Rule 34

anything: I’m not responsible for these deaths.” You shrug, then lean back in your well-upholstered command chair. “I assure you, they are nothing to do with me.” You look at Maryland. “Is your government . . . ?”

Maryland looks as if she’s swallowed a live toad. “We’re not in the remote-kill business these days. This isn’t the noughties: Congress would never stand for it.” Ever since Filipino Jemaah Islamiyah hackers pwned an MQ-9 Reaper and zapped the governor of Palawan with USAF-owned Hellfire missiles, the Americans have gone back to keeping a human finger on the trigger: not because a state governor from a foreign country was killed, but because of who was in the armoured limousine right behind him. (The prospect of having to utter the term collateral damage in the same sentence as President of the United States before a congressional enquiry had focussed a few minds.) “Where’s the attack coming from?”

“It’s not part of the original picture.” It’s uncomfortable to talk about. “To make IRIK look plausible, it was necessary to provide a haven for certain undesirable elements. They run botnets, of course, but their customers are . . . unclear. We had assumed the traditional, of course: spammers, malware vendors, child-labour sweat-shops providing teleoperator control of animatronic sex toys for paedophiles.” You clear your throat. “What we weren’t expecting: cheap grid computing for pharmaceutical companies solving protein-folding problems. A Chinese automobile company using a botnet to evolve the design of their latest car using genetic algorithms fed with data from consumer surveys. Artificial- intelligence researchers renting the same botnets that spammers rely on to train their spam filters. Who knew? It is a, a soup of virtual machines boiling out on the darknet, coordinated through channels that our targets operate from corrupted routers in the State Telephone Company hosting centres in Karakol. I don’t have the resources to trace them, in any event. We will shut them down when we spring the trap and snap their worthless necks, but until we are ready to close the honeypot, I cannot stop the attacks.”

“Twenty-four hours.” This from the delegate from Beijing, whose screen is an opaque black cube. “That is unacceptable.”

“I fail to see why. The operation is proceeding nominally.”

“The operation is out of control, Colonel. Sequestrating the assets of organized crime is acceptable. Creating a honeypot for international cybercrime in order to shut them down is acceptable. But sheltering murderers is not. There have been regrettable excesses. The younger brother of the chairman of a state party branch that I shall not trouble you with. The aunt of a Central Committee member. You must shut it down now—or we will.”

You grit your teeth. Your stomach churns: “It continues for twenty-four hours, and no more. The operation will conclude tomorrow, at twelve hundred hours, universal time, and not a second earlier.” Maryland and Brussels are opening their mouths: “We’ve got to let it run its course! If we don’t, the CDOs won’t be fully vested—the targets will not be bankrupted, but they will be annoyed with us.”

“They’ll be annoyed with you.” Brussels looks smug.

“Ah, no, I can see you misunderstand me. They’ll certainly be annoyed with me, but also with you, Francois, and you, Lorna, and you Li”—you stab a finger at Beijing—“because if any of you pull out of your side of the agreement prematurely, I will see to it that full details of this operation are published on the Internet, with all identifying names attached.” Your smile tightens. “Thank you for your help.” You stab a finger hard on the CALL TERMINATE icon before any of them have time to frame a reply, then curse them all for a donkey’s illegitimate get. “Fuck me, when will they learn?” You roll your eyes. “Fucking amateurs.” Jumped-up crime-control bureaucrats with delusions of special-operations grandeur.

You glance at your clock. It’s almost four in the afternoon, and the latest auction of national-debt futures leveraged against Issyk-Kulistan are due to close in an hour. The inflow is tapering off, as expected, but as long as the gangsters keep paying, there’s no reason to weld your wallet shut and go to the end game.

Eagle’s Nest had fucking better be pleased with this day’s work. You’re not sure how much more bullshit you can take.

ADAM: LOLspammers

You should have known it was too good to be true.

With twenty/twenty hindsight, the alarm bells should have started ringing three years ago, when Larry gave his presentation during that BOF breakout session on Network Assisted Crime Prevention at the Fourth International Conference on Emergent Metacognition. You can see him now if you put on your specs and tell your lifelog to retrieve him: enthusiastic, lanky, Midwestern.

“Realistically, we’re trapped between a rock and a hard place,” he explained to the room, hands moving incessantly as he spoke: “The trouble is, there are too many crimes. Three and a half thousand new offences were created in just ten years under one British government. The US Code is even worse— something like a third of a million distinct activities can lead to felony charges by some estimates. Nobody can be expected to keep track of that; it’s inhuman. But with the kind of filtering we’re having to apply to keep the communication channels open and relatively spam-free, it’s more than possible to envisage agent-based monitoring for signs of criminal intent.”

They’ve been keyword-filtering email for decades, looking for terrorist needles in a haystack. But what Larry proposed was different: trawling for patterns of suspicious behaviour online. Take, say, a disgruntled employee bitching about how they hate their boss online. That’s one thing. But if they start hunting the blacknets for templates for machine pistols and downloading VR training materials, that’s another.

“But what if we go a step further?” asked Larry. “Subjects who exhibit signature behaviours online pointing to potentially violent outbursts may not provide law enforcement with sufficient evidence to justify an arrest. But that’s no reason not to provide an agent-based intervention in the online space. Once ATHENA has a sufficiently large corpus of interaction patterns, we can use it to do behavioural targeting and apply inputs weighted to divert high-risk subjects towards less damaging outcomes. Or to indirectly flag them for police attention.”

Your typical disgruntled employee is a fizzing human bomb for some time before they go postal. Their social contacts are fraying, inhibitions against violence decaying: They’re muttering to strangers in bars, reading about serial killers and fantasizing bloody revenge by night. The police will never know until they explode with murderous intent. But the spam filters monitoring their communication channels will have everything they need to diagnose the downward spiral: From their increasingly disjointed mutterings to the logs of their incoming web surfing, the pattern’s all there. And with enough data, all correlations become obvious. But what Larry was proposing . . .

“We’ve had behavioural targeting ever since the nineties: ‘If you like product X, you’ll love product Y,’ because that’s what everyone else with tastes like you bought. We can configure ATHENA to apply the same sort of recommendation nudge to behaviour to bring the subject’s outputs back towards baseline. ATHENA’s already pretty good at discriminating human-content communications from non-metacognitive signals; can we take the discrimination further, reliably, and derive objective data about internal emotional states?”

You lean back in your office chair—it squeaks angrily under your weight—and stare at the dusty display case on the opposite wall.

“Say that again,” you say.

“I’m sorry, Dr. MacDonald; it’s been a big shock to all of us here . . . can’t quite believe it. The funeral’s going to be held next Thursday morning. I’m sure everyone will understand if you can’t make it—it’s a long way to come—”

Your fingers move, eyes unseeing, to open the log of your last discussion.

ADAM@Edinburgh GMT +01:00: I didn’t adjust the preferential weightings in the naive morality table. Did you?

LARRY@Cambridge MA GMT +05:00: Not me.

VERA@Frankfurt GMT -01:00: Do we have hysteresis here? There is feedback from the second-order outcomes-triggering network.

SALLY@Edinburgh GMT +01:00: I’ve been trying to get my head around the second-order table