Dice (unloaded) seem to be a paradigm example of chance: when one rolls a die, one cannot know the outcome because it is supposed to be random. For example, if you roll a twenty-sided die, then there is an equal chance for any number to come up. If you roll the die 20 times, you would not be surprised if you did not roll every number on the die. If you rolled the doe 100 times, chance would indicate that you would roll each number 5 times—but it would not be shocking if this did not occur. But if you rolled 1,000 times or a million times, then you would expect the results to match the predicted probability very closely—that is, you would expect the law of large numbers to be in effect.

While dice provide a simple example of chance, the world is full of what seems to be chance. For example, diseases are presented in terms of chance: a person has X% chance of catching the disease and, if it can be fatal, they have a Y% chance of dying from it. Deadly dice of disease, indeed. While the actual method of calculating chance in the context of death by a disease is complicated, the very rough idea involves determining the number of people in a category who become infected and the number in that group who die. To use a made-up example, if 1 person out of every 100 dies, then the chance of dying from infection would be a scary 1%.

This estimate can be off for many reasons, but one obvious concern is that one is estimating probability based on the outcome. That this is a problem can be shown by imagining an artificial scenario in which you are given the results of repeated rolling of a die, and you are trying to figure out from that the type of die that is being rolled and whether it is weighted in some manner. You could, of course, make some reasonable inferences. For example, if the highest number you are given is a 30, you know that the die has at least 30 sides. Matters also become more complicated if you are not sure that a die is being rolled—you might be given numbers generated by some other means. The person giving you the numbers could select them to create the impression of chance—even though they are intentionally selected. One could, for example, create the impression that they are rolling a 20-sided die by picking numbers to create the expected results for such a die. A similar sort of thing could occur in the world, something that can be illustrated by the disease example.

Let us imagine two universes. Universe A is a random universe that has real chance and probability (whatever that might mean). In that world, there would be a metaphysical and metaphorical roll of the dice to determine outcomes that arise from chance. For example, a disease that had a 1% fatality rate would work like this (metaphorically): each infected person would get a roll with a d100 and if the result was a 01, then they would die. Thanks to the law of large numbers, if enough people got infected then this would work out to 1 in 100 people dying in this random universe. Naturally, smaller numbers will not match the 1 in 100 perfectly—but with a large enough number of infections the 1 in 100 will be achieved (oversimplifying things a bit). Now to universe B.

Universe B is not random—it could be a deterministic or pre-determined universe or whatever non-random reality you want. In this universe the disease kills 1 in 100 people, but this is not the result of chance. Out of every 100 infected people, there will be one who will die (this oversimplifies things a bit for the sake of the example). This is not due to chance since this is not (by hypothesis) a random universe. In terms of why it occurs, this will depend on the sort of non-random universe one has picked. For example, perhaps the universe is run by a god who has created the 1 in 100 death disease and has sorted out humans into groups of 100 using whatever standard the god has chosen.

From the standpoint of humans, this universe will (probably) appear identical to random universe A. After all, the samples people have will be imperfect and will create the impression that it is not a perfect 1 in 100 every time. As such, it will seem random. Unless, of course, humans can figure out how the 100 person groups work. One could imagine a short story based on this idea in which scientists find that a disease is always fatal to 1 person out of a group of 100 people and the 100 person groups are divided up by the X factor they find. But if humans do not sort out the grouping, then the non-random universe would seem random because of human ignorance.

We do not, of course, know what sort of universe we live in. Roughly put, this might be a random universe and a 1 in 100 chance is “rolled” with metaphysical metaphorical dice. Or it might be a non-random universe in which a 1 in 100 “chance” means that it is “set” to happen once out of every group of 100. Unless we can identify the groupings and get complete data, then we will never know what sort of universe we inhabit.

## Leave a Reply