When two quantum particles are entangled, it can also be said they are “nonlocal”: their physical proximity does not affect the way their quantum states are linked.
“Be the best “you” that you can be! Sign up for MarkovLife today, and unlock your true potential! With MarkovLife’s patented DecisionPaths, live with confidence, knowing that your decisions will be the best of all possible worlds. Sign up today on your computer or mobile device and guarantee your best possible life!”
-MarkovLife ad, early 21st century
Things used to be so simple.
You weighed your options, with what little information you had, and you made a choice.
Sometimes it turned out well, sometimes not so well, but that was life. You couldn’t go back and change things. You could always keep second-guessing yourself with ‘what-ifs’. Keep yourself up at night, staring at the ceiling, asking yourself if you’d made the right choice. But you’d never really know how things might have been. Might be.
That all changed with MarkovLife. It was born out of some think tank project called Cassandra, trying to use math to predict the results of choices, or something like that. Apparently, one day someone had the bright idea to combine project Cassandra with quantum computing. I remember seeing articles when it first began, talking about “radically parallelized simulation” and “probabilistic evaluations”. Talking heads promised “an end to uncertainty” and you couldn’t go anywhere without hearing about it.
First, governments used MarkovLife to predict the best places to send humanitarian aid, predict natural disasters, that kind of thing. It actually worked; thousands of lives were saved.
Soon, MarkovLife was expanded, with agencies using it to determine what technologies to invest in, what policies to enact and so forth. It was hailed as the next and best tool to “advance the human condition”. MarkovLife was used more and more, for more and more tasks, eventually spreading to the public sector. For a small monthly fee, you too could make choices in absolute confidence.
Soon, no one made any decisions without asking MarkovLife.
Trying to decide whether or not to leave your job?
Should you get sandwiches, or pizza?
Swipe left or swipe right?
Everything became so simple. You just chose the recommended path for your best and brightest future. No messy dates, no indigestion, no unexpectedly shitty bosses. Sure, sometimes your “best” option wasn’t very good, but it sure wasn’t any worse than it had been before that. On that, everyone could agree.
And for a while, it was good.
Global happiness went up, standards of living increased, mortality rates dropped. Even technology advanced at an unprecedented rate. When you can accurately simulate billions of possible experimental outcomes from MarkovLife “Experiment Analysis SErvices”, it really cuts down on R&D time. The MarkovBuddy was built; a small brain implant, hooked into the global MarkovLIfe network, that made it possible to evaluate your decisions in real time, without a clunky cell phone. We were living a predictively-assisted golden age. A new breed of extreme sports even developed--unassisted decision-making. It seemed ludicrous to members of the older generations, but for people whose whole life had been a MarkovLife, making choices without knowing what might happen? It was almost unthinkable.
Thinking back on it, the collapse was inevitable. Almost no one thought about the downside to optimal decision making, and those who tried to warn us were ignored as alarmists. It turns out just because someone can choose the best of all possible worlds, it doesn’t mean that any of their worlds are very good. Of course, there was nothing in MarkovLife to balance out decisions for the whole, at least not inherently. It was a tool, a digital hammer. Sure, it could be used to predict what decision would be best for us all within some time frame, but it rarely was. And when a fast food worker and a billionaire take their best paths, whose do you think makes more of a difference?
People began to rely on their MarkovBuddies more and more. Everyone was performing at their best possible level, so each decision became increasingly important. Room for error became smaller, and smaller and soon failure to use MarkovLife for on-the-job-decisions was grounds for firing. With most people so close to the edge, and with community optimization a premium service, charity support dropped to almost zero. Governments tried to rebuild social safety nets as more and more people began to slip from “getting by” to “not”. Riots began, with MarkovBuddies being used by police and rioters alike. Public transportation ground to a halt in many cities, pushing more people over the edge. Trucks of food were ambushed and looted, causing shortages.
Eventually, we hit the tipping point.
A lot of us didn’t survive the collapse. Some people just didn’t have enough to make it through, even doing their best. Others panicked, abandoning MarkovLife and ignoring their MarkovBuddies, believing that it must have been a scam all along. Of course, they’d never made their own decisions before, so going it on their own didn’t last long. Others became predators, using their MarkovBuddies to take what they needed. Some of us banded together and pooled our collective resources and decision-making, to build small communities, protected by MarkovLife.
Of course, MarkovLife, their servers, power-generation, security, and mobile device infrastructure, even the ability to build more MarkovBuddies, all survived. The company had, of course, been making the best possible choices. Their resources just meant that their best possible decisions were better than everyone else’s.
So now we live day-to-day, but we have enough to get by. We try to make sure that we’re safe, that we have enough food, that we can improve things just a little bit, and maybe leave a better world behind for our children. And every time we make a choice, we use our MarkovBuddies. If we’re lucky, we’ll save enough to make sure that our children can get their own MarkovBuddies. We all want to be sure that our children can live with confidence and without MarkovLife, how else can we guarantee their best possible life?