By afternoon, Prophet was turning up all sorts of information. Snippets of conversation and pictures picked up by image sensors in vehicle, traffic, street, parking, private and satellite infrastructures indicated that the highly automated Prosthetic Device Production Center (PDPC) in my hospital was the focus of considerable attention.
Of particular interest was what appeared to be a chance encounter at a vehicle “KwickC” charging station between Dr. Shanti and a former Prophet Analytics supervisor, Dr. Clark Hallick during which both had entered the restroom area at the same time. In fact, I happened to remember Clark very well, as we had dated for a while way back in our pre-IPO days. But all the good looks in the world couldn’t blind me to Clark’s overbearing and selfcentered attitude. We had parted bitterly and he had left the company shortly thereafter. Now it turned out that he was leading a robotic learning optimization program at the hospital — and that air filtration sensors in the charge station lavatory had picked up molecules of something very unusual for such a venue: melittin.
Having acquired a huge amount of data regarding the potential perpetrators’ personalities, histories, and realtime activities, Prophet’s prediction engine began to zero in on probable scenarios. And the one that received the highest level of probability — with a 93 percent chance of realization — was exactly what began to unfold.
Late that evening, Hallick’s department apparently began preparations for a test to see if the hospital’s robotic vision systems and associated sensors could be hacked. According to official records, the test would be conducted two days later during the small hours of the night — in other words only shortly before my admission and treatment time.
Now, as I lay on the treatment table and Dr. Higgs examined the representation of my mitral valve on a swivel arm-based display, the outlines of an optimized prosthetic clip automatically took shape on the screen. He clicked a few virtual buttons on the screen’s interface, dispatching the dataset to the PDPC for production. Moments later a bright blue light on a nearby control panel began blinking, indicating that a custom-made prosthetic clip had arrived via pneumatic line.
“We’ll have you squared away in no time, Denise,” said Higgs reassuringly. “I’ll just give you a sedative…” He started to reach for a small, glowing dial attached to the catheter line that had been connected to my groin.
But before he could touch the dial I caught his hand. “Dr. Higgs, let me take a look at the prosthesis first,” I said. “Just open the pneumatic drawer and let me examine it with my smartphone.” The drawer opened and I pointed the phone at the tiny object.
The latest phones are designed to recognize objects — regardless of how unusual they may be — to catalogue them complete with price and location information. Specialized applications allow users to virtually “open” devices by interrogating their internet datasets to see, hear, analyze, or price-compare their inner parts, or to remotely control them. But equipped with Prophet technology, such a phone will look for anything that, based on previous knowledge, fits a predicted outcome.
A moment later, a warning appeared on the phone indicating that the PDPC had experienced a data outage prior to production of the prosthesis. And worse: the phone’s built-in laser diode spectrometer had found traces of melittin embedded in the prosthesis, indicating a potential time-release delivery mechanism.
“Good God!” Exclaimed Higgs. “With your medical history that would have…” “Exactly,” I said. “And nothing would have happened until well after my release from the hospital.”