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As an amateur who has interest in logic and mathematics I've been reading about the concept of different probability perceptions. I'd like to have your opinions over the subject below.

When it comes to probability assessment/comparison of two unlikely events does logic give us a single definitive and universal answer? Please take this question into account over the examples below.

The events in my question concern one astronomically unlikely and measurable hypotethical event (let's call this Event 1) and another unlikely hypotethical event for which its probability cannot be easily measured yet its nature is recognizable due to being exposed to similar ones. (lets call this Event 2, more detaled explanation follows below)

To illustrate what I mean over two examples:

Event 1 is the likelihood of having an uniform picture let's say a cat photo on a random pixel generator.

Suppose we have a random pixel generator which has 1920 x 1080 screen resolution with 24 bit colors. For each pixel on the screen we have a 1 in 10^14981179 chance of being set at the correct position to generate any image we can think of hence a cat picture. (2^24^1920 x 1080) We end up with an unfathomably low probability.

I am taking the liberty of calling Event 2 a likelihood extremely surprising for some but just usual news to many people. Take crimes for instance, unfortunately every day on the news we come across several crimes therefore we are exposed to a sample unlike Event 1. Let's take hypotethically person A is committing a serious crime i.e robbery (You can name it to increase the degree of surprisingness) and it is extremely unexpected due to its not so easily explainable nature (no obvious motivation and reason for such action, completely opposite character of the person, serious consequences etc. but note that there is nothing supernatural about the action)

For me almost anything that can occur in this world would have much higher probability than the event 1 which is absurdly improbable. Let alone the lifetime of our universe, mathematically millions of universe wouldn't be enough to see a uniform real cat picture on a random pixel generator even it shuffles the pixels every second.

However can a person find Event 2 less likely than Event 1 just because his experience and belief over the person who hypotetically commits the crime?

Do logic and maths tell us that likelihood comparison of these events are subjective therefore we cannot argue about the odds?

Is Event 2 a case which is impossible to measure its probability? Or regardless of the peculiarity of the person who hypotethically commits the crime is taking into account other similar cases (i.e same type of crime ratios over a certain period) sufficient to conclude that Event 2 has higher probability without any doubt ?

Thanks for reading so far. Lastly is there any specific branch or body of work that focuses on such probability and logic topics?

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  • Seems your detailed thought process above already solved most of your questions, you're just not sure if it's possible to measure E2's probability, and your penultimate section should satisfy such possibility... May 20 at 3:19
  • @Double Knot, would you be so kind to answer my questions in bold. Do you think for example likelihood comparison of E1 and E2 subjective and we cannot argue about the odds? Can you explain please? Thanks!
    – Geerts
    May 20 at 5:27
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    How can you be so sure as an objective fact that "... that Person A could be the last person on earth to commit such crime due to his character..."? Thus it's totally logical that Event 2 is more likely than Event 1 in terms of probability which can be interpreted both as objective frequency and subjective degree of belief, since the true posterior crime probability of E2 has to be within the confidence interval of the usual level of the stats and your shocking feeling is just a Bayesian update about that person... May 20 at 6:20
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    Re your above "Such person from the family is therefore someone who experiences first hand hard to explain nature of E2", the difficulty lies in the limitation of current psychology knowledge, some philosophers/neuroscientists even reject existence of psychology. Thus your shocking unbelievable emotion may not be objectively well founded. Indeed, sometimes even family members don't truly understand each other psychologically which actually occurs quite common as described in many ancient classic books such as filial piety sutra... May 20 at 19:59
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    Even you change person A to self, I'd rather still depend on stats since know thy self is extremely hard per the famous Greek Delphic maxim perhaps due to the similar limitation of folk (pseudoscientific?) psychology theory and also consider there're not that many people as denominator of your E2 probability compared to E1. But I speculate if one truly knows oneself such as attaining Buddhahood, then in such rare case E2 can be certain to be less than E1 as it can then be claimed infinitesimally approaching zilch. As reminded by Hegel your sense certainty is likely not a universal truth. May 25 at 2:18

2 Answers 2

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For very simple events, like particle interactions or dice rolls, we can derive quite rigorous models. Our intuition is often misleading about these cases, because while we recognise the cat is unlikely, we struggle with the idea a specific image of static is equally unlikely. We perform a 'chunking' process, where we merge many distinct states. We should understand thermodynamics like thus, with there being many similar equilibrium states like the static, and few with special properties, like the cat.

For more complex events where the parts or interactions are beyond being precisely modelled, we need Bayesian inference, where we begin with priors, or expectations. These can come from almost anywhere, we are only required to think of the best likelihoods we can. Then we adjust them over time.

It's important to understand all probability is based on a fantasy: counterfactuals. That is, we imagine the event could happen again from the same initial conditions. For simple cases, we can mimic the starting conditions closely enough, and prove this by statistical analysis. Bayesian reasoning can be used to predict complex systems, like the intentions of other humans. We know from the Dunbar Number our neocortex evolved primarily for predicting other humans, and gives us a cognitive bias towards narrating subjectivities. See: Is the idea of a causal chain physical (or even scientific)? Hume's Problem Of Induction shows us that in truth relying on the past as a guide is not a logical choice, but one derived from experience. Popper who dismissed induction's role in science, essentially argued science is about conjecture and criticism including by experiment, which fits with the Bayesian perspective.

