
Sheepdog arrived at the office, pretty hungover, and he must have slept hard because one of his eyes seemed to be permanently out of focus for the day. He decided to work through it. After grabbing his first coffee, he dove into his terminal and immediately opened the clip of the Bowler Hat man and the ghost he was meeting with. It didn’t matter which angle he chose, which AI assisted with the reconstruction or image processing, the data for the ghost simply didn’t exist. Res wasn’t in the office today so he had to tackle it alone. It wasn’t that big of a problem because she had already asked the questions he first asked when he stumbled across and essentially became obsessed with solving this mystery. The camera hardware checked out, software was up to date, and he was at an impasse. How do you create data where there is none, or find out what was removed and how?
He checked the time stamp for the footage and made a note of the date and time of day. He searched the Splicer archives for any other instances of the Bowler Hat man in that area and ran into the retention wall, but not before finding a similar clip 2 months prior to what he was looking at. The footage might as well have been identical, because as he loaded the older clips, he had the exact same problem. Limo arrives, Bowler Hat man gets out, shakes hands with nothing, gets back into his car and drives away. Obviously, it was some kind of scheduled transaction, and since he had already identified the man and his car, he knew it was one of their own clients. Frank, a very early adopter. This made Sheepdog even more suspicious. If he was such an old client, and there were at least 2 instances of him meeting a ghost, why didn’t his AI, Genesis, pick up on this and sound the alarm? As far as he knew, AI weren’t breaking rules or forming their own ideas about morality nor bending the rules for their monitoring. How could Genesis not recognize this gap in coverage as a threat? Something was wrong at a fundamental level, he felt. And that sense of dread could easily infect his concepts of how the organization at large was providing the protection these clients were paying for. This sense of dread and unease led him to an unusual request. He needed to conduct field research in that area.
He stepped into the manager’s office and briefly discussed the issue with him. The manager asked Sheepdog what he planned to do, and how he would do it. Sheep outlined a quick plan using on-the-ground testing hardware fitted neatly in a backpack. Your usual radio scanners, frequency detectors, jammers, and other penetration testing tools. He wanted to bring everything he could to the site to test everything, visible and invisible, ruling nothing out. The manager agreed to let him check it out on two conditions.
One, he didn’t raise any suspicions, and two, he wouldn’t interrupt the standard monitoring deployed at the site. Sheepdog agreed and changed into a generic technician’s outfit before cramming his backpack full of specialized hardware. He would leave no stone unturned, and he would do it without the cover of a service vehicle.
Sheep rode the monorail to the intersection, got off and got to work. First, he scanned for any unusual localized radio spectrum frequencies. He was looking for a bubble, something focused and small aimed at the site. Running through radio wave frequency blocks, his device turned up nothing unusual. Going on the offensive, he ran a Sendai 9 attack platform to attempt to interfere with anything wireless in that location. The devices easily routed around the localized attack by performing channel hopping and other defensive measures designed to overcome noise. Nothing was working in Sheep’s toolkit. He thought for sure the brand-new Sendai 9 would have a noticeable impact to all the radio signals floating around in the air within a 30-foot radius, but there seemed to be no service disruptions at all.