When I finally figured all this out, I was furious with Julia for not telling me what was going on. For making me worry. But of course, she was diseased. And there’s no point in being angry with her now.
Eric’s MP3 player was cut by gamma assemblers, the same way the cars in the desert were. And just as the MRI was. For some reason the gamma assemblers cut memory chips and leave central processors alone. I haven’t heard an explanation why. There was a swarm in the convertible with Julia that night. It had come back with her from the desert. I don’t know whether she brought it intentionally or not. The swarm could collapse into nothing, which is why Eric didn’t see anything when he went out to the car to look. And I wasn’t sure of what I saw when she pulled away, which was reasonable enough. The swarm was probably catching the light in odd ways. In my memory, it looked a little like Ricky, but it was probably too soon for the swarm to be taking on appearances. It hadn’t evolved that much, yet. Or maybe I just saw an indistinct shape, and in my jealousy I imagined it to be a person. I don’t think I made it up, but maybe I did. Ellen thinks I might have. After her car crashed, Julia called for the cleanup crews. That’s why they were there on the road late that night. They were waiting to go down the hill and clean up the site. I don’t know what caused the crash itself, whether it was something to do with the swarm or whether it was just an accident. There’s no one to ask about it now.
The facility in the desert was entirely destroyed. There was enough methane in the main laboratory to produce a fireball in excess of two thousand degrees Fahrenheit. Any biological materials would have been incinerated. But I still worry. They never found any bodies in the ruins, not even skeletons.
…
Mae took the bacteriophage to her old lab in Palo Alto. I hope she made them understand how desperate the situation is. She’s being very quiet about their reaction. I think they should put the phage into the water supply, but Mae says the chlorine will take it out. Maybe there should be a vaccine program. As far as we know, the phage works to kill the swarms. Sometimes I have ringing in my ears, which is a worrisome sign. And I feel a vibrating in my chest and abdomen. I can’t tell if I am just paranoid, or if something is really happening to me. I try to keep a brave face for the kids, but of course you can’t fool kids. They know I’m frightened.
The last mystery to be cleared up was why the swarms always returned to the laboratory. It never made any sense to me. I kept worrying about it because it was such an unreasonable goal. It didn’t fit the PREDPREY formulations. Why would a predator keep returning to a particular location?
Of course, in retrospect there was only one possible answer. The swarms were intentionally programmed to return. The goal was explicitly defined by the programmers themselves. But why would anybody program in a goal like that?
I didn’t know until a few hours ago.
The code that Ricky showed me wasn’t the code they had actually used on the particles. He couldn’t show me the real code, because I would have known immediately what had been done. Ricky didn’t ever tell me. Nobody ever told me.
What bothers me most is an email I found on Julia’s hard drive earlier today. It was from her to Ricky Morse, with a CC to Larry Handler, the head of Xymos, outlining the procedure to follow to get the camera swarm to work in high wind. The plan was to intentionally release a swarm into the environment.
And that’s exactly what they did.
They pretended it was an accidental release, caused by missing air filters. That’s why Ricky gave me that long guided tour, and the song and dance about the contractor and ventilation system. But none of what he told me was true. The release was planned. It was intentional from the beginning.
When they couldn’t make the swarm work in high wind, they tried to engineer a solution. They failed. The particles were just too small and light-and arguably too stupid, too. They had design flaws from the beginning and now they couldn’t solve them. Their whole multimillion-dollar defense project was going down the drain, and they couldn’t solve it. So they decided to make the swarm solve it for them.
They reconfigured the nanoparticles to add solar power and memory. They rewrote the particle program to include a genetic algorithm. And they released the particles to reproduce and evolve, and see if the swarm could learn to survive on its own. And they succeeded.
It was so dumb, it was breathtaking. I didn’t understand how they could have embarked on this plan without recognizing the consequences. Like everything else I’d seen at Xymos, it was jerry-built, half-baked, concocted in a hurry to solve present problems and never a thought to the future. That might be typical corporate thinking when you were under the gun, but with technologies like these it was dangerous as hell.