So. Can you model the situation unambiguously? First approach. Should ve able to agree. Is the situation to complex to model completely, and unambiguously? All the computing power on Earth is limited to the quantum states of a lump of matter about the size of a tennis ball, so anything like biology that uses a substantial fraction of the available complexity, is far beyond what we can currently model explicitly. So we need conceptual chunking, and learning from experience, which will depend on framing and our past.

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  • Your insights are interesting. However with my limited mathematics I don't think I can model Event 2 unambiguously. Its likelihood indeed is hard to calculate, not straightforward like Event 1. That's why I've posted this question. Does the fact that there are seemingly similar cases for the Event 2 (robbery statistics) necessarily mean that it has to have higher likelihood than Event 1 which has infinitely small likelihood? Do you think it can be completely logical that Event 2 has less likelihood than Event 1? Please see the comments under the answer of 'tkruse' for the details.
    – Geerts
    May 23 at 12:24
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Psychology at least tells us that most humans are extremely bad at judging probability from observation, even for frequently occuring events. There are also biases like selective perception, selective memory, confirmation bias...

It's also difficult to objectively apply maths to model real world events, as any two mathematicians or statisticans can reasonably disagree on how reality should be modeled, depending also on the purpose of such an effort.

So there are pragmatic, psychological and political limitations at least to answer questions about mathematical properties of reality.

Regarding probabilistic predictions of the future, it is not possible to define one probabilistic prediction of a single event as correct. Assume a 1% chance of rain tomorrow, this is "true" both if tomorrow it rains or does not rain.

For methods of prediction, we can measure their usefulness by comparing them to outcomes over many events, but that does not make any single prediction correct or better. A wise man might much more often predict well the future than a fool, but the fool might still be right about the next day when the wise man is wrong.

Events need not be rare for this, rarity just makes it harder to compare the methods. But single predictions remain incomparable even for frequent events.

Unpredictability is similar to rarity in a way. For predicting the final position of a ball at a roulette table, similar questions in the quality of individual predictions arise.

For your random pixel generator, it is practically impossible to ever show a specific cat picture. But if you take any random picture that your generator already has generated, the likelihood for generating that random image again is still the same as for generating your cat photo. And it was the same as for your cat picture even before. So every time your generator creates a random image, it creates something that was practically impossible to happen a moment before, according to statistics. So observing anything happening does not allow use to say it was likely to happen because it happened.

We can also trivially find events that are even less likely than your cat photo generator, by using a generator with more pixels, as an example. We can find examples that are more likely, by using a generator with fewer pixels. If we observe some rare event in our lives, then without further knowledge it would seem rational to assume we might observe it again, but again, every time we observe your generator generating a random image, we can be sure we'll never see that same image again, our knowledge of the space of possibilities is just as important as observation of events.

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  • What you mean as disagreement is a situation as follows? In Event 2, for robbery case let’s say Person A is waiting a bus in front of a bank office. He knows that likelihood of attempting a bank robbery for him is 0%, impossible. There is no reason at all for him to do such action as he isn't an immoral person and he isn't mad either psychopath. He's looking forward to arriving home, having dinner with his beautiful wife and lovely children etc. However there is also Person B who is passing by the bank.
    – Geerts
    May 22 at 10:00
  • For Person B, Person A is a complete stranger. When asked Person B, I think he cannot say Person A’s likelihood of commit such crime is 0%. He doesn’t know him, he cannot rule out statistical bank robbery cases. Thus Person B will give a different likelihood, not 0%. I hope my example is clear. We can change the subject Person A with ourselves to stress that ‘It won’t happen because I know’. How do you explain such phenomenon? Which perspective of likelihood is correct? Apologies for giving such disturbing example, this is just mathematical/philosophical discussion in relation to the topic.
    – Geerts
    May 22 at 10:03
  • Those are estimates under different knowledge. It would be usually much more surprising if in such an situation were exactly the same. However if the people involved exchanged a lot of knowledge and opinions, we can expect their estimates to approach each other. However, their combined estimate might still be far off a scientific estimate done by experts. Untrained humans are overall incredibly bad at statistical judgement.
    – tkruse
    May 22 at 13:36
  • It's clear to me that untrained humans are overall bad at such judgements. I see from your reply that indeed there is one correct likelihood judgement. Your reply is appreciated but I'm still struggling with finding answers. Is it then possible that Person A's judgement which is 0% hence impossible can be the correct one? Relating to my original post can likelihood of Event 2 be lower than Event 1 which is so extremely small?
    – Geerts
    May 22 at 14:56
  • So individual estimates cannot be correct or incorrect before the event. Regarding tomorrow's weather over New York at 1pm local time, one forecast might give a probability of rain of 10%, another at 20%. Neither can be defined usefully as more correct than the other. Only the underlying methods of prediction can be judged after observing them for many days, counting their success. But even if we find one method has better success over 100 days, that does not mean it provides necessarily a better prediction for the next day. It's impossible to define such quality criteria for single estimates.
    – tkruse
    May 22 at 23:58

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