All right, all right: it was cool math.
“Now do you see why I like information theory so much?” Kuroda said, his tone suggesting he was still trying to cajole her. “Hey, do you know John Gordon’s old story about the student of information theory on his first day at university?”
Anna said, “Not this one again!” but Kuroda pressed on undaunted.
“Well,” he said, “the student shows up at the departmental office and hears the professors calling out numbers. One would call out, say, ‘74!,’ and all the other professors would laugh. Then another would call out a different number, say, ‘812,’ and again everyone would laugh.”
“Uh huh,” said Caitlin.
“So the student asks what’s going on, and a prof says, ‘We’re telling jokes. See, we’ve all worked together so long, we know each other’s jokes by heart. There are a thousand of them, so, being information theorists, we applied data compression to them, assigning each one a number from zero through 999. Go ahead, try it yourself.’ And so the student calls out a number: ‘63.’ But no one laughs. He tries again: ‘512!’ Nothing. ‘What’s wrong?’ the student asks.
‘Why is no one laughing?’ And the kindly old prof says, ‘Well, it’s not just the joke — it’s how you tell it.’”
Caitlin found herself smiling despite herself.
“But one day,” Kuroda said, “the student was looking at a weather report for the far north and happened to exclaim the temperature: ‘Minus 45!’ And all the professors burst out laughing.”
He paused, and Caitlin said, “Why?”
“Because,” he replied, and she could tell by his voice that he was grinning, “they’d never heard that one before!”
Caitlin laughed out loud, and found herself feeling better, but her father said, “Ahem” — actually saying it as if it were an English word, rather than like a throat-clearing. “Might we get on with it?”
“Sorry,” said Kuroda, but he sounded like he was still grinning. “Okay, here we go…”
He used the technique he’d developed before to send freeze frames of the Jagster data to Caitlin’s eyePod, and from there to her implant. By trial and error, they found the right refresh rate to get what she was seeing to increment by just one step — just one iteration of whatever rule was governing the cellular automata as they changed from black to white or vice versa. She could now watch, frame by frame, at whatever playback speed she wished, as spaceships moved across her field of view, without missing any steps.
Kuroda had no way to filter out just the cellular automata from the Jagster feed, but Caitlin could do it with ease, simply by focusing on only a portion of the background.
“And,” he said, “speaking of Mathematica, Malcolm, do you have it?”
“Of course,” he said. “It should be accessible here. Let me…”
Caitlin heard them moving around, then, after a bit, Kuroda said, “Ah, thanks,” to her dad, and then, generally, to everyone, “Okay, let’s run the Zipf-plotting function.” Key clicks. “Of course, we’ll have to try a lot of different ways of parsing the datastream,” he continued, “to make sure we are isolating individual informational units. First, we’ll—”
“There!” interrupted her dad, actually sounding excited.
“What?” said Caitlin.
“Well, that’s it, isn’t it?” said Kuroda.
“What?” she repeated more firmly.
“You’re sure you’re concentrating on just the cellular automata?” Kuroda asked.
“Yes, yes.”
“Well,” he said, “what we’re getting as we plot them flipping from black to white is a lovely diagonal line — from the upper left to the lower right. A negative-one slope all the way.”
Caitlin lifted her eyebrows. “So there is information — real content — in the background of the Web?”
“I’d say so, yes,” said Kuroda. “Malcolm?”
“There’s no random process that can generate a negative-one slope,” he said.
“Le’azazel!” exclaimed Anna; it sounded like a curse word to Caitlin.
“What?” said Kuroda.
“Don’t you see?” Anna said. “A negative-one slope: it’s intelligent content on the Web in a place it’s not supposed to be — intelligence disguised to look like random noise.” She paused as if waiting for one of the men to supply the answer and, when they didn’t, she said, “It’s got to be the NSA.” She paused, letting that sink in. “Or maybe it’s comparable spooks elsewhere — Shin Bet, perhaps — but I’d bet it’s the NSA. We already know, from Hepting, that they muck around with the traffic on the net; it looks like they’ve found a way to package clandestine communications that move in the apparent noise.”
“What sort of content could it be, though?” asked Caitlin.
“Who knows?” said Anna. “Secret communiqués? Like I said, people have tried to use cellular automata before for data encryption, but nobody — at least not anyone who’s gone public — has ever worked out a system. But the NSA scoops up a lot of the top math grads in the US.”
“Really?” said Caitlin, surprised.
“Oh, yes,” said Anna. “It’s a real problem in the field of math academically, actually. Most of the best US grads in math and computer science either go to the NSA, where they work on classified projects, or to private-sector places like Google or Electronic Arts, where they do stuff that’s covered by nondisclosure agreements. God knows what they’ve come up with; it’s never published in journals.”
Kuroda said something that might have been a swearword of his own in Japanese, then: “She may be right. We should tread very, very carefully here, my friends. If this stuff in the background of the Web is supposed to be secret, those in power may take … steps … to ensure that it remains that way. Miss Caitlin, far be it from me to tell you what to do, but perhaps you could be circumspect about this topic in your blog?”
“Oh, no one pays attention to my LiveJournal. Besides, I flock — friends-lock — anything that I don’t want strangers to read.”
“Do what he says,” her dad said, startling her by the sharpness of his voice.
“The authorities could seize your implant and eyePod as threats to national security.”
Caitlin got down off the table. “They wouldn’t do that,” she replied.
“Besides, we’re in Canada now.”
“Don’t think for one second that the Canadian authorities won’t do whatever Washington asks,” her father said.
She wasn’t sure what to make of all this. “Um, okay,” she said at last. “But you guys are going to keep studying it, right?”
“Of course,” Dr. Kuroda said. “But carefully, and without tipping our hand.”
He paused. “It’s a good thing we’re doing a video conference with Anna; if this were text-based IM the authorities would already know what we’ve found. At least for now, video is a lot harder for them to automatically monitor.”
The full impact of what he and Anna were saying was coming to her. She turned her head toward Kuroda. “But what about our paper?”
“Eventually, Miss Caitlin, perhaps. But for now, the better part of valor is discretion.”
Chapter 30
Masayuki Kuroda had spent the rest of Saturday, and all day Sunday, working with Miss Caitlin, studying the cellular automata. But it was now Monday, the first day of October. Masayuki had been in Canada a week now. He missed his wife and his own daughter, and felt guilty that Hiroshi was having to cover his classes for him. But, still, he was entitled to a little time off while he was here, no? Besides, there was only so much he could do while Miss Caitlin was at school.
He took another bite of his roast-beef sandwich and looked around the kitchen. He didn’t think he’d ever get used to North American houses. A home this size would be almost impossible to find in Tokyo, and yet there were streets full of them here. Of course, the Decters obviously weren’t hurting for cash, but, still, with only Malcolm working, and with all the expensive equipment Caitlin had, they certainly couldn’t have a lot of disposable income left.