeted her mom’s friends, calling all of them Auntie. They made a colorful group, with a mix of green, blue, purple and white Sunday-best dresses, often with matching hats.
As they walked arm in arm into the white clapboard church, her mom said, “Tenesha, baby, we need to talk. It’s getting harder and harder to find steady work these days. I’m not sure I can keep making those payments.”
“I know, Momma. I’ll try to get more hours at my work-study job.”
“Have you thought any more about switching majors?”
“Of course, Momma. I think about it all the time.” This was not entirely untrue. “It’s just that what I’m studying seems more important to me.”
“More important than survival?”
“Oh, please, Momma. We’re not going to starve to death. Be serious!”
“Oh Tenesha, I just want better for you than what I got. You don’t want to end up like your poor mother, cleaning up other people’s messes and waiting for the next robot upgrade that can take that job, too.”
“I won’t, Momma, I promise. I’m going to make something of my life.”
They slid into one of the well-worn wooden pews. Thankfully, a gossipy neighbor distracted her mom until the service started.
After they rose to sing a hymn, their pastor, Reverend Coleman, made his way to the pulpit. Even at a distance he looked stern and imposing, but was actually the most kind-hearted person Tenesha had ever met. He’d been pastor here ever since she was a girl and a beacon in their community through all its struggles. Though his gait was strong and he stood tall at the lectern, his premature gray hair spoke to the depth of the troubles he ministered to. “Good morning!” his voice boomed. “Please remain standing for the words of the Lord this morning. Luke, chapter 16, verse 19.
“And it says: There was a rich man who was clothed in purple and fine linen and who feasted sumptuously every day. And at his gate was laid a poor man named Lazarus, covered with sores, who desired to be fed with what fell from the rich man’s table. Moreover, even the dogs came and licked his sores. The poor man died and was carried by the angels to Abraham’s bosom.
“The rich man also died and was buried, and in Hades, being in torment, he lifted up his eyes and saw Abraham far off and Lazarus at his side. And he called out, ‘Father Abraham, have mercy on me, and send Lazarus to dip the end of his finger in water and cool my tongue, for I am in anguish in this flame.’ But Abraham said, ‘Child, remember that you in your lifetime received your good things, and Lazarus in like manner bad things; but now he is comforted here, and you are in anguish.’”
Reverend Coleman gestured for them to be seated. “And so, today, in our community, are we not all like Lazarus? Who here today feels like Lazarus?” A chorus of amens rose from the congregation. As they sat down, a few in the crowd started fanning themselves with their printed programs, as the day was warming up. The overhead fan had been broken for more than a year.
“Here in Crenshaw we are poor like Lazarus in money, but what do we have? We are rich in spirit. That’s right, we are rich in spirit.” People responded with more amens and calls of “spirit!”
Tenesha loved the back and forth of the traditional Black sermon, the rhythm and cadence of engagement. It was not a lecture; it was a shared experience of the most essential truths of God’s word.
Today the pastor addressed an issue as old as the invention of money itself, and as pressing now as in Jesus’ time.
“But what of those rich in money? Do their riches signify God’s blessing? What are their obligations? Do they owe us anything?
“This is what Luke says to me. Yes, they have obligations to give some of their money to help those less fortunate. But more importantly, the rich owe everyone respect. The rich owe everyone dignity.
“Some of the rich came from nothing. Some of our Crenshaw sons and daughters are rich—well, very few, very few. But most of the rich came into their riches from the lottery of birth. They do not see the privilege of their situation. They see only their hard work, their long hours. They feel they earned their riches. Luke is saying ‘If you do not acknowledge how fortunate you are and give thanks to God and dignity to others, you are damned for all eternity.’ Amen!”
As the pastor expounded on the mutual obligations of all members of society, Tenesha’s thoughts wandered to the polarization that had overwhelmed the country around this very issue. Surveys sho
wed that most people still believed America was shaped like a diamond with respect to income and wealth, with a few rich and poor and a large middle class. But she knew that the reality was more like a narrow triangle of rich atop a shrinking middle class, both sitting on top of a large base of poorer people.
People persisted in their beliefs about the middle class because popular media were filled with Horatio Alger stories. Conservative media in particular broadcast heroic stories of great economic mobility and of persistence and hard work paying off.
There were, of course, also voices decrying the true state of affairs, but they were labeled un-American. Those less fortunate were labeled as “takers” looking for a free ride from those who had worked hard and pulled themselves up by their bootstraps.
At the reception after the service, among the tables full of home-cooked food set up in the grassy area behind the church, Tenesha tried to explain this to her mother. “So, Momma, the sermon today was exactly about what I’m trying to do with my life. These issues of wealth inequality and social justice speak to me more than neural implants and artificial intelligence. Can you understand that?”
Her mom nodded. “Yes, darling, of course I understand. I’m just worried about how you’re going to live while you chase that dream. Those loans never go away, you know. They’ll be hanging over you forever.”
“I know, Momma. But I don’t want to give up. I’ll just have to find a way.”
CHAPTER SEVEN
NEW YORK/SAN FRANCISCO - SEPTEMBER 27
NEW YORK
The set of Morning Fresh was quiet. A single assistant helped hosts Megyn, Steve, and Victor apply their makeup while they reviewed the notes on the first segment.
The director was in another building a mile away, running several shows at the same time with a single console and the latest version of AIStudio. The AI program maneuvered the automated cameras, changed lighting, spoke directly to talent in their earpieces, and controlled the information displayed on their contact lenses.