I’m interested in developing the skill to estimate probabilities for real-world situations. What are the best ways to learn this systematically? Are there books, courses, or exercises that teach probabilistic thinking, Bayesian reasoning, or practical forecasting skills?
I want to check this math and see if the AI is gaslighting me.
When in doubt, the AI is gaslighting you.
When you’re sure, the AI is still probably gaslighting you.
What you’re interested in is actuarial science. It’s an interesting and complex field. Pretty much every insurance company is built on the backs of a few talented actuaries.
It kind of depends on if there is anything specific you want to try and forecast. That said, a lot to data scientists would probably point to Bayesian statistics
50/50
It either happens, or it doesn’t. So easy, next question pls.
Two outcomes does not mean 50/50 chances. Maybe you were being sarcastic about that, but people actually use that reasoning in the real world all the time.
Predictions are hard, especially about the future.
You don’t say exactly what you want to predict so it’s hard to say exactly what you need to learn. The link returns an error to me.
If you want to predict the next economic crash you’ll have to study a lot of economics. If you want to predict the next pandemic you’ll have to study medicine etc. Years of study no matter what.
Once you know a lot about a topic you have to put a ton of effort into study current events and still be wrong a lot of the time.
This is not an ability the Jedi of Lemmy will ever teach you.
Seeing as 9-11 only happened once in the past few thousand years, the AI odds check out.
I’ve heard podcasts about super forecasters, but haven’t come across a systemic way to learn about this. But knowing a name used for this might help in your search
Ignoring the AI part, since it doesn’t even know it’s gaslighting you.
Maybe read some Buckminster Fuller. He opined to some length about trends in real-world changes.
Isaac Asimov as well, just for a general sense of the approach.
But overall probabilities are kinda arbitrary when applied to specific events. They work fine for a whole lot of similar events (e.g. pulling colored marbles out of a bag) but they don’t really have any tangible meaning for unique events. Either you guess wrong or you guess right.
If you want to predict future events, you need to have a good grasp on current events, past events, and systemic behavior in general. There isn’t one methodology that yields results generally. You need to tailor your approach to suit each prediction.
That’s not something you can learn from one book, course, or series of exercises. It relies on broad scholarship.
For one off events like 9/11, you can’t. There isn’t an accepted definition of “probability” for things like that. Either The question is completely nonsensical (Frequentist view) or the numbers are more or less all arbitrary (Bayesian view).
Prediction markets are a thing…
Generally yes there is TONS of theories and methods relating to forecasting and prediction. Its a very interesting field.
What was the link to? Cant seem to work for me.
Oh and just fyi AI models as most know them only run through outout as highest likely to be following a given chain, all based on trained data. The closest you can get to real “math” would be training a model to context strip metadata from an input, to very specific output, use that to input data into a database, have an actual program do the math or call relevant statistics, peform the calc then give the output. Buuuuut that is pretty much not done at all by anyone beyond custom written systems for specific use cases, and any forward facing companies having AI models arent much doing that, the output is a fluke.