But of course, the real truth was more complicated. The technology itself invited the behavior. Distributed agent systems ran by themselves. That was how they functioned. That was the whole point: you set them up and let them go. You got in the habit of doing that. You got in the habit of treating agent networks that way. Autonomy was the point of it all. But it was one thing to release a population of virtual agents inside a computer’s memory to solve a problem. It was another thing to set real agents free in the real world. They just didn’t see the difference. Or they didn’t care to see it.
And they set the swarm free.
The technical term for this is “self-optimization.” The swarm evolves on its own, the less successful agents die off, and the more successful agents reproduce the next generation. After ten or a hundred generations, the swarm evolves toward a best solution. An optimum solution. This kind of thing is done all the time inside the computer. It’s even used to generate new computer algorithms. Danny Hillis did one of the first of those runs years back, to optimize a sorting algorithm. To see if the computer could figure out how to make itself work better. The program found a new method. Other people quickly followed his lead. But it hasn’t been done with autonomous robots in the real world. As far as I know, this was the first time. Maybe it’s already happened, and we just didn’t hear about it. Anyway, I’m sure it’ll happen again.
Probably soon.
It’s two in the morning. The kids finally stopped vomiting. They’ve gone to sleep. They seem to be peaceful. The baby is asleep. Ellen is still pretty sick. I must have dozed off again. I don’t know what woke me. I see Mae coming up the hill from behind my house. She’s with the guy in the silver suit, and the rest of the SSVT team. She’s walking toward me. I can see that she’s smiling. I hope her news is good.
I could use some good news right now.
Julia’s original email says, “We have nothing to lose.” But in the end they lost everything-their company, their lives, everything. And the ironic thing is, the procedure worked. The swarm actually solved the problem they had set for it.
But then it kept going, kept evolving.
And they let it.
They didn’t understand what they were doing.
I’m afraid that will be on the tombstone of the human race.
I hope it’s not.
We might get lucky.
Bibliography
This novel is entirely fictitious, but the underlying research programs are real. The following references may assist the interested reader to learn more about the growing convergence of genetics, nanotechnology, and distributed intelligence.
Adami, Christoph. Introduction to Artificial Life. New York: Springer-Verlag, 1998. Bedau, Mark A., John S. McCaskill, Norman H. Packard, and Steen Rasmussen. Artificial Life VII, Proceedings of the Seventh International Conference on Artificial Life. Cambridge, Mass.: MIT Press, 2000.
Bentley, Peter, ed. Evolutionary Design by Computers. San Francisco: Morgan Kaufmann, 1999.
Bonabeau, Eric, Marco Dorigo, and Guy Theraulaz. Swarm Intelligence: From Natural to Artificial Systems. New York: Oxford Univ. Press, 1999.
Brams, Steven J. Theory of Moves. New York: Cambridge Univ. Press, 1994.
Brooks, Rodney A. Cambrian Intelligence. Cambridge, Mass.: MIT Press, 1999.
Camazine, Scott, Jean-Louis Deneubourg, Nigel R. Franks, James Sneyd, Guy Theraulaz, and Eric Bonabeau. Self-Organization in Biological Systems. Princeton, N.J.: Princeton, 2001. See especially chapter 19.
Caro, T. M., and Clare D. Fitzgibbon. “Large Carnivores and Their Prey.” In Crawley, Natural Enemies, 1992.
Crandall, B. C. “Molecular Engineering,” in B. C. Crandall, ed., Nanotechnology, Cambridge, Mass.: MIT Press, 1996.
Crawley, Michael J., ed. Natural Enemies: The Population Biology of Predators, Parasites, and Diseases. London: Blackwell, 1992.
Davenport, Guy, tran. 7 Greeks. New York: New Directions, 1995.
Dobson, Andrew P., Peter J. Hudson, and Annarie M. Lyles. “Macroparasites,” from Crawley, Natural Enemies, 1992.
Drexler, K. Eric. Nanosystems, Molecular Machinery, Manufacturing, and Computation. New York: Wiley & Sons, 1992.
—. “Introduction to Nanotechnology,” in Krummenacker and Lewis, Prospects in Nanotechnology.
Ewald, Paul W. Evolution of Infectious Disease. New York: Oxford Univ. Press, 1994.
Ferber, Jacques. Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Reading, Mass.: Addison-Wesley, 1999.
Goldberg, David E. Genetic Algorithms in Search, Optimization and Machine Learning. Boston: Addison-Wesley, 1989.
Hassell, Michael P. The Dynamics of Competition and Predation. Institute of Biology, Studies in Biology No. 72, London: Edward Arnold, 1976.
Hassell, Michael P., and H. Charles J. Godfray. “The Population Biology of Insect Parasitoids,” in Crawley, Natural Enemies, 1992.
Holland, John H. Hidden Order: How Adaptation Builds Complexity. Cambridge, Mass.: Perseus, 1996.
Koza, John R. “Artificial Life: Spontaneous Emergence of Self-Replicating and Evolutionary Self-Improving Computer Programs,” in Langton, ed., Artificial Life III.
Kelly, Kevin. Out of Control. Cambridge, Mass.: Perseus, 1994.
Kennedy, James, and Russell C. Eberhart. Swarm Intelligence. San Diego: Academic Press, 2001.
Kohler, Timothy A., and George J. Gumerman. Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes. New York: Oxford Univ. Press, 2000.
Kortenkamp, David, R. Peter Bonasso, and Robin Murphy. Artificial Intelligence and Mobile Robots. Cambridge, Mass.: MIT Press, 1998.
Krummenacker, Markus, and James Lewis, eds. Prospects in Nanotechnology: Toward Molecular Manufacturing. New York: Wiley & Sons, 1995.
Kruuk, Hans. The Spotted Hyena: A Study of Predation and Social Behavior. Chicago: Univ. Chicago Press, 1972.
Langton, Christopher G., ed. Artificial Life. Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. VI. Reading, Mass.: Addison-Wesley, 1989.
Langton, Christopher G., Charles Taylor, J. Doyne Farmer, and Steen Rasmussen, eds. Artificial Life II. Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. X. Redwood City, Calif.: Addison-Wesley, 1992.
Langton, Christopher G., ed. Artificial Life III. Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. XVII. Reading, Mass.: Addison-Wesley, 1994.
Levy, Steven. Artificial Life. New York: Pantheon, 1992.
Lyshevski, Sergey Edward. Nano- and Microelectromechanical Systems: Fundamentals of Nano- and Microengineering. New York: CRC Press, 2001.
Millonas, Mark M.,”Swarms, Phase Transitions, and Collective Intelligence,” in Langton, ed., Artificial Life III.
Mitchell, Melanie. An Introduction to Genetic Algorithms. Cambridge, Mass.: MIT Press, 1996.
Nishimura, Shin I. “Studying Attention Dynamics of a Predator in a Prey-Predator System,” in Bedau et al., Artificial Life VII.
Nishimura, Shin I., and Takashi Ikegami. “Emergence of Collective Strategies in a Prey-Predator Game Model.” Artificial Life, V. 3, no. 4, 1997, p. 423 ff.
Nolfi, Stefano. “Coevolving Predator and Prey Robots: Do ‘Arms Races’ Arise in Artificial Evolution?” Artificial Life, Fall 98, V. 4, 1998, p. 311 ff.
Nolfi, Stefano, and Dario Floreano. Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines. Cambridge, Mass.: MIT Press, 2000.
Reggia, James A., Reiner Schulz, Gerald S. Wilkinson, and Juan Uriagereka. “Conditions Enabling the Evolution of Inter-Agent Signaling in an Artificial World.” Artificial Life, V. 7, 2001, p. 3.
Reynolds, Craig R. “An Evolved, Vision-Based Model of Obstacle Avoidance Behavior” in Langton, ed., Artificial Life III.
Schelling, Thomas C. Micromotives and Macrobehavior. New York: Norton, 1978.
Solem, Johndale C. “The Motility of Microrobots,” in Langton, et al., Artificial Life III.
Wooldridge, Michael. Reasoning About Rational Agents. Cambridge, Mass.: MIT Press, 2000.
Yaeger, Larry. “Computational Genetics, Physiology, Metabolism, Neural Systems, Learning, Vision, and Behavior or PolyWorld: Life in a New Context,” in Langton, ed., Artificial Life III.
The End